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Created May 22, 2022 01:31
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BasketballRefClustering.ipynb
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basketballrefclustering.ipynb
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{
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"source": [
"import pandas as pd"
]
},
{
"cell_type": "code",
"source": [
"#load data\n",
"url = 'https://www.basketball-reference.com/leagues/NBA_2022_per_poss.html#per_poss_stats::7' #From get table as link feature\n",
"df = pd.read_html(url)[0]\n",
"display(df)"
],
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" Rk Player Pos Age Tm G GS MP FG FGA ... TRB \\\n",
"0 1 Precious Achiuwa C 22 TOR 73 28 1725 7.7 17.5 ... 13.7 \n",
"1 2 Steven Adams C 28 MEM 76 75 1999 5.0 9.2 ... 18.2 \n",
"2 3 Bam Adebayo C 24 MIA 56 56 1825 11.1 20.0 ... 15.5 \n",
"3 4 Santi Aldama PF 21 MEM 32 0 360 7.0 17.5 ... 11.6 \n",
"4 5 LaMarcus Aldridge C 36 BRK 47 12 1050 11.6 21.1 ... 11.9 \n",
".. ... ... .. .. ... .. .. ... ... ... ... ... \n",
"837 601 Thaddeus Young PF 33 TOR 26 0 475 7.1 15.2 ... 12.1 \n",
"838 602 Trae Young PG 23 ATL 76 76 2652 13.2 28.6 ... 5.3 \n",
"839 603 Omer Yurtseven C 23 MIA 56 12 706 9.2 17.5 ... 20.8 \n",
"840 604 Cody Zeller C 29 POR 27 0 355 7.0 12.4 ... 17.2 \n",
"841 605 Ivica Zubac C 24 LAC 76 76 1852 8.2 13.1 ... 17.0 \n",
"\n",
" AST STL BLK TOV PF PTS Unnamed: 29 ORtg DRtg \n",
"0 2.4 1.1 1.2 2.4 4.4 19.2 NaN 105 110 \n",
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"3 2.8 0.8 1.3 2.1 4.8 17.5 NaN 101 111 \n",
"4 1.9 0.6 2.2 2.0 3.6 28.0 NaN 119 112 \n",
".. ... ... ... ... ... ... ... ... ... \n",
"837 4.7 3.3 1.2 2.3 4.5 17.3 NaN 113 106 \n",
"838 13.7 1.3 0.1 5.6 2.4 39.9 NaN 119 118 \n",
"839 3.5 1.2 1.4 2.9 6.0 21.2 NaN 112 104 \n",
"840 3.0 1.1 0.8 2.6 7.7 19.3 NaN 127 116 \n",
"841 3.2 1.0 2.0 3.0 5.4 20.8 NaN 126 107 \n",
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" <td>Cody Zeller</td>\n",
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" <td>POR</td>\n",
" <td>27</td>\n",
" <td>0</td>\n",
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{
"cell_type": "code",
"source": [
"#Need to get rid of the repeat line\n",
"df = df[df['Player'] != 'Player']"
],
"metadata": {
"id": "U8m7TeM14nC3"
},
"execution_count": 30,
"outputs": []
},
{
"cell_type": "code",
"source": [
"#See the data types\n",
"df.info()\n",
"#I shortened the output but basically some are objects"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "rWVyGM9U1mHa",
"outputId": "e491d76f-74ca-448a-eabd-a9979bf9fa9d"
},
"execution_count": 31,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"<class 'pandas.core.frame.DataFrame'>\n",
"Int64Index: 812 entries, 0 to 841\n",
"Data columns (total 32 columns):\n",
" # Column Non-Null Count Dtype \n",
"--- ------ -------------- ----- \n",
" 0 Rk 812 non-null object \n",
" 1 Player 812 non-null object \n",
" 2 Pos 812 non-null object \n",
" 3 Age 812 non-null object \n",
" 4 Tm 812 non-null object \n",
" 5 G 812 non-null object \n",
" 6 GS 812 non-null object \n",
" 7 MP 812 non-null object \n",
" 8 FG 812 non-null object \n",
" 9 FGA 812 non-null object \n",
" 10 FG% 797 non-null object \n",
" 11 3P 812 non-null object \n",
" 12 3PA 812 non-null object \n",
" 13 3P% 740 non-null object \n",
" 14 2P 812 non-null object \n",
" 15 2PA 812 non-null object \n",
" 16 2P% 784 non-null object \n",
" 17 FT 812 non-null object \n",
" 18 FTA 812 non-null object \n",
" 19 FT% 715 non-null object \n",
" 20 ORB 812 non-null object \n",
" 21 DRB 812 non-null object \n",
" 22 TRB 812 non-null object \n",
" 23 AST 812 non-null object \n",
" 24 STL 812 non-null object \n",
" 25 BLK 812 non-null object \n",
" 26 TOV 812 non-null object \n",
" 27 PF 812 non-null object \n",
" 28 PTS 812 non-null object \n",
" 29 Unnamed: 29 0 non-null float64\n",
" 30 ORtg 802 non-null object \n",
" 31 DRtg 812 non-null object \n",
"dtypes: float64(1), object(31)\n",
"memory usage: 209.3+ KB\n"
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{
"cell_type": "code",
"source": [
"#Converting to float\n",
"cols = [\n",
" 'Age', \n",
" 'G', \n",
" 'GS', \n",
" 'MP', \n",
" 'FG', \n",
" 'FGA', \n",
" 'FG%', \n",
" '3P', \n",
" '3PA', \n",
" '3P%', \n",
" '2P', \n",
" '2PA', \n",
" '2P%', \n",
" 'FT', \n",
" 'FTA', \n",
" 'FT%', \n",
" 'ORB', \n",
" 'DRB', \n",
" 'TRB', \n",
" 'AST', \n",
" 'STL', \n",
" 'BLK', \n",
" 'TOV', \n",
" 'PF', \n",
" 'PTS', \n",
" 'ORtg', \n",
" 'DRtg']\n",
"\n",
"for col in cols:\n",
" df[col] = pd.to_numeric(df[col])"
],
"metadata": {
"id": "f3nBcoNF1s8X"
},
"execution_count": 32,
"outputs": []
},
{
"cell_type": "code",
"source": [
"#See what the data generally looks like\n",
"df.describe(include = 'all')"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 522
},
"id": "ZdHg1pJm1KHe",
"outputId": "30eb4095-0811-4248-dda8-0803274d43f7"
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},
"metadata": {},
"execution_count": 33
}
]
},
{
"cell_type": "code",
"source": [
"#Filter out low minutes players (arbitrarily defined as players who are 1.5 standard deviations below average)\n",
"df = df[df['MP'] >= (825.188-1.5*5.67)]\n",
"df"
],
"metadata": {
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"height": 424
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"id": "HH4__fU05Itq",
"outputId": "db52f789-f8c5-4d06-f631-29f0c9f9786d"
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"execution_count": 34,
"outputs": [
{
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" Rk Player Pos Age Tm G GS MP FG FGA \\\n",
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" <td>2.4</td>\n",
" <td>4.4</td>\n",
" <td>19.2</td>\n",
" <td>NaN</td>\n",
" <td>105.0</td>\n",
" <td>110</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>2</td>\n",
" <td>Steven Adams</td>\n",
" <td>C</td>\n",
" <td>28</td>\n",
" <td>MEM</td>\n",
" <td>76</td>\n",
" <td>75</td>\n",
" <td>1999</td>\n",
" <td>5.0</td>\n",
" <td>9.2</td>\n",
" <td>...</td>\n",
" <td>18.2</td>\n",
" <td>6.1</td>\n",
" <td>1.6</td>\n",
" <td>1.4</td>\n",
" <td>2.8</td>\n",
" <td>3.7</td>\n",
" <td>12.6</td>\n",
" <td>NaN</td>\n",
" <td>125.0</td>\n",
" <td>108</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>3</td>\n",
" <td>Bam Adebayo</td>\n",
" <td>C</td>\n",
" <td>24</td>\n",
" <td>MIA</td>\n",
" <td>56</td>\n",
" <td>56</td>\n",
" <td>1825</td>\n",
" <td>11.1</td>\n",
" <td>20.0</td>\n",
" <td>...</td>\n",
" <td>15.5</td>\n",
" <td>5.2</td>\n",
" <td>2.2</td>\n",
" <td>1.2</td>\n",
" <td>4.1</td>\n",
" <td>4.7</td>\n",
" <td>29.3</td>\n",
" <td>NaN</td>\n",
" <td>117.0</td>\n",
" <td>104</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>5</td>\n",
" <td>LaMarcus Aldridge</td>\n",
" <td>C</td>\n",
" <td>36</td>\n",
" <td>BRK</td>\n",
" <td>47</td>\n",
" <td>12</td>\n",
" <td>1050</td>\n",
" <td>11.6</td>\n",
" <td>21.1</td>\n",
" <td>...</td>\n",
" <td>11.9</td>\n",
" <td>1.9</td>\n",
" <td>0.6</td>\n",
" <td>2.2</td>\n",
" <td>2.0</td>\n",
" <td>3.6</td>\n",
" <td>28.0</td>\n",
" <td>NaN</td>\n",
" <td>119.0</td>\n",
" <td>112</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5</th>\n",
" <td>6</td>\n",
" <td>Nickeil Alexander-Walker</td>\n",
" <td>SG</td>\n",
" <td>23</td>\n",
" <td>TOT</td>\n",
" <td>65</td>\n",
" <td>21</td>\n",
" <td>1466</td>\n",
" <td>8.5</td>\n",
" <td>22.9</td>\n",
" <td>...</td>\n",
" <td>6.3</td>\n",
" <td>5.3</td>\n",
" <td>1.5</td>\n",
" <td>0.8</td>\n",
" <td>3.1</td>\n",
" <td>3.5</td>\n",
" <td>23.3</td>\n",
" <td>NaN</td>\n",
" <td>98.0</td>\n",
" <td>114</td>\n",
" </tr>\n",
" <tr>\n",
" <th>...</th>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>826</th>\n",
" <td>595</td>\n",
" <td>Christian Wood</td>\n",
" <td>C</td>\n",
" <td>26</td>\n",
" <td>HOU</td>\n",
" <td>68</td>\n",
" <td>67</td>\n",
" <td>2094</td>\n",
" <td>10.0</td>\n",
" <td>20.0</td>\n",
" <td>...</td>\n",
" <td>15.6</td>\n",
" <td>3.5</td>\n",
" <td>1.2</td>\n",
" <td>1.5</td>\n",
" <td>2.9</td>\n",
" <td>3.9</td>\n",
" <td>27.7</td>\n",
" <td>NaN</td>\n",
" <td>114.0</td>\n",
" <td>113</td>\n",
" </tr>\n",
" <tr>\n",
" <th>828</th>\n",
" <td>597</td>\n",
" <td>Delon Wright</td>\n",
" <td>SG</td>\n",
" <td>29</td>\n",
" <td>ATL</td>\n",
" <td>77</td>\n",
" <td>8</td>\n",
" <td>1452</td>\n",
" <td>4.1</td>\n",
" <td>9.1</td>\n",
" <td>...</td>\n",
" <td>7.4</td>\n",
" <td>6.4</td>\n",
" <td>3.1</td>\n",
" <td>0.6</td>\n",
" <td>1.5</td>\n",
" <td>1.9</td>\n",
" <td>11.6</td>\n",
" <td>NaN</td>\n",
" <td>126.0</td>\n",
" <td>112</td>\n",
" </tr>\n",
" <tr>\n",
" <th>835</th>\n",
" <td>601</td>\n",
" <td>Thaddeus Young</td>\n",
" <td>PF</td>\n",
" <td>33</td>\n",
" <td>TOT</td>\n",
" <td>52</td>\n",
" <td>1</td>\n",
" <td>845</td>\n",
" <td>8.2</td>\n",
" <td>15.8</td>\n",
" <td>...</td>\n",
" <td>12.1</td>\n",
" <td>6.0</td>\n",
" <td>3.1</td>\n",
" <td>1.0</td>\n",
" <td>3.0</td>\n",
" <td>4.7</td>\n",
" <td>18.7</td>\n",
" <td>NaN</td>\n",
" <td>113.0</td>\n",
" <td>108</td>\n",
" </tr>\n",
" <tr>\n",
" <th>838</th>\n",
" <td>602</td>\n",
" <td>Trae Young</td>\n",
" <td>PG</td>\n",
" <td>23</td>\n",
" <td>ATL</td>\n",
" <td>76</td>\n",
" <td>76</td>\n",
" <td>2652</td>\n",
" <td>13.2</td>\n",
" <td>28.6</td>\n",
" <td>...</td>\n",
" <td>5.3</td>\n",
" <td>13.7</td>\n",
" <td>1.3</td>\n",
" <td>0.1</td>\n",
" <td>5.6</td>\n",
" <td>2.4</td>\n",
" <td>39.9</td>\n",
" <td>NaN</td>\n",
" <td>119.0</td>\n",
" <td>118</td>\n",
" </tr>\n",
" <tr>\n",
" <th>841</th>\n",
" <td>605</td>\n",
" <td>Ivica Zubac</td>\n",
" <td>C</td>\n",
" <td>24</td>\n",
" <td>LAC</td>\n",
" <td>76</td>\n",
" <td>76</td>\n",
" <td>1852</td>\n",
" <td>8.2</td>\n",
" <td>13.1</td>\n",
" <td>...</td>\n",
" <td>17.0</td>\n",
" <td>3.2</td>\n",
" <td>1.0</td>\n",
" <td>2.0</td>\n",
" <td>3.0</td>\n",
" <td>5.4</td>\n",
" <td>20.8</td>\n",
" <td>NaN</td>\n",
" <td>126.0</td>\n",
" <td>107</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>339 rows × 32 columns</p>\n",
"</div>\n",
" <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-d9d4449f-e369-444f-a10b-7ba6c988b408')\"\n",
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" </svg>\n",
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" background-color: #3B4455;\n",
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" background-color: #434B5C;\n",
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" const dataTable =\n",
" await google.colab.kernel.invokeFunction('convertToInteractive',\n",
" [key], {});\n",
" if (!dataTable) return;\n",
"\n",
" const docLinkHtml = 'Like what you see? Visit the ' +\n",
" '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
" + ' to learn more about interactive tables.';\n",
" element.innerHTML = '';\n",
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" const docLink = document.createElement('div');\n",
" docLink.innerHTML = docLinkHtml;\n",
" element.appendChild(docLink);\n",
" }\n",
" </script>\n",
" </div>\n",
" </div>\n",
" "
]
},
"metadata": {},
"execution_count": 34
}
]
},
{
"cell_type": "markdown",
"source": [
"Start Kmeans analysis now that data is semi-clean"
],
"metadata": {
"id": "c3PIENUY_u-n"
}
},
{
"cell_type": "code",
"source": [
"from sklearn.cluster import KMeans"
],
"metadata": {
"id": "2GeTccdL9eAA"
},
"execution_count": 35,
"outputs": []
},
{
"cell_type": "code",
"source": [
"x = pd.DataFrame()\n",
"cols = [\n",
" '3PA', \n",
" '2PA', \n",
" '2P%', \n",
" 'FTA', \n",
" 'ORB', \n",
" 'DRB', \n",
" 'AST', \n",
" 'STL', \n",
" 'BLK', \n",
" 'TOV', \n",
" 'PF', \n",
" 'PTS'] #These are the features I want because I eliminated some collinearity (well at least the intuitive collineartiy)\n",
"for col in cols:\n",
" x[col] = df[col]\n",
"x.head()"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 206
},
"id": "uFsGMxN-_0P5",
"outputId": "99c8ea91-05eb-4ad9-9e6d-90c469190b71"
},
"execution_count": 36,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
" 3PA 2PA 2P% FTA ORB DRB AST STL BLK TOV PF PTS\n",
"0 4.5 13.0 0.468 3.8 4.2 9.5 2.4 1.1 1.2 2.4 4.4 19.2\n",
"1 0.0 9.2 0.548 4.8 8.4 9.8 6.1 1.6 1.4 2.8 3.7 12.6\n",
"2 0.2 19.8 0.562 9.3 3.8 11.7 5.2 2.2 1.2 4.1 4.7 29.3\n",
"4 2.1 19.0 0.578 4.7 3.4 8.5 1.9 0.6 2.2 2.0 3.6 28.0\n",
"5 11.4 11.5 0.433 3.7 1.2 5.1 5.3 1.5 0.8 3.1 3.5 23.3"
],
"text/html": [
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]
},
"metadata": {},
"execution_count": 36
}
]
},
{
"cell_type": "code",
"source": [
"#Need to standardize\n",
"from sklearn.preprocessing import StandardScaler\n",
"#Scale the df\n",
"scaler = StandardScaler()\n",
"x_scaled = pd.DataFrame(scaler.fit_transform(x),columns = x.columns)\n",
"#Check\n",
"x_scaled"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 424
},
"id": "gvDP8wxZAhn6",
"outputId": "ad19201f-565c-43de-fe79-b92a9ade867f"
},
"execution_count": 37,
"outputs": [
{
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"data": {
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" 3PA 2PA 2P% FTA ORB DRB AST \\\n",
"0 -0.703707 0.541970 -0.971234 -0.241697 1.285013 0.946373 -0.923370 \n",
"1 -1.935215 -0.326720 0.193783 0.167570 3.837114 1.056431 0.407110 \n",
"2 -1.880482 2.096468 0.397661 2.009270 1.041956 1.753468 0.083480 \n",
"3 -1.360512 1.913586 0.630664 0.126643 0.798898 0.579511 -1.103165 \n",
"4 1.184605 0.199066 -1.480929 -0.282623 -0.537917 -0.667818 0.119439 \n",
".. ... ... ... ... ... ... ... \n",
"334 0.144665 0.381948 0.514162 1.272590 0.252020 2.267074 -0.527822 \n",
"335 -0.867908 -1.241130 -0.359600 -0.937450 -0.234095 -0.411015 0.514987 \n",
"336 -1.168944 0.541970 0.281159 -0.650963 1.528070 0.175964 0.371151 \n",
"337 1.157238 1.524962 -0.330475 2.377610 -0.720210 -0.961307 3.139989 \n",
"338 -1.935215 0.564831 1.329674 0.658690 2.196478 1.606724 -0.635699 \n",
"\n",
" STL BLK TOV PF PTS \n",
"0 -0.807018 0.291299 -0.195716 0.373290 -0.489053 \n",
"1 0.078351 0.550486 0.178074 -0.220819 -1.519282 \n",
"2 1.140794 0.291299 1.392888 0.627908 1.087510 \n",
"3 -1.692387 1.587235 -0.569505 -0.305692 0.884586 \n",
"4 -0.098723 -0.227075 0.458415 -0.390565 0.150938 \n",
".. ... ... ... ... ... \n",
"334 -0.629944 0.680080 0.271521 -0.051074 0.837758 \n",
"335 2.734458 -0.486263 -1.036741 -1.748528 -1.675377 \n",
"336 2.734458 0.032112 0.364968 0.627908 -0.567100 \n",
"337 -0.452870 -1.134230 2.794597 -1.324165 2.742121 \n",
"338 -0.984092 1.328047 0.364968 1.222017 -0.239300 \n",
"\n",
"[339 rows x 12 columns]"
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]
},
"metadata": {},
"execution_count": 37
}
]
},
{
"cell_type": "code",
"source": [
"#Just noticed I need to fill NaN as 0\n",
"x_scaled.fillna(value=0, inplace = True)\n",
"#Check\n",
"x_scaled"
],
"metadata": {
"colab": {
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"height": 424
},
"id": "9R6Q04bwB0Zg",
"outputId": "74df20eb-ddc6-41c6-ce71-d1a6ba0f3651"
},
"execution_count": 38,
"outputs": [
{
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" 3PA 2PA 2P% FTA ORB DRB AST \\\n",
"0 -0.703707 0.541970 -0.971234 -0.241697 1.285013 0.946373 -0.923370 \n",
"1 -1.935215 -0.326720 0.193783 0.167570 3.837114 1.056431 0.407110 \n",
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"\n",
" STL BLK TOV PF PTS \n",
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" <td>0.252020</td>\n",
" <td>2.267074</td>\n",
" <td>-0.527822</td>\n",
" <td>-0.629944</td>\n",
" <td>0.680080</td>\n",
" <td>0.271521</td>\n",
" <td>-0.051074</td>\n",
" <td>0.837758</td>\n",
" </tr>\n",
" <tr>\n",
" <th>335</th>\n",
" <td>-0.867908</td>\n",
" <td>-1.241130</td>\n",
" <td>-0.359600</td>\n",
" <td>-0.937450</td>\n",
" <td>-0.234095</td>\n",
" <td>-0.411015</td>\n",
" <td>0.514987</td>\n",
" <td>2.734458</td>\n",
" <td>-0.486263</td>\n",
" <td>-1.036741</td>\n",
" <td>-1.748528</td>\n",
" <td>-1.675377</td>\n",
" </tr>\n",
" <tr>\n",
" <th>336</th>\n",
" <td>-1.168944</td>\n",
" <td>0.541970</td>\n",
" <td>0.281159</td>\n",
" <td>-0.650963</td>\n",
" <td>1.528070</td>\n",
" <td>0.175964</td>\n",
" <td>0.371151</td>\n",
" <td>2.734458</td>\n",
" <td>0.032112</td>\n",
" <td>0.364968</td>\n",
" <td>0.627908</td>\n",
" <td>-0.567100</td>\n",
" </tr>\n",
" <tr>\n",
" <th>337</th>\n",
" <td>1.157238</td>\n",
" <td>1.524962</td>\n",
" <td>-0.330475</td>\n",
" <td>2.377610</td>\n",
" <td>-0.720210</td>\n",
" <td>-0.961307</td>\n",
" <td>3.139989</td>\n",
" <td>-0.452870</td>\n",
" <td>-1.134230</td>\n",
" <td>2.794597</td>\n",
" <td>-1.324165</td>\n",
" <td>2.742121</td>\n",
" </tr>\n",
" <tr>\n",
" <th>338</th>\n",
" <td>-1.935215</td>\n",
" <td>0.564831</td>\n",
" <td>1.329674</td>\n",
" <td>0.658690</td>\n",
" <td>2.196478</td>\n",
" <td>1.606724</td>\n",
" <td>-0.635699</td>\n",
" <td>-0.984092</td>\n",
" <td>1.328047</td>\n",
" <td>0.364968</td>\n",
" <td>1.222017</td>\n",
" <td>-0.239300</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>339 rows × 12 columns</p>\n",
"</div>\n",
" <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-45140d44-6495-46d7-a2d4-c367614a6267')\"\n",
" title=\"Convert this dataframe to an interactive table.\"\n",
" style=\"display:none;\">\n",
" \n",
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" <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
" </svg>\n",
" </button>\n",
" \n",
" <style>\n",
" .colab-df-container {\n",
" display:flex;\n",
" flex-wrap:wrap;\n",
" gap: 12px;\n",
" }\n",
"\n",
" .colab-df-convert {\n",
" background-color: #E8F0FE;\n",
" border: none;\n",
" border-radius: 50%;\n",
" cursor: pointer;\n",
" display: none;\n",
" fill: #1967D2;\n",
" height: 32px;\n",
" padding: 0 0 0 0;\n",
" width: 32px;\n",
" }\n",
"\n",
" .colab-df-convert:hover {\n",
" background-color: #E2EBFA;\n",
" box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
" fill: #174EA6;\n",
" }\n",
"\n",
" [theme=dark] .colab-df-convert {\n",
" background-color: #3B4455;\n",
" fill: #D2E3FC;\n",
" }\n",
"\n",
" [theme=dark] .colab-df-convert:hover {\n",
" background-color: #434B5C;\n",
" box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
" filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
" fill: #FFFFFF;\n",
" }\n",
" </style>\n",
"\n",
" <script>\n",
" const buttonEl =\n",
" document.querySelector('#df-45140d44-6495-46d7-a2d4-c367614a6267 button.colab-df-convert');\n",
" buttonEl.style.display =\n",
" google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
"\n",
" async function convertToInteractive(key) {\n",
" const element = document.querySelector('#df-45140d44-6495-46d7-a2d4-c367614a6267');\n",
" const dataTable =\n",
" await google.colab.kernel.invokeFunction('convertToInteractive',\n",
" [key], {});\n",
" if (!dataTable) return;\n",
"\n",
" const docLinkHtml = 'Like what you see? Visit the ' +\n",
" '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
" + ' to learn more about interactive tables.';\n",
" element.innerHTML = '';\n",
" dataTable['output_type'] = 'display_data';\n",
" await google.colab.output.renderOutput(dataTable, element);\n",
" const docLink = document.createElement('div');\n",
" docLink.innerHTML = docLinkHtml;\n",
" element.appendChild(docLink);\n",
" }\n",
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" </div>\n",
" "
]
},
"metadata": {},
"execution_count": 38
}
]
},
{
"cell_type": "code",
"source": [
"import numpy as np\n",
"import matplotlib.pyplot as plt\n",
"#Now just gonna do an elbow plot to find the best cluster count\n",
"distortions = []\n",
"K = range(1,50)\n",
"for k in K:\n",
" kmeanModel = KMeans(n_clusters=k)\n",
" kmeanModel.fit(x_scaled)\n",
" distortions.append(kmeanModel.inertia_)\n",
"#Graph\n",
"plt.figure(figsize=(16,8))\n",
"plt.plot(K, distortions, 'bx-')\n",
"plt.xlabel('k')\n",
"plt.ylabel('Distortion')\n",
"plt.title('The Elbow Method showing the optimal k')\n",
"plt.show()"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 513
},
"id": "6ZBKFsDfBLxl",
"outputId": "6b308e60-f3f9-4a99-b78e-87c63dabaa03"
},
"execution_count": 40,
"outputs": [
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 1152x576 with 1 Axes>"
],
"image/png": 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},
"metadata": {
"needs_background": "light"
}
}
]
},
{
"cell_type": "code",
"source": [
"#23 looks like a good elbow point\n",
"k = KMeans(n_clusters=23)\n",
"clusters = k.fit_predict(x_scaled)\n",
"df_c = df.copy()\n",
"df_c['Clusters'] = clusters \n",
"df_c"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 424
},
"id": "llUYeoXaCyyo",
"outputId": "304feb79-76d0-4812-cf76-3a2386759d8d"
},
"execution_count": 42,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
" Rk Player Pos Age Tm G GS MP FG FGA \\\n",
"0 1 Precious Achiuwa C 22 TOR 73 28 1725 7.7 17.5 \n",
"1 2 Steven Adams C 28 MEM 76 75 1999 5.0 9.2 \n",
"2 3 Bam Adebayo C 24 MIA 56 56 1825 11.1 20.0 \n",
"4 5 LaMarcus Aldridge C 36 BRK 47 12 1050 11.6 21.1 \n",
"5 6 Nickeil Alexander-Walker SG 23 TOT 65 21 1466 8.5 22.9 \n",
".. ... ... .. ... ... .. .. ... ... ... \n",
"826 595 Christian Wood C 26 HOU 68 67 2094 10.0 20.0 \n",
"828 597 Delon Wright SG 29 ATL 77 8 1452 4.1 9.1 \n",
"835 601 Thaddeus Young PF 33 TOT 52 1 845 8.2 15.8 \n",
"838 602 Trae Young PG 23 ATL 76 76 2652 13.2 28.6 \n",
"841 605 Ivica Zubac C 24 LAC 76 76 1852 8.2 13.1 \n",
"\n",
" ... AST STL BLK TOV PF PTS Unnamed: 29 ORtg DRtg Clusters \n",
"0 ... 2.4 1.1 1.2 2.4 4.4 19.2 NaN 105.0 110 16 \n",
"1 ... 6.1 1.6 1.4 2.8 3.7 12.6 NaN 125.0 108 9 \n",
"2 ... 5.2 2.2 1.2 4.1 4.7 29.3 NaN 117.0 104 20 \n",
"4 ... 1.9 0.6 2.2 2.0 3.6 28.0 NaN 119.0 112 21 \n",
"5 ... 5.3 1.5 0.8 3.1 3.5 23.3 NaN 98.0 114 14 \n",
".. ... ... ... ... ... ... ... ... ... ... ... \n",
"826 ... 3.5 1.2 1.5 2.9 3.9 27.7 NaN 114.0 113 7 \n",
"828 ... 6.4 3.1 0.6 1.5 1.9 11.6 NaN 126.0 112 11 \n",
"835 ... 6.0 3.1 1.0 3.0 4.7 18.7 NaN 113.0 108 4 \n",
"838 ... 13.7 1.3 0.1 5.6 2.4 39.9 NaN 119.0 118 5 \n",
"841 ... 3.2 1.0 2.0 3.0 5.4 20.8 NaN 126.0 107 9 \n",
"\n",
"[339 rows x 33 columns]"
],
"text/html": [
"\n",
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" <div class=\"colab-df-container\">\n",
" <div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
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"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Rk</th>\n",
" <th>Player</th>\n",
" <th>Pos</th>\n",
" <th>Age</th>\n",
" <th>Tm</th>\n",
" <th>G</th>\n",
" <th>GS</th>\n",
" <th>MP</th>\n",
" <th>FG</th>\n",
" <th>FGA</th>\n",
" <th>...</th>\n",
" <th>AST</th>\n",
" <th>STL</th>\n",
" <th>BLK</th>\n",
" <th>TOV</th>\n",
" <th>PF</th>\n",
" <th>PTS</th>\n",
" <th>Unnamed: 29</th>\n",
" <th>ORtg</th>\n",
" <th>DRtg</th>\n",
" <th>Clusters</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>1</td>\n",
" <td>Precious Achiuwa</td>\n",
" <td>C</td>\n",
" <td>22</td>\n",
" <td>TOR</td>\n",
" <td>73</td>\n",
" <td>28</td>\n",
" <td>1725</td>\n",
" <td>7.7</td>\n",
" <td>17.5</td>\n",
" <td>...</td>\n",
" <td>2.4</td>\n",
" <td>1.1</td>\n",
" <td>1.2</td>\n",
" <td>2.4</td>\n",
" <td>4.4</td>\n",
" <td>19.2</td>\n",
" <td>NaN</td>\n",
" <td>105.0</td>\n",
" <td>110</td>\n",
" <td>16</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>2</td>\n",
" <td>Steven Adams</td>\n",
" <td>C</td>\n",
" <td>28</td>\n",
" <td>MEM</td>\n",
" <td>76</td>\n",
" <td>75</td>\n",
" <td>1999</td>\n",
" <td>5.0</td>\n",
" <td>9.2</td>\n",
" <td>...</td>\n",
" <td>6.1</td>\n",
" <td>1.6</td>\n",
" <td>1.4</td>\n",
" <td>2.8</td>\n",
" <td>3.7</td>\n",
" <td>12.6</td>\n",
" <td>NaN</td>\n",
" <td>125.0</td>\n",
" <td>108</td>\n",
" <td>9</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>3</td>\n",
" <td>Bam Adebayo</td>\n",
" <td>C</td>\n",
" <td>24</td>\n",
" <td>MIA</td>\n",
" <td>56</td>\n",
" <td>56</td>\n",
" <td>1825</td>\n",
" <td>11.1</td>\n",
" <td>20.0</td>\n",
" <td>...</td>\n",
" <td>5.2</td>\n",
" <td>2.2</td>\n",
" <td>1.2</td>\n",
" <td>4.1</td>\n",
" <td>4.7</td>\n",
" <td>29.3</td>\n",
" <td>NaN</td>\n",
" <td>117.0</td>\n",
" <td>104</td>\n",
" <td>20</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>5</td>\n",
" <td>LaMarcus Aldridge</td>\n",
" <td>C</td>\n",
" <td>36</td>\n",
" <td>BRK</td>\n",
" <td>47</td>\n",
" <td>12</td>\n",
" <td>1050</td>\n",
" <td>11.6</td>\n",
" <td>21.1</td>\n",
" <td>...</td>\n",
" <td>1.9</td>\n",
" <td>0.6</td>\n",
" <td>2.2</td>\n",
" <td>2.0</td>\n",
" <td>3.6</td>\n",
" <td>28.0</td>\n",
" <td>NaN</td>\n",
" <td>119.0</td>\n",
" <td>112</td>\n",
" <td>21</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5</th>\n",
" <td>6</td>\n",
" <td>Nickeil Alexander-Walker</td>\n",
" <td>SG</td>\n",
" <td>23</td>\n",
" <td>TOT</td>\n",
" <td>65</td>\n",
" <td>21</td>\n",
" <td>1466</td>\n",
" <td>8.5</td>\n",
" <td>22.9</td>\n",
" <td>...</td>\n",
" <td>5.3</td>\n",
" <td>1.5</td>\n",
" <td>0.8</td>\n",
" <td>3.1</td>\n",
" <td>3.5</td>\n",
" <td>23.3</td>\n",
" <td>NaN</td>\n",
" <td>98.0</td>\n",
" <td>114</td>\n",
" <td>14</td>\n",
" </tr>\n",
" <tr>\n",
" <th>...</th>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
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" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>826</th>\n",
" <td>595</td>\n",
" <td>Christian Wood</td>\n",
" <td>C</td>\n",
" <td>26</td>\n",
" <td>HOU</td>\n",
" <td>68</td>\n",
" <td>67</td>\n",
" <td>2094</td>\n",
" <td>10.0</td>\n",
" <td>20.0</td>\n",
" <td>...</td>\n",
" <td>3.5</td>\n",
" <td>1.2</td>\n",
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" <td>3.9</td>\n",
" <td>27.7</td>\n",
" <td>NaN</td>\n",
" <td>114.0</td>\n",
" <td>113</td>\n",
" <td>7</td>\n",
" </tr>\n",
" <tr>\n",
" <th>828</th>\n",
" <td>597</td>\n",
" <td>Delon Wright</td>\n",
" <td>SG</td>\n",
" <td>29</td>\n",
" <td>ATL</td>\n",
" <td>77</td>\n",
" <td>8</td>\n",
" <td>1452</td>\n",
" <td>4.1</td>\n",
" <td>9.1</td>\n",
" <td>...</td>\n",
" <td>6.4</td>\n",
" <td>3.1</td>\n",
" <td>0.6</td>\n",
" <td>1.5</td>\n",
" <td>1.9</td>\n",
" <td>11.6</td>\n",
" <td>NaN</td>\n",
" <td>126.0</td>\n",
" <td>112</td>\n",
" <td>11</td>\n",
" </tr>\n",
" <tr>\n",
" <th>835</th>\n",
" <td>601</td>\n",
" <td>Thaddeus Young</td>\n",
" <td>PF</td>\n",
" <td>33</td>\n",
" <td>TOT</td>\n",
" <td>52</td>\n",
" <td>1</td>\n",
" <td>845</td>\n",
" <td>8.2</td>\n",
" <td>15.8</td>\n",
" <td>...</td>\n",
" <td>6.0</td>\n",
" <td>3.1</td>\n",
" <td>1.0</td>\n",
" <td>3.0</td>\n",
" <td>4.7</td>\n",
" <td>18.7</td>\n",
" <td>NaN</td>\n",
" <td>113.0</td>\n",
" <td>108</td>\n",
" <td>4</td>\n",
" </tr>\n",
" <tr>\n",
" <th>838</th>\n",
" <td>602</td>\n",
" <td>Trae Young</td>\n",
" <td>PG</td>\n",
" <td>23</td>\n",
" <td>ATL</td>\n",
" <td>76</td>\n",
" <td>76</td>\n",
" <td>2652</td>\n",
" <td>13.2</td>\n",
" <td>28.6</td>\n",
" <td>...</td>\n",
" <td>13.7</td>\n",
" <td>1.3</td>\n",
" <td>0.1</td>\n",
" <td>5.6</td>\n",
" <td>2.4</td>\n",
" <td>39.9</td>\n",
" <td>NaN</td>\n",
" <td>119.0</td>\n",
" <td>118</td>\n",
" <td>5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>841</th>\n",
" <td>605</td>\n",
" <td>Ivica Zubac</td>\n",
" <td>C</td>\n",
" <td>24</td>\n",
" <td>LAC</td>\n",
" <td>76</td>\n",
" <td>76</td>\n",
" <td>1852</td>\n",
" <td>8.2</td>\n",
" <td>13.1</td>\n",
" <td>...</td>\n",
" <td>3.2</td>\n",
" <td>1.0</td>\n",
" <td>2.0</td>\n",
" <td>3.0</td>\n",
" <td>5.4</td>\n",
" <td>20.8</td>\n",
" <td>NaN</td>\n",
" <td>126.0</td>\n",
" <td>107</td>\n",
" <td>9</td>\n",
" </tr>\n",
" </tbody>\n",
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"<p>339 rows × 33 columns</p>\n",
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},
"metadata": {},
"execution_count": 42
}
]
},
{
"cell_type": "code",
"source": [
"#Analyzing results\n",
"for n in range(0,23):\n",
" display(df_c[df_c['Clusters'] == n])\n",
" display(df_c[df_c['Clusters'] == n].describe())\n",
" print('----\\n\\n')"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 1000
},
"id": "2zRaVpNbIxlj",
"outputId": "ee6d8c19-4436-4145-9d19-fb72b493fada"
},
"execution_count": 43,
"outputs": [
{
"output_type": "display_data",
"data": {
"text/plain": [
" Rk Player Pos Age Tm G GS MP FG FGA ... \\\n",
"18 15 Cole Anthony PG 21 ORL 65 65 2059 8.4 21.4 ... \n",
"83 69 Malcolm Brogdon PG 29 IND 36 36 1206 9.9 22.1 ... \n",
"165 126 Stephen Curry PG 33 GSW 64 64 2211 11.8 27.0 ... \n",
"207 156 Anthony Edwards SG 20 MIN 72 72 2466 10.6 24.0 ... \n",
"255 184 Darius Garland PG 22 CLE 68 68 2430 11.1 24.1 ... \n",
"320 236 Tyler Herro SG 22 MIA 66 10 2151 11.7 26.1 ... \n",
"369 266 Kyrie Irving PG 29 BRK 29 29 1091 12.8 27.4 ... \n",
"380 273 Reggie Jackson SG 31 LAC 75 75 2337 10.0 25.6 ... \n",
"468 332 Damian Lillard PG 31 POR 29 29 1056 10.3 25.5 ... \n",
"508 362 CJ McCollum SG 30 TOT 62 62 2145 12.3 26.6 ... \n",
"510 362 CJ McCollum SG 30 NOP 26 26 878 13.8 28.1 ... \n",
"525 377 Khris Middleton SF 30 MIL 66 66 2141 10.1 22.9 ... \n",
"534 383 Donovan Mitchell SG 25 UTA 67 67 2266 13.5 30.0 ... \n",
"604 439 Cameron Payne PG 27 PHO 58 12 1278 9.0 22.1 ... \n",
"618 450 Jordan Poole SG 22 GSW 76 51 2283 10.1 22.6 ... \n",
"619 451 Kevin Porter Jr. PG 21 HOU 61 61 1907 8.4 20.2 ... \n",
"669 486 D'Angelo Russell PG 25 MIN 65 65 2077 9.2 22.3 ... \n",
"681 493 Dennis Schröder SG-PG 28 TOT 64 29 1837 8.4 19.4 ... \n",
"775 554 Fred VanVleet PG 27 TOR 65 65 2462 9.0 22.3 ... \n",
"\n",
" AST STL BLK TOV PF PTS Unnamed: 29 ORtg DRtg Clusters \n",
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"207 5.3 2.0 0.9 3.7 3.2 29.6 NaN 108.0 112 0 \n",
"255 12.0 1.8 0.1 5.1 2.4 30.3 NaN 112.0 112 0 \n",
"320 6.1 1.0 0.2 4.0 2.2 31.8 NaN 107.0 111 0 \n",
"369 7.4 1.8 0.8 3.2 3.6 35.4 NaN 117.0 114 0 \n",
"380 7.5 1.2 0.3 3.6 3.3 26.5 NaN 99.0 113 0 \n",
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"618 6.5 1.3 0.5 4.0 4.4 30.0 NaN 112.0 110 0 \n",
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" <td>PG</td>\n",
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" <td>NaN</td>\n",
" <td>116.0</td>\n",
" <td>118</td>\n",
" <td>0</td>\n",
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" <th>165</th>\n",
" <td>126</td>\n",
" <td>Stephen Curry</td>\n",
" <td>PG</td>\n",
" <td>33</td>\n",
" <td>GSW</td>\n",
" <td>64</td>\n",
" <td>64</td>\n",
" <td>2211</td>\n",
" <td>11.8</td>\n",
" <td>27.0</td>\n",
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" <td>8.9</td>\n",
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" <td>115.0</td>\n",
" <td>108</td>\n",
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" <th>207</th>\n",
" <td>156</td>\n",
" <td>Anthony Edwards</td>\n",
" <td>SG</td>\n",
" <td>20</td>\n",
" <td>MIN</td>\n",
" <td>72</td>\n",
" <td>72</td>\n",
" <td>2466</td>\n",
" <td>10.6</td>\n",
" <td>24.0</td>\n",
" <td>...</td>\n",
" <td>5.3</td>\n",
" <td>2.0</td>\n",
" <td>0.9</td>\n",
" <td>3.7</td>\n",
" <td>3.2</td>\n",
" <td>29.6</td>\n",
" <td>NaN</td>\n",
" <td>108.0</td>\n",
" <td>112</td>\n",
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" <th>255</th>\n",
" <td>184</td>\n",
" <td>Darius Garland</td>\n",
" <td>PG</td>\n",
" <td>22</td>\n",
" <td>CLE</td>\n",
" <td>68</td>\n",
" <td>68</td>\n",
" <td>2430</td>\n",
" <td>11.1</td>\n",
" <td>24.1</td>\n",
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" <td>112.0</td>\n",
" <td>112</td>\n",
" <td>0</td>\n",
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" <tr>\n",
" <th>320</th>\n",
" <td>236</td>\n",
" <td>Tyler Herro</td>\n",
" <td>SG</td>\n",
" <td>22</td>\n",
" <td>MIA</td>\n",
" <td>66</td>\n",
" <td>10</td>\n",
" <td>2151</td>\n",
" <td>11.7</td>\n",
" <td>26.1</td>\n",
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" <td>6.1</td>\n",
" <td>1.0</td>\n",
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" <td>2.2</td>\n",
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" <td>NaN</td>\n",
" <td>107.0</td>\n",
" <td>111</td>\n",
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" <td>117.0</td>\n",
" <td>114</td>\n",
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" <td>75</td>\n",
" <td>75</td>\n",
" <td>2337</td>\n",
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" <td>99.0</td>\n",
" <td>113</td>\n",
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" <td>29</td>\n",
" <td>29</td>\n",
" <td>1056</td>\n",
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" <td>25.5</td>\n",
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" <td>NaN</td>\n",
" <td>112.0</td>\n",
" <td>120</td>\n",
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" <td>62</td>\n",
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" <td>114</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>525</th>\n",
" <td>377</td>\n",
" <td>Khris Middleton</td>\n",
" <td>SF</td>\n",
" <td>30</td>\n",
" <td>MIL</td>\n",
" <td>66</td>\n",
" <td>66</td>\n",
" <td>2141</td>\n",
" <td>10.1</td>\n",
" <td>22.9</td>\n",
" <td>...</td>\n",
" <td>8.0</td>\n",
" <td>1.7</td>\n",
" <td>0.4</td>\n",
" <td>4.3</td>\n",
" <td>3.6</td>\n",
" <td>29.7</td>\n",
" <td>NaN</td>\n",
" <td>112.0</td>\n",
" <td>112</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>534</th>\n",
" <td>383</td>\n",
" <td>Donovan Mitchell</td>\n",
" <td>SG</td>\n",
" <td>25</td>\n",
" <td>UTA</td>\n",
" <td>67</td>\n",
" <td>67</td>\n",
" <td>2266</td>\n",
" <td>13.5</td>\n",
" <td>30.0</td>\n",
" <td>...</td>\n",
" <td>7.8</td>\n",
" <td>2.2</td>\n",
" <td>0.3</td>\n",
" <td>4.4</td>\n",
" <td>3.6</td>\n",
" <td>37.8</td>\n",
" <td>NaN</td>\n",
" <td>114.0</td>\n",
" <td>111</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>604</th>\n",
" <td>439</td>\n",
" <td>Cameron Payne</td>\n",
" <td>PG</td>\n",
" <td>27</td>\n",
" <td>PHO</td>\n",
" <td>58</td>\n",
" <td>12</td>\n",
" <td>1278</td>\n",
" <td>9.0</td>\n",
" <td>22.1</td>\n",
" <td>...</td>\n",
" <td>10.6</td>\n",
" <td>1.5</td>\n",
" <td>0.6</td>\n",
" <td>3.9</td>\n",
" <td>4.5</td>\n",
" <td>23.6</td>\n",
" <td>NaN</td>\n",
" <td>104.0</td>\n",
" <td>109</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>618</th>\n",
" <td>450</td>\n",
" <td>Jordan Poole</td>\n",
" <td>SG</td>\n",
" <td>22</td>\n",
" <td>GSW</td>\n",
" <td>76</td>\n",
" <td>51</td>\n",
" <td>2283</td>\n",
" <td>10.1</td>\n",
" <td>22.6</td>\n",
" <td>...</td>\n",
" <td>6.5</td>\n",
" <td>1.3</td>\n",
" <td>0.5</td>\n",
" <td>4.0</td>\n",
" <td>4.4</td>\n",
" <td>30.0</td>\n",
" <td>NaN</td>\n",
" <td>112.0</td>\n",
" <td>110</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>619</th>\n",
" <td>451</td>\n",
" <td>Kevin Porter Jr.</td>\n",
" <td>PG</td>\n",
" <td>21</td>\n",
" <td>HOU</td>\n",
" <td>61</td>\n",
" <td>61</td>\n",
" <td>1907</td>\n",
" <td>8.4</td>\n",
" <td>20.2</td>\n",
" <td>...</td>\n",
" <td>9.4</td>\n",
" <td>1.7</td>\n",
" <td>0.5</td>\n",
" <td>4.8</td>\n",
" <td>3.9</td>\n",
" <td>23.7</td>\n",
" <td>NaN</td>\n",
" <td>103.0</td>\n",
" <td>117</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>669</th>\n",
" <td>486</td>\n",
" <td>D'Angelo Russell</td>\n",
" <td>PG</td>\n",
" <td>25</td>\n",
" <td>MIN</td>\n",
" <td>65</td>\n",
" <td>65</td>\n",
" <td>2077</td>\n",
" <td>9.2</td>\n",
" <td>22.3</td>\n",
" <td>...</td>\n",
" <td>10.5</td>\n",
" <td>1.4</td>\n",
" <td>0.5</td>\n",
" <td>3.8</td>\n",
" <td>3.0</td>\n",
" <td>26.9</td>\n",
" <td>NaN</td>\n",
" <td>112.0</td>\n",
" <td>115</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>681</th>\n",
" <td>493</td>\n",
" <td>Dennis Schröder</td>\n",
" <td>SG-PG</td>\n",
" <td>28</td>\n",
" <td>TOT</td>\n",
" <td>64</td>\n",
" <td>29</td>\n",
" <td>1837</td>\n",
" <td>8.4</td>\n",
" <td>19.4</td>\n",
" <td>...</td>\n",
" <td>7.9</td>\n",
" <td>1.4</td>\n",
" <td>0.2</td>\n",
" <td>3.8</td>\n",
" <td>4.1</td>\n",
" <td>23.2</td>\n",
" <td>NaN</td>\n",
" <td>107.0</td>\n",
" <td>112</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>775</th>\n",
" <td>554</td>\n",
" <td>Fred VanVleet</td>\n",
" <td>PG</td>\n",
" <td>27</td>\n",
" <td>TOR</td>\n",
" <td>65</td>\n",
" <td>65</td>\n",
" <td>2462</td>\n",
" <td>9.0</td>\n",
" <td>22.3</td>\n",
" <td>...</td>\n",
" <td>8.8</td>\n",
" <td>2.3</td>\n",
" <td>0.7</td>\n",
" <td>3.5</td>\n",
" <td>3.3</td>\n",
" <td>26.8</td>\n",
" <td>NaN</td>\n",
" <td>115.0</td>\n",
" <td>111</td>\n",
" <td>0</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>19 rows × 33 columns</p>\n",
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" Age G GS MP FG FGA \\\n",
"count 19.000000 19.000000 19.000000 19.000000 19.000000 19.000000 \n",
"mean 26.473684 58.631579 50.105263 1909.526316 10.547368 24.194737 \n",
"std 4.101062 15.889236 21.413637 527.323785 1.704037 2.859385 \n",
"min 20.000000 26.000000 10.000000 878.000000 8.400000 19.400000 \n",
"25% 22.000000 59.500000 29.000000 1557.500000 9.100000 22.200000 \n",
"50% 27.000000 65.000000 62.000000 2141.000000 10.100000 24.000000 \n",
"75% 30.000000 66.500000 65.500000 2274.500000 11.750000 26.350000 \n",
"max 33.000000 76.000000 75.000000 2466.000000 13.800000 30.000000 \n",
"\n",
" FG% 3P 3PA 3P% ... AST STL \\\n",
"count 19.000000 19.000000 19.000000 19.000000 ... 19.000000 19.000000 \n",
"mean 0.434211 3.947368 10.831579 0.362263 ... 8.394737 1.568421 \n",
"std 0.028071 0.952989 2.379321 0.028734 ... 1.637231 0.409678 \n",
"min 0.391000 2.300000 6.700000 0.312000 ... 5.300000 0.800000 \n",
"25% 0.410000 3.550000 9.500000 0.339000 ... 7.450000 1.250000 \n",
"50% 0.441000 4.000000 10.600000 0.364000 ... 8.500000 1.600000 \n",
"75% 0.448000 4.350000 12.150000 0.381500 ... 9.150000 1.850000 \n",
"max 0.493000 6.300000 16.500000 0.418000 ... 12.000000 2.300000 \n",
"\n",
" BLK TOV PF PTS Unnamed: 29 ORtg \\\n",
"count 19.000000 19.000000 19.000000 19.000000 0.0 19.000000 \n",
"mean 0.452632 3.873684 3.257895 29.631579 NaN 110.263158 \n",
"std 0.219516 0.576235 0.755216 4.422173 NaN 5.183758 \n",
"min 0.100000 2.900000 1.700000 23.200000 NaN 99.000000 \n",
"25% 0.300000 3.550000 2.850000 26.650000 NaN 107.000000 \n",
"50% 0.500000 3.800000 3.300000 29.700000 NaN 112.000000 \n",
"75% 0.550000 4.150000 3.750000 32.000000 NaN 114.500000 \n",
"max 0.900000 5.100000 4.500000 37.800000 NaN 117.000000 \n",
"\n",
" DRtg Clusters \n",
"count 19.000000 19.0 \n",
"mean 113.157895 0.0 \n",
"std 3.149306 0.0 \n",
"min 108.000000 0.0 \n",
"25% 111.000000 0.0 \n",
"50% 112.000000 0.0 \n",
"75% 114.500000 0.0 \n",
"max 120.000000 0.0 \n",
"\n",
"[8 rows x 29 columns]"
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" <th></th>\n",
" <th>Age</th>\n",
" <th>G</th>\n",
" <th>GS</th>\n",
" <th>MP</th>\n",
" <th>FG</th>\n",
" <th>FGA</th>\n",
" <th>FG%</th>\n",
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" <th>count</th>\n",
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" <td>19.000000</td>\n",
" <td>19.000000</td>\n",
" <td>19.000000</td>\n",
" <td>19.000000</td>\n",
" <td>19.000000</td>\n",
" <td>19.000000</td>\n",
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" <td>19.000000</td>\n",
" <td>19.000000</td>\n",
" <td>19.000000</td>\n",
" <td>19.000000</td>\n",
" <td>19.000000</td>\n",
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" <td>19.000000</td>\n",
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" <td>10.547368</td>\n",
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" <td>3.947368</td>\n",
" <td>10.831579</td>\n",
" <td>0.362263</td>\n",
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" <td>8.394737</td>\n",
" <td>1.568421</td>\n",
" <td>0.452632</td>\n",
" <td>3.873684</td>\n",
" <td>3.257895</td>\n",
" <td>29.631579</td>\n",
" <td>NaN</td>\n",
" <td>110.263158</td>\n",
" <td>113.157895</td>\n",
" <td>0.0</td>\n",
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" <td>21.413637</td>\n",
" <td>527.323785</td>\n",
" <td>1.704037</td>\n",
" <td>2.859385</td>\n",
" <td>0.028071</td>\n",
" <td>0.952989</td>\n",
" <td>2.379321</td>\n",
" <td>0.028734</td>\n",
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" <td>1.637231</td>\n",
" <td>0.409678</td>\n",
" <td>0.219516</td>\n",
" <td>0.576235</td>\n",
" <td>0.755216</td>\n",
" <td>4.422173</td>\n",
" <td>NaN</td>\n",
" <td>5.183758</td>\n",
" <td>3.149306</td>\n",
" <td>0.0</td>\n",
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" <th>min</th>\n",
" <td>20.000000</td>\n",
" <td>26.000000</td>\n",
" <td>10.000000</td>\n",
" <td>878.000000</td>\n",
" <td>8.400000</td>\n",
" <td>19.400000</td>\n",
" <td>0.391000</td>\n",
" <td>2.300000</td>\n",
" <td>6.700000</td>\n",
" <td>0.312000</td>\n",
" <td>...</td>\n",
" <td>5.300000</td>\n",
" <td>0.800000</td>\n",
" <td>0.100000</td>\n",
" <td>2.900000</td>\n",
" <td>1.700000</td>\n",
" <td>23.200000</td>\n",
" <td>NaN</td>\n",
" <td>99.000000</td>\n",
" <td>108.000000</td>\n",
" <td>0.0</td>\n",
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" <th>25%</th>\n",
" <td>22.000000</td>\n",
" <td>59.500000</td>\n",
" <td>29.000000</td>\n",
" <td>1557.500000</td>\n",
" <td>9.100000</td>\n",
" <td>22.200000</td>\n",
" <td>0.410000</td>\n",
" <td>3.550000</td>\n",
" <td>9.500000</td>\n",
" <td>0.339000</td>\n",
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" <td>7.450000</td>\n",
" <td>1.250000</td>\n",
" <td>0.300000</td>\n",
" <td>3.550000</td>\n",
" <td>2.850000</td>\n",
" <td>26.650000</td>\n",
" <td>NaN</td>\n",
" <td>107.000000</td>\n",
" <td>111.000000</td>\n",
" <td>0.0</td>\n",
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" <th>50%</th>\n",
" <td>27.000000</td>\n",
" <td>65.000000</td>\n",
" <td>62.000000</td>\n",
" <td>2141.000000</td>\n",
" <td>10.100000</td>\n",
" <td>24.000000</td>\n",
" <td>0.441000</td>\n",
" <td>4.000000</td>\n",
" <td>10.600000</td>\n",
" <td>0.364000</td>\n",
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" <td>8.500000</td>\n",
" <td>1.600000</td>\n",
" <td>0.500000</td>\n",
" <td>3.800000</td>\n",
" <td>3.300000</td>\n",
" <td>29.700000</td>\n",
" <td>NaN</td>\n",
" <td>112.000000</td>\n",
" <td>112.000000</td>\n",
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" <td>66.500000</td>\n",
" <td>65.500000</td>\n",
" <td>2274.500000</td>\n",
" <td>11.750000</td>\n",
" <td>26.350000</td>\n",
" <td>0.448000</td>\n",
" <td>4.350000</td>\n",
" <td>12.150000</td>\n",
" <td>0.381500</td>\n",
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" <td>9.150000</td>\n",
" <td>1.850000</td>\n",
" <td>0.550000</td>\n",
" <td>4.150000</td>\n",
" <td>3.750000</td>\n",
" <td>32.000000</td>\n",
" <td>NaN</td>\n",
" <td>114.500000</td>\n",
" <td>114.500000</td>\n",
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" <td>30.000000</td>\n",
" <td>0.493000</td>\n",
" <td>6.300000</td>\n",
" <td>16.500000</td>\n",
" <td>0.418000</td>\n",
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" <td>12.000000</td>\n",
" <td>2.300000</td>\n",
" <td>0.900000</td>\n",
" <td>5.100000</td>\n",
" <td>4.500000</td>\n",
" <td>37.800000</td>\n",
" <td>NaN</td>\n",
" <td>117.000000</td>\n",
" <td>120.000000</td>\n",
" <td>0.0</td>\n",
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" Rk Player Pos Age Tm G GS MP FG FGA ... \\\n",
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"308 227 Isaiah Hartenstein C 23 LAC 68 0 1216 9.2 14.7 ... \n",
"311 230 Jaxson Hayes C 21 NOP 70 28 1398 8.7 14.1 ... \n",
"363 262 Serge Ibaka C-PF 32 TOT 54 12 877 8.2 16.4 ... \n",
"395 284 James Johnson PF 34 BRK 62 10 1191 5.9 12.5 ... \n",
"409 292 Damian Jones C 26 SAC 56 15 1017 8.3 12.6 ... \n",
"410 293 Derrick Jones Jr. PF 24 CHI 51 8 899 5.7 10.6 ... \n",
"614 446 Mason Plumlee C 31 CHO 73 73 1793 5.5 8.6 ... \n",
"627 457 Dwight Powell C 30 DAL 82 71 1798 7.5 11.2 ... \n",
"647 472 Naz Reid C 22 MIN 77 6 1215 9.1 18.6 ... \n",
"660 480 Isaiah Roby PF 23 OKC 45 28 948 8.5 16.6 ... \n",
"687 497 Alperen Şengün C 19 HOU 72 13 1489 8.0 16.8 ... \n",
"733 525 Jae'Sean Tate SF 26 HOU 78 77 2056 8.4 16.9 ... \n",
"740 532 Daniel Theis C 29 TOT 47 27 977 7.5 14.4 ... \n",
"799 573 Trendon Watford SF 21 POR 48 10 869 8.0 15.0 ... \n",
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" Age G GS MP FG FGA \\\n",
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"75% 31.000000 72.000000 28.000000 1398.000000 8.400000 16.400000 \n",
"max 36.000000 82.000000 77.000000 2056.000000 9.200000 18.600000 \n",
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" FG% 3P 3PA 3P% ... AST STL \\\n",
"count 17.000000 17.000000 17.000000 17.000000 ... 17.000000 17.000000 \n",
"mean 0.543176 1.035294 3.158824 0.296471 ... 3.570588 1.423529 \n",
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"25% 0.489000 0.500000 1.400000 0.266000 ... 2.700000 1.200000 \n",
"50% 0.518000 0.900000 3.300000 0.328000 ... 2.800000 1.400000 \n",
"75% 0.616000 1.500000 5.100000 0.351000 ... 5.100000 1.700000 \n",
"max 0.671000 2.300000 6.500000 0.467000 ... 6.400000 2.000000 \n",
"\n",
" BLK TOV PF PTS Unnamed: 29 ORtg \\\n",
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"std 0.584103 0.813580 0.609846 4.164415 NaN 9.349033 \n",
"min 0.900000 1.400000 5.200000 12.100000 NaN 107.000000 \n",
"25% 1.400000 1.900000 5.700000 15.500000 NaN 113.000000 \n",
"50% 1.700000 2.400000 6.200000 20.200000 NaN 120.000000 \n",
"75% 2.100000 2.800000 6.700000 22.100000 NaN 127.000000 \n",
"max 3.100000 4.600000 7.200000 24.900000 NaN 142.000000 \n",
"\n",
" DRtg Clusters \n",
"count 17.000000 17.0 \n",
"mean 111.529412 1.0 \n",
"std 2.527787 0.0 \n",
"min 106.000000 1.0 \n",
"25% 110.000000 1.0 \n",
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"max 116.000000 1.0 \n",
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" Rk Player Pos Age Tm G GS MP FG FGA ... AST \\\n",
"80 66 Mikal Bridges SF 25 PHO 82 82 2854 7.7 14.5 ... 3.1 \n",
"154 120 Torrey Craig SF 31 TOT 78 16 1596 6.1 13.4 ... 2.8 \n",
"155 120 Torrey Craig SF 31 IND 51 14 1034 6.1 13.3 ... 2.7 \n",
"187 143 Ayo Dosunmu SG 22 CHI 77 40 2110 6.4 12.4 ... 5.9 \n",
"280 208 Jeff Green C 35 DEN 75 63 1849 7.3 14.0 ... 2.5 \n",
"295 219 Maurice Harkless SF 28 SAC 47 24 863 4.6 10.1 ... 1.3 \n",
"401 288 Stanley Johnson PF 25 LAL 48 27 1094 5.1 11.0 ... 3.5 \n",
"460 326 Damion Lee SG 29 GSW 63 5 1256 6.6 14.9 ... 2.4 \n",
"487 346 Terance Mann SF 25 LAC 81 33 2317 7.1 14.6 ... 4.4 \n",
"497 354 Kenyon Martin Jr. SF 21 HOU 79 2 1656 8.0 15.0 ... 2.9 \n",
"512 364 Jaden McDaniels PF 21 MIN 70 31 1803 6.7 14.6 ... 2.1 \n",
"513 365 Jalen McDaniels SF 24 CHO 55 2 895 6.6 13.6 ... 3.1 \n",
"588 423 Isaac Okoro SF 21 CLE 67 61 1981 5.2 10.9 ... 3.1 \n",
"634 461 Taurean Prince PF 27 MIN 69 8 1177 7.2 15.8 ... 2.7 \n",
"641 468 Austin Reaves SG 23 LAL 61 19 1418 4.9 10.7 ... 3.7 \n",
"726 519 Lamar Stevens PF 24 CLE 63 13 1015 7.7 15.7 ... 2.2 \n",
"765 548 P.J. Tucker PF 36 MIA 71 70 1981 5.2 10.8 ... 3.8 \n",
"793 569 P.J. Washington PF 23 CHO 65 28 1768 6.8 14.4 ... 4.0 \n",
"810 581 Aaron Wiggins SG 23 OKC 50 35 1209 6.3 13.6 ... 2.7 \n",
"814 585 Grant Williams PF 23 BOS 77 21 1875 5.4 11.4 ... 2.1 \n",
"\n",
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" if (!dataTable) return;\n",
"\n",
" const docLinkHtml = 'Like what you see? Visit the ' +\n",
" '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
" + ' to learn more about interactive tables.';\n",
" element.innerHTML = '';\n",
" dataTable['output_type'] = 'display_data';\n",
" await google.colab.output.renderOutput(dataTable, element);\n",
" const docLink = document.createElement('div');\n",
" docLink.innerHTML = docLinkHtml;\n",
" element.appendChild(docLink);\n",
" }\n",
" </script>\n",
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" Age G GS MP FG FGA \\\n",
"count 20.000000 20.000000 20.000000 20.000000 20.000000 20.000000 \n",
"mean 25.850000 66.450000 29.700000 1587.550000 6.350000 13.235000 \n",
"std 4.487116 11.459195 23.120053 527.467582 1.010732 1.818118 \n",
"min 21.000000 47.000000 2.000000 863.000000 4.600000 10.100000 \n",
"25% 23.000000 59.500000 13.750000 1156.250000 5.350000 11.300000 \n",
"50% 24.500000 68.000000 25.500000 1626.000000 6.500000 13.600000 \n",
"75% 28.250000 77.000000 36.250000 1901.500000 7.125000 14.600000 \n",
"max 36.000000 82.000000 82.000000 2854.000000 8.000000 15.800000 \n",
"\n",
" FG% 3P 3PA 3P% ... AST STL \\\n",
"count 20.000000 20.000000 20.000000 20.000000 ... 20.000000 20.000000 \n",
"mean 0.479450 1.980000 5.720000 0.345700 ... 3.050000 1.360000 \n",
"std 0.027839 0.613532 1.512614 0.036692 ... 0.994987 0.301575 \n",
"min 0.441000 0.900000 3.200000 0.277000 ... 1.300000 0.700000 \n",
"25% 0.459000 1.600000 4.575000 0.316500 ... 2.475000 1.175000 \n",
"50% 0.472500 1.850000 5.600000 0.343500 ... 2.850000 1.400000 \n",
"75% 0.485250 2.225000 6.650000 0.370750 ... 3.550000 1.500000 \n",
"max 0.534000 3.500000 9.300000 0.415000 ... 5.900000 1.900000 \n",
"\n",
" BLK TOV PF PTS Unnamed: 29 ORtg \\\n",
"count 20.00000 20.000000 20.000000 20.000000 0.0 20.000000 \n",
"mean 0.86500 1.805000 4.210000 16.920000 NaN 114.450000 \n",
"std 0.40946 0.326827 0.801249 2.380093 NaN 6.176995 \n",
"min 0.20000 1.100000 2.500000 12.100000 NaN 101.000000 \n",
"25% 0.60000 1.575000 3.775000 15.450000 NaN 110.750000 \n",
"50% 0.80000 1.800000 4.150000 16.950000 NaN 114.000000 \n",
"75% 1.12500 2.000000 4.725000 18.500000 NaN 119.250000 \n",
"max 1.70000 2.500000 5.900000 20.500000 NaN 125.000000 \n",
"\n",
" DRtg Clusters \n",
"count 20.00000 20.0 \n",
"mean 113.20000 2.0 \n",
"std 2.64774 0.0 \n",
"min 109.00000 2.0 \n",
"25% 111.50000 2.0 \n",
"50% 113.00000 2.0 \n",
"75% 115.00000 2.0 \n",
"max 118.00000 2.0 \n",
"\n",
"[8 rows x 29 columns]"
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"<table border=\"1\" class=\"dataframe\">\n",
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" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Age</th>\n",
" <th>G</th>\n",
" <th>GS</th>\n",
" <th>MP</th>\n",
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" <tr>\n",
" <th>count</th>\n",
" <td>20.000000</td>\n",
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" <td>20.00000</td>\n",
" <td>20.000000</td>\n",
" <td>20.000000</td>\n",
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" <th>mean</th>\n",
" <td>25.850000</td>\n",
" <td>66.450000</td>\n",
" <td>29.700000</td>\n",
" <td>1587.550000</td>\n",
" <td>6.350000</td>\n",
" <td>13.235000</td>\n",
" <td>0.479450</td>\n",
" <td>1.980000</td>\n",
" <td>5.720000</td>\n",
" <td>0.345700</td>\n",
" <td>...</td>\n",
" <td>3.050000</td>\n",
" <td>1.360000</td>\n",
" <td>0.86500</td>\n",
" <td>1.805000</td>\n",
" <td>4.210000</td>\n",
" <td>16.920000</td>\n",
" <td>NaN</td>\n",
" <td>114.450000</td>\n",
" <td>113.20000</td>\n",
" <td>2.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>std</th>\n",
" <td>4.487116</td>\n",
" <td>11.459195</td>\n",
" <td>23.120053</td>\n",
" <td>527.467582</td>\n",
" <td>1.010732</td>\n",
" <td>1.818118</td>\n",
" <td>0.027839</td>\n",
" <td>0.613532</td>\n",
" <td>1.512614</td>\n",
" <td>0.036692</td>\n",
" <td>...</td>\n",
" <td>0.994987</td>\n",
" <td>0.301575</td>\n",
" <td>0.40946</td>\n",
" <td>0.326827</td>\n",
" <td>0.801249</td>\n",
" <td>2.380093</td>\n",
" <td>NaN</td>\n",
" <td>6.176995</td>\n",
" <td>2.64774</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>min</th>\n",
" <td>21.000000</td>\n",
" <td>47.000000</td>\n",
" <td>2.000000</td>\n",
" <td>863.000000</td>\n",
" <td>4.600000</td>\n",
" <td>10.100000</td>\n",
" <td>0.441000</td>\n",
" <td>0.900000</td>\n",
" <td>3.200000</td>\n",
" <td>0.277000</td>\n",
" <td>...</td>\n",
" <td>1.300000</td>\n",
" <td>0.700000</td>\n",
" <td>0.20000</td>\n",
" <td>1.100000</td>\n",
" <td>2.500000</td>\n",
" <td>12.100000</td>\n",
" <td>NaN</td>\n",
" <td>101.000000</td>\n",
" <td>109.00000</td>\n",
" <td>2.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>25%</th>\n",
" <td>23.000000</td>\n",
" <td>59.500000</td>\n",
" <td>13.750000</td>\n",
" <td>1156.250000</td>\n",
" <td>5.350000</td>\n",
" <td>11.300000</td>\n",
" <td>0.459000</td>\n",
" <td>1.600000</td>\n",
" <td>4.575000</td>\n",
" <td>0.316500</td>\n",
" <td>...</td>\n",
" <td>2.475000</td>\n",
" <td>1.175000</td>\n",
" <td>0.60000</td>\n",
" <td>1.575000</td>\n",
" <td>3.775000</td>\n",
" <td>15.450000</td>\n",
" <td>NaN</td>\n",
" <td>110.750000</td>\n",
" <td>111.50000</td>\n",
" <td>2.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>50%</th>\n",
" <td>24.500000</td>\n",
" <td>68.000000</td>\n",
" <td>25.500000</td>\n",
" <td>1626.000000</td>\n",
" <td>6.500000</td>\n",
" <td>13.600000</td>\n",
" <td>0.472500</td>\n",
" <td>1.850000</td>\n",
" <td>5.600000</td>\n",
" <td>0.343500</td>\n",
" <td>...</td>\n",
" <td>2.850000</td>\n",
" <td>1.400000</td>\n",
" <td>0.80000</td>\n",
" <td>1.800000</td>\n",
" <td>4.150000</td>\n",
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" <td>114.000000</td>\n",
" <td>113.00000</td>\n",
" <td>2.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>75%</th>\n",
" <td>28.250000</td>\n",
" <td>77.000000</td>\n",
" <td>36.250000</td>\n",
" <td>1901.500000</td>\n",
" <td>7.125000</td>\n",
" <td>14.600000</td>\n",
" <td>0.485250</td>\n",
" <td>2.225000</td>\n",
" <td>6.650000</td>\n",
" <td>0.370750</td>\n",
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" <td>3.550000</td>\n",
" <td>1.500000</td>\n",
" <td>1.12500</td>\n",
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" <td>4.725000</td>\n",
" <td>18.500000</td>\n",
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" <td>115.00000</td>\n",
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" <th>max</th>\n",
" <td>36.000000</td>\n",
" <td>82.000000</td>\n",
" <td>82.000000</td>\n",
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" <td>1.900000</td>\n",
" <td>1.70000</td>\n",
" <td>2.500000</td>\n",
" <td>5.900000</td>\n",
" <td>20.500000</td>\n",
" <td>NaN</td>\n",
" <td>125.000000</td>\n",
" <td>118.00000</td>\n",
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"</table>\n",
"<p>8 rows × 29 columns</p>\n",
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{
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"text": [
"----\n",
"\n",
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"output_type": "display_data",
"data": {
"text/plain": [
" Rk Player Pos Age Tm G GS MP FG FGA \\\n",
"17 14 Carmelo Anthony PF 37 LAL 69 3 1793 8.5 19.3 \n",
"51 42 Malik Beasley SG 25 MIN 79 18 1976 8.0 20.5 \n",
"60 47 Saddiq Bey SF 22 DET 82 82 2704 8.1 20.5 \n",
"108 85 Alec Burks SG 30 NYK 81 44 2318 6.2 15.7 \n",
"112 89 Kentavious Caldwell-Pope SG 28 WAS 77 77 2329 7.7 17.6 \n",
"120 95 Jevon Carter PG 26 TOT 66 3 905 5.2 13.5 \n",
"139 109 Amir Coffey SG 24 LAC 69 30 1567 6.6 14.6 \n",
"232 171 Bryn Forbes SG 28 TOT 75 2 1286 8.7 20.3 \n",
"251 182 Danilo Gallinari PF 33 ATL 66 18 1672 7.6 17.5 \n",
"291 217 Tim Hardaway Jr. SG 29 DAL 42 20 1245 8.4 21.4 \n",
"301 222 Gary Harris SG 27 ORL 61 30 1730 6.7 15.5 \n",
"337 246 Justin Holiday SF-SG 32 TOT 74 65 2057 6.2 15.7 \n",
"371 268 Frank Jackson PG 23 DET 53 7 1164 8.1 20.2 \n",
"392 281 Cameron Johnson PF 25 PHO 66 16 1730 7.8 16.9 \n",
"426 304 Luke Kennard SG 25 LAC 70 13 1919 7.3 16.3 \n",
"451 321 Jeremy Lamb SF-SG 29 TOT 56 0 935 6.9 18.1 \n",
"490 349 Lauri Markkanen PF 24 CLE 61 61 1878 8.3 18.7 \n",
"514 366 Doug McDermott PF 30 SAS 51 51 1223 8.4 18.2 \n",
"527 379 Patty Mills PG 33 BRK 81 48 2346 6.7 16.4 \n",
"558 399 Trey Murphy III SF 21 NOP 62 1 864 6.2 15.8 \n",
"579 417 Jordan Nwora SF 23 MIL 62 13 1185 7.5 18.7 \n",
"649 474 Josh Richardson SG 28 TOT 65 7 1600 7.2 16.4 \n",
"650 474 Josh Richardson SG 28 BOS 44 0 1087 6.9 15.7 \n",
"689 499 Landry Shamet SG 24 PHO 69 14 1437 6.4 16.2 \n",
"776 555 Devin Vassell SF 21 SAS 71 32 1937 8.1 18.9 \n",
"\n",
" ... AST STL BLK TOV PF PTS Unnamed: 29 ORtg DRtg Clusters \n",
"17 ... 1.8 1.3 1.4 1.6 4.4 24.6 NaN 114.0 114 3 \n",
"51 ... 2.8 1.0 0.3 1.0 2.1 22.9 NaN 111.0 116 3 \n",
"60 ... 4.2 1.3 0.3 1.7 2.3 23.8 NaN 110.0 116 3 \n",
"108 ... 5.2 1.8 0.6 2.0 4.6 20.4 NaN 117.0 110 3 \n",
"112 ... 3.1 1.8 0.6 2.1 3.0 21.6 NaN 109.0 116 3 \n",
"120 ... 5.1 1.3 0.7 1.8 3.6 14.8 NaN 110.0 114 3 \n",
"139 ... 3.9 1.2 0.5 1.4 2.7 19.4 NaN 120.0 113 3 \n",
"232 ... 2.8 0.9 0.2 2.1 3.6 25.0 NaN 109.0 117 3 \n",
"251 ... 3.0 0.8 0.4 1.1 2.7 22.7 NaN 120.0 117 3 \n",
"291 ... 3.7 1.5 0.2 1.4 3.0 24.2 NaN 107.0 111 3 \n",
"301 ... 3.0 1.6 0.3 1.7 3.1 19.0 NaN 110.0 116 3 \n",
"337 ... 3.0 1.3 0.8 1.7 3.6 17.7 NaN 107.0 118 3 \n",
"371 ... 2.3 1.1 0.4 1.6 3.7 23.5 NaN 106.0 118 3 \n",
"392 ... 2.8 1.6 0.4 1.3 3.1 22.9 NaN 123.0 109 3 \n",
"426 ... 3.7 1.1 0.2 1.5 2.6 21.3 NaN 119.0 113 3 \n",
"451 ... 4.2 1.6 1.1 1.9 3.1 21.3 NaN 109.0 116 3 \n",
"490 ... 2.2 1.2 0.8 1.4 3.5 23.9 NaN 117.0 110 3 \n",
"514 ... 2.5 0.5 0.2 1.7 3.1 22.7 NaN 112.0 118 3 \n",
"527 ... 3.8 1.1 0.4 1.5 2.3 19.1 NaN 112.0 117 3 \n",
"558 ... 2.2 1.3 0.4 0.9 3.4 19.1 NaN 120.0 115 3 \n",
"579 ... 2.4 1.0 0.7 2.3 3.2 19.7 NaN 100.0 113 3 \n",
"649 ... 3.5 1.7 0.9 2.0 3.6 20.4 NaN 113.0 110 3 \n",
"650 ... 3.0 1.6 1.1 1.8 3.7 19.5 NaN 113.0 109 3 \n",
"689 ... 3.6 0.9 0.3 1.4 3.1 19.2 NaN 111.0 112 3 \n",
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" <td>...</td>\n",
" <td>1.8</td>\n",
" <td>1.3</td>\n",
" <td>1.4</td>\n",
" <td>1.6</td>\n",
" <td>4.4</td>\n",
" <td>24.6</td>\n",
" <td>NaN</td>\n",
" <td>114.0</td>\n",
" <td>114</td>\n",
" <td>3</td>\n",
" </tr>\n",
" <tr>\n",
" <th>51</th>\n",
" <td>42</td>\n",
" <td>Malik Beasley</td>\n",
" <td>SG</td>\n",
" <td>25</td>\n",
" <td>MIN</td>\n",
" <td>79</td>\n",
" <td>18</td>\n",
" <td>1976</td>\n",
" <td>8.0</td>\n",
" <td>20.5</td>\n",
" <td>...</td>\n",
" <td>2.8</td>\n",
" <td>1.0</td>\n",
" <td>0.3</td>\n",
" <td>1.0</td>\n",
" <td>2.1</td>\n",
" <td>22.9</td>\n",
" <td>NaN</td>\n",
" <td>111.0</td>\n",
" <td>116</td>\n",
" <td>3</td>\n",
" </tr>\n",
" <tr>\n",
" <th>60</th>\n",
" <td>47</td>\n",
" <td>Saddiq Bey</td>\n",
" <td>SF</td>\n",
" <td>22</td>\n",
" <td>DET</td>\n",
" <td>82</td>\n",
" <td>82</td>\n",
" <td>2704</td>\n",
" <td>8.1</td>\n",
" <td>20.5</td>\n",
" <td>...</td>\n",
" <td>4.2</td>\n",
" <td>1.3</td>\n",
" <td>0.3</td>\n",
" <td>1.7</td>\n",
" <td>2.3</td>\n",
" <td>23.8</td>\n",
" <td>NaN</td>\n",
" <td>110.0</td>\n",
" <td>116</td>\n",
" <td>3</td>\n",
" </tr>\n",
" <tr>\n",
" <th>108</th>\n",
" <td>85</td>\n",
" <td>Alec Burks</td>\n",
" <td>SG</td>\n",
" <td>30</td>\n",
" <td>NYK</td>\n",
" <td>81</td>\n",
" <td>44</td>\n",
" <td>2318</td>\n",
" <td>6.2</td>\n",
" <td>15.7</td>\n",
" <td>...</td>\n",
" <td>5.2</td>\n",
" <td>1.8</td>\n",
" <td>0.6</td>\n",
" <td>2.0</td>\n",
" <td>4.6</td>\n",
" <td>20.4</td>\n",
" <td>NaN</td>\n",
" <td>117.0</td>\n",
" <td>110</td>\n",
" <td>3</td>\n",
" </tr>\n",
" <tr>\n",
" <th>112</th>\n",
" <td>89</td>\n",
" <td>Kentavious Caldwell-Pope</td>\n",
" <td>SG</td>\n",
" <td>28</td>\n",
" <td>WAS</td>\n",
" <td>77</td>\n",
" <td>77</td>\n",
" <td>2329</td>\n",
" <td>7.7</td>\n",
" <td>17.6</td>\n",
" <td>...</td>\n",
" <td>3.1</td>\n",
" <td>1.8</td>\n",
" <td>0.6</td>\n",
" <td>2.1</td>\n",
" <td>3.0</td>\n",
" <td>21.6</td>\n",
" <td>NaN</td>\n",
" <td>109.0</td>\n",
" <td>116</td>\n",
" <td>3</td>\n",
" </tr>\n",
" <tr>\n",
" <th>120</th>\n",
" <td>95</td>\n",
" <td>Jevon Carter</td>\n",
" <td>PG</td>\n",
" <td>26</td>\n",
" <td>TOT</td>\n",
" <td>66</td>\n",
" <td>3</td>\n",
" <td>905</td>\n",
" <td>5.2</td>\n",
" <td>13.5</td>\n",
" <td>...</td>\n",
" <td>5.1</td>\n",
" <td>1.3</td>\n",
" <td>0.7</td>\n",
" <td>1.8</td>\n",
" <td>3.6</td>\n",
" <td>14.8</td>\n",
" <td>NaN</td>\n",
" <td>110.0</td>\n",
" <td>114</td>\n",
" <td>3</td>\n",
" </tr>\n",
" <tr>\n",
" <th>139</th>\n",
" <td>109</td>\n",
" <td>Amir Coffey</td>\n",
" <td>SG</td>\n",
" <td>24</td>\n",
" <td>LAC</td>\n",
" <td>69</td>\n",
" <td>30</td>\n",
" <td>1567</td>\n",
" <td>6.6</td>\n",
" <td>14.6</td>\n",
" <td>...</td>\n",
" <td>3.9</td>\n",
" <td>1.2</td>\n",
" <td>0.5</td>\n",
" <td>1.4</td>\n",
" <td>2.7</td>\n",
" <td>19.4</td>\n",
" <td>NaN</td>\n",
" <td>120.0</td>\n",
" <td>113</td>\n",
" <td>3</td>\n",
" </tr>\n",
" <tr>\n",
" <th>232</th>\n",
" <td>171</td>\n",
" <td>Bryn Forbes</td>\n",
" <td>SG</td>\n",
" <td>28</td>\n",
" <td>TOT</td>\n",
" <td>75</td>\n",
" <td>2</td>\n",
" <td>1286</td>\n",
" <td>8.7</td>\n",
" <td>20.3</td>\n",
" <td>...</td>\n",
" <td>2.8</td>\n",
" <td>0.9</td>\n",
" <td>0.2</td>\n",
" <td>2.1</td>\n",
" <td>3.6</td>\n",
" <td>25.0</td>\n",
" <td>NaN</td>\n",
" <td>109.0</td>\n",
" <td>117</td>\n",
" <td>3</td>\n",
" </tr>\n",
" <tr>\n",
" <th>251</th>\n",
" <td>182</td>\n",
" <td>Danilo Gallinari</td>\n",
" <td>PF</td>\n",
" <td>33</td>\n",
" <td>ATL</td>\n",
" <td>66</td>\n",
" <td>18</td>\n",
" <td>1672</td>\n",
" <td>7.6</td>\n",
" <td>17.5</td>\n",
" <td>...</td>\n",
" <td>3.0</td>\n",
" <td>0.8</td>\n",
" <td>0.4</td>\n",
" <td>1.1</td>\n",
" <td>2.7</td>\n",
" <td>22.7</td>\n",
" <td>NaN</td>\n",
" <td>120.0</td>\n",
" <td>117</td>\n",
" <td>3</td>\n",
" </tr>\n",
" <tr>\n",
" <th>291</th>\n",
" <td>217</td>\n",
" <td>Tim Hardaway Jr.</td>\n",
" <td>SG</td>\n",
" <td>29</td>\n",
" <td>DAL</td>\n",
" <td>42</td>\n",
" <td>20</td>\n",
" <td>1245</td>\n",
" <td>8.4</td>\n",
" <td>21.4</td>\n",
" <td>...</td>\n",
" <td>3.7</td>\n",
" <td>1.5</td>\n",
" <td>0.2</td>\n",
" <td>1.4</td>\n",
" <td>3.0</td>\n",
" <td>24.2</td>\n",
" <td>NaN</td>\n",
" <td>107.0</td>\n",
" <td>111</td>\n",
" <td>3</td>\n",
" </tr>\n",
" <tr>\n",
" <th>301</th>\n",
" <td>222</td>\n",
" <td>Gary Harris</td>\n",
" <td>SG</td>\n",
" <td>27</td>\n",
" <td>ORL</td>\n",
" <td>61</td>\n",
" <td>30</td>\n",
" <td>1730</td>\n",
" <td>6.7</td>\n",
" <td>15.5</td>\n",
" <td>...</td>\n",
" <td>3.0</td>\n",
" <td>1.6</td>\n",
" <td>0.3</td>\n",
" <td>1.7</td>\n",
" <td>3.1</td>\n",
" <td>19.0</td>\n",
" <td>NaN</td>\n",
" <td>110.0</td>\n",
" <td>116</td>\n",
" <td>3</td>\n",
" </tr>\n",
" <tr>\n",
" <th>337</th>\n",
" <td>246</td>\n",
" <td>Justin Holiday</td>\n",
" <td>SF-SG</td>\n",
" <td>32</td>\n",
" <td>TOT</td>\n",
" <td>74</td>\n",
" <td>65</td>\n",
" <td>2057</td>\n",
" <td>6.2</td>\n",
" <td>15.7</td>\n",
" <td>...</td>\n",
" <td>3.0</td>\n",
" <td>1.3</td>\n",
" <td>0.8</td>\n",
" <td>1.7</td>\n",
" <td>3.6</td>\n",
" <td>17.7</td>\n",
" <td>NaN</td>\n",
" <td>107.0</td>\n",
" <td>118</td>\n",
" <td>3</td>\n",
" </tr>\n",
" <tr>\n",
" <th>371</th>\n",
" <td>268</td>\n",
" <td>Frank Jackson</td>\n",
" <td>PG</td>\n",
" <td>23</td>\n",
" <td>DET</td>\n",
" <td>53</td>\n",
" <td>7</td>\n",
" <td>1164</td>\n",
" <td>8.1</td>\n",
" <td>20.2</td>\n",
" <td>...</td>\n",
" <td>2.3</td>\n",
" <td>1.1</td>\n",
" <td>0.4</td>\n",
" <td>1.6</td>\n",
" <td>3.7</td>\n",
" <td>23.5</td>\n",
" <td>NaN</td>\n",
" <td>106.0</td>\n",
" <td>118</td>\n",
" <td>3</td>\n",
" </tr>\n",
" <tr>\n",
" <th>392</th>\n",
" <td>281</td>\n",
" <td>Cameron Johnson</td>\n",
" <td>PF</td>\n",
" <td>25</td>\n",
" <td>PHO</td>\n",
" <td>66</td>\n",
" <td>16</td>\n",
" <td>1730</td>\n",
" <td>7.8</td>\n",
" <td>16.9</td>\n",
" <td>...</td>\n",
" <td>2.8</td>\n",
" <td>1.6</td>\n",
" <td>0.4</td>\n",
" <td>1.3</td>\n",
" <td>3.1</td>\n",
" <td>22.9</td>\n",
" <td>NaN</td>\n",
" <td>123.0</td>\n",
" <td>109</td>\n",
" <td>3</td>\n",
" </tr>\n",
" <tr>\n",
" <th>426</th>\n",
" <td>304</td>\n",
" <td>Luke Kennard</td>\n",
" <td>SG</td>\n",
" <td>25</td>\n",
" <td>LAC</td>\n",
" <td>70</td>\n",
" <td>13</td>\n",
" <td>1919</td>\n",
" <td>7.3</td>\n",
" <td>16.3</td>\n",
" <td>...</td>\n",
" <td>3.7</td>\n",
" <td>1.1</td>\n",
" <td>0.2</td>\n",
" <td>1.5</td>\n",
" <td>2.6</td>\n",
" <td>21.3</td>\n",
" <td>NaN</td>\n",
" <td>119.0</td>\n",
" <td>113</td>\n",
" <td>3</td>\n",
" </tr>\n",
" <tr>\n",
" <th>451</th>\n",
" <td>321</td>\n",
" <td>Jeremy Lamb</td>\n",
" <td>SF-SG</td>\n",
" <td>29</td>\n",
" <td>TOT</td>\n",
" <td>56</td>\n",
" <td>0</td>\n",
" <td>935</td>\n",
" <td>6.9</td>\n",
" <td>18.1</td>\n",
" <td>...</td>\n",
" <td>4.2</td>\n",
" <td>1.6</td>\n",
" <td>1.1</td>\n",
" <td>1.9</td>\n",
" <td>3.1</td>\n",
" <td>21.3</td>\n",
" <td>NaN</td>\n",
" <td>109.0</td>\n",
" <td>116</td>\n",
" <td>3</td>\n",
" </tr>\n",
" <tr>\n",
" <th>490</th>\n",
" <td>349</td>\n",
" <td>Lauri Markkanen</td>\n",
" <td>PF</td>\n",
" <td>24</td>\n",
" <td>CLE</td>\n",
" <td>61</td>\n",
" <td>61</td>\n",
" <td>1878</td>\n",
" <td>8.3</td>\n",
" <td>18.7</td>\n",
" <td>...</td>\n",
" <td>2.2</td>\n",
" <td>1.2</td>\n",
" <td>0.8</td>\n",
" <td>1.4</td>\n",
" <td>3.5</td>\n",
" <td>23.9</td>\n",
" <td>NaN</td>\n",
" <td>117.0</td>\n",
" <td>110</td>\n",
" <td>3</td>\n",
" </tr>\n",
" <tr>\n",
" <th>514</th>\n",
" <td>366</td>\n",
" <td>Doug McDermott</td>\n",
" <td>PF</td>\n",
" <td>30</td>\n",
" <td>SAS</td>\n",
" <td>51</td>\n",
" <td>51</td>\n",
" <td>1223</td>\n",
" <td>8.4</td>\n",
" <td>18.2</td>\n",
" <td>...</td>\n",
" <td>2.5</td>\n",
" <td>0.5</td>\n",
" <td>0.2</td>\n",
" <td>1.7</td>\n",
" <td>3.1</td>\n",
" <td>22.7</td>\n",
" <td>NaN</td>\n",
" <td>112.0</td>\n",
" <td>118</td>\n",
" <td>3</td>\n",
" </tr>\n",
" <tr>\n",
" <th>527</th>\n",
" <td>379</td>\n",
" <td>Patty Mills</td>\n",
" <td>PG</td>\n",
" <td>33</td>\n",
" <td>BRK</td>\n",
" <td>81</td>\n",
" <td>48</td>\n",
" <td>2346</td>\n",
" <td>6.7</td>\n",
" <td>16.4</td>\n",
" <td>...</td>\n",
" <td>3.8</td>\n",
" <td>1.1</td>\n",
" <td>0.4</td>\n",
" <td>1.5</td>\n",
" <td>2.3</td>\n",
" <td>19.1</td>\n",
" <td>NaN</td>\n",
" <td>112.0</td>\n",
" <td>117</td>\n",
" <td>3</td>\n",
" </tr>\n",
" <tr>\n",
" <th>558</th>\n",
" <td>399</td>\n",
" <td>Trey Murphy III</td>\n",
" <td>SF</td>\n",
" <td>21</td>\n",
" <td>NOP</td>\n",
" <td>62</td>\n",
" <td>1</td>\n",
" <td>864</td>\n",
" <td>6.2</td>\n",
" <td>15.8</td>\n",
" <td>...</td>\n",
" <td>2.2</td>\n",
" <td>1.3</td>\n",
" <td>0.4</td>\n",
" <td>0.9</td>\n",
" <td>3.4</td>\n",
" <td>19.1</td>\n",
" <td>NaN</td>\n",
" <td>120.0</td>\n",
" <td>115</td>\n",
" <td>3</td>\n",
" </tr>\n",
" <tr>\n",
" <th>579</th>\n",
" <td>417</td>\n",
" <td>Jordan Nwora</td>\n",
" <td>SF</td>\n",
" <td>23</td>\n",
" <td>MIL</td>\n",
" <td>62</td>\n",
" <td>13</td>\n",
" <td>1185</td>\n",
" <td>7.5</td>\n",
" <td>18.7</td>\n",
" <td>...</td>\n",
" <td>2.4</td>\n",
" <td>1.0</td>\n",
" <td>0.7</td>\n",
" <td>2.3</td>\n",
" <td>3.2</td>\n",
" <td>19.7</td>\n",
" <td>NaN</td>\n",
" <td>100.0</td>\n",
" <td>113</td>\n",
" <td>3</td>\n",
" </tr>\n",
" <tr>\n",
" <th>649</th>\n",
" <td>474</td>\n",
" <td>Josh Richardson</td>\n",
" <td>SG</td>\n",
" <td>28</td>\n",
" <td>TOT</td>\n",
" <td>65</td>\n",
" <td>7</td>\n",
" <td>1600</td>\n",
" <td>7.2</td>\n",
" <td>16.4</td>\n",
" <td>...</td>\n",
" <td>3.5</td>\n",
" <td>1.7</td>\n",
" <td>0.9</td>\n",
" <td>2.0</td>\n",
" <td>3.6</td>\n",
" <td>20.4</td>\n",
" <td>NaN</td>\n",
" <td>113.0</td>\n",
" <td>110</td>\n",
" <td>3</td>\n",
" </tr>\n",
" <tr>\n",
" <th>650</th>\n",
" <td>474</td>\n",
" <td>Josh Richardson</td>\n",
" <td>SG</td>\n",
" <td>28</td>\n",
" <td>BOS</td>\n",
" <td>44</td>\n",
" <td>0</td>\n",
" <td>1087</td>\n",
" <td>6.9</td>\n",
" <td>15.7</td>\n",
" <td>...</td>\n",
" <td>3.0</td>\n",
" <td>1.6</td>\n",
" <td>1.1</td>\n",
" <td>1.8</td>\n",
" <td>3.7</td>\n",
" <td>19.5</td>\n",
" <td>NaN</td>\n",
" <td>113.0</td>\n",
" <td>109</td>\n",
" <td>3</td>\n",
" </tr>\n",
" <tr>\n",
" <th>689</th>\n",
" <td>499</td>\n",
" <td>Landry Shamet</td>\n",
" <td>SG</td>\n",
" <td>24</td>\n",
" <td>PHO</td>\n",
" <td>69</td>\n",
" <td>14</td>\n",
" <td>1437</td>\n",
" <td>6.4</td>\n",
" <td>16.2</td>\n",
" <td>...</td>\n",
" <td>3.6</td>\n",
" <td>0.9</td>\n",
" <td>0.3</td>\n",
" <td>1.4</td>\n",
" <td>3.1</td>\n",
" <td>19.2</td>\n",
" <td>NaN</td>\n",
" <td>111.0</td>\n",
" <td>112</td>\n",
" <td>3</td>\n",
" </tr>\n",
" <tr>\n",
" <th>776</th>\n",
" <td>555</td>\n",
" <td>Devin Vassell</td>\n",
" <td>SF</td>\n",
" <td>21</td>\n",
" <td>SAS</td>\n",
" <td>71</td>\n",
" <td>32</td>\n",
" <td>1937</td>\n",
" <td>8.1</td>\n",
" <td>18.9</td>\n",
" <td>...</td>\n",
" <td>3.4</td>\n",
" <td>1.9</td>\n",
" <td>1.0</td>\n",
" <td>1.4</td>\n",
" <td>3.5</td>\n",
" <td>21.6</td>\n",
" <td>NaN</td>\n",
" <td>109.0</td>\n",
" <td>112</td>\n",
" <td>3</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>25 rows × 33 columns</p>\n",
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" Rk Player Pos Age Tm G GS MP FG FGA ... \\\n",
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"176 137 Hamidou Diallo SG 23 DET 58 29 1269 10.0 20.2 ... \n",
"279 207 Javonte Green SF 28 CHI 65 45 1519 5.7 10.4 ... \n",
"281 209 Josh Green SG 21 DAL 67 3 1039 6.3 12.4 ... \n",
"411 294 Herbert Jones PF 23 NOP 78 69 2335 5.8 12.2 ... \n",
"492 351 Caleb Martin SF 26 MIA 60 12 1372 7.6 15.0 ... \n",
"564 404 Larry Nance Jr. PF 29 TOT 46 11 1040 6.1 11.6 ... \n",
"565 404 Larry Nance Jr. PF 29 POR 37 11 858 5.8 11.3 ... \n",
"607 441 Gary Payton II PG 29 GSW 71 16 1247 8.3 13.5 ... \n",
"756 540 Matisse Thybulle SG 24 PHI 66 50 1685 4.4 8.9 ... \n",
"762 545 Juan Toscano-Anderson SF 28 GSW 73 6 994 5.6 11.5 ... \n",
"774 553 Jarred Vanderbilt PF 22 MIN 74 67 1880 5.4 9.1 ... \n",
"835 601 Thaddeus Young PF 33 TOT 52 1 845 8.2 15.8 ... \n",
"\n",
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" <td>44</td>\n",
" <td>DeAndre' Bembry</td>\n",
" <td>SF</td>\n",
" <td>27</td>\n",
" <td>BRK</td>\n",
" <td>48</td>\n",
" <td>20</td>\n",
" <td>949</td>\n",
" <td>6.2</td>\n",
" <td>10.9</td>\n",
" <td>...</td>\n",
" <td>3.1</td>\n",
" <td>2.4</td>\n",
" <td>1.3</td>\n",
" <td>1.5</td>\n",
" <td>5.3</td>\n",
" <td>14.2</td>\n",
" <td>NaN</td>\n",
" <td>120.0</td>\n",
" <td>111</td>\n",
" <td>4</td>\n",
" </tr>\n",
" <tr>\n",
" <th>88</th>\n",
" <td>72</td>\n",
" <td>Bruce Brown</td>\n",
" <td>SF</td>\n",
" <td>25</td>\n",
" <td>BRK</td>\n",
" <td>72</td>\n",
" <td>45</td>\n",
" <td>1774</td>\n",
" <td>7.0</td>\n",
" <td>13.8</td>\n",
" <td>...</td>\n",
" <td>4.0</td>\n",
" <td>2.1</td>\n",
" <td>1.4</td>\n",
" <td>1.5</td>\n",
" <td>4.8</td>\n",
" <td>17.7</td>\n",
" <td>NaN</td>\n",
" <td>121.0</td>\n",
" <td>111</td>\n",
" <td>4</td>\n",
" </tr>\n",
" <tr>\n",
" <th>176</th>\n",
" <td>137</td>\n",
" <td>Hamidou Diallo</td>\n",
" <td>SG</td>\n",
" <td>23</td>\n",
" <td>DET</td>\n",
" <td>58</td>\n",
" <td>29</td>\n",
" <td>1269</td>\n",
" <td>10.0</td>\n",
" <td>20.2</td>\n",
" <td>...</td>\n",
" <td>2.8</td>\n",
" <td>2.7</td>\n",
" <td>0.7</td>\n",
" <td>2.2</td>\n",
" <td>5.5</td>\n",
" <td>24.5</td>\n",
" <td>NaN</td>\n",
" <td>107.0</td>\n",
" <td>111</td>\n",
" <td>4</td>\n",
" </tr>\n",
" <tr>\n",
" <th>279</th>\n",
" <td>207</td>\n",
" <td>Javonte Green</td>\n",
" <td>SF</td>\n",
" <td>28</td>\n",
" <td>CHI</td>\n",
" <td>65</td>\n",
" <td>45</td>\n",
" <td>1519</td>\n",
" <td>5.7</td>\n",
" <td>10.4</td>\n",
" <td>...</td>\n",
" <td>1.9</td>\n",
" <td>2.2</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>4.2</td>\n",
" <td>15.0</td>\n",
" <td>NaN</td>\n",
" <td>131.0</td>\n",
" <td>112</td>\n",
" <td>4</td>\n",
" </tr>\n",
" <tr>\n",
" <th>281</th>\n",
" <td>209</td>\n",
" <td>Josh Green</td>\n",
" <td>SG</td>\n",
" <td>21</td>\n",
" <td>DAL</td>\n",
" <td>67</td>\n",
" <td>3</td>\n",
" <td>1039</td>\n",
" <td>6.3</td>\n",
" <td>12.4</td>\n",
" <td>...</td>\n",
" <td>3.8</td>\n",
" <td>2.2</td>\n",
" <td>0.7</td>\n",
" <td>2.1</td>\n",
" <td>5.6</td>\n",
" <td>15.5</td>\n",
" <td>NaN</td>\n",
" <td>114.0</td>\n",
" <td>109</td>\n",
" <td>4</td>\n",
" </tr>\n",
" <tr>\n",
" <th>411</th>\n",
" <td>294</td>\n",
" <td>Herbert Jones</td>\n",
" <td>PF</td>\n",
" <td>23</td>\n",
" <td>NOP</td>\n",
" <td>78</td>\n",
" <td>69</td>\n",
" <td>2335</td>\n",
" <td>5.8</td>\n",
" <td>12.2</td>\n",
" <td>...</td>\n",
" <td>3.5</td>\n",
" <td>2.7</td>\n",
" <td>1.3</td>\n",
" <td>2.1</td>\n",
" <td>5.0</td>\n",
" <td>15.7</td>\n",
" <td>NaN</td>\n",
" <td>114.0</td>\n",
" <td>112</td>\n",
" <td>4</td>\n",
" </tr>\n",
" <tr>\n",
" <th>492</th>\n",
" <td>351</td>\n",
" <td>Caleb Martin</td>\n",
" <td>SF</td>\n",
" <td>26</td>\n",
" <td>MIA</td>\n",
" <td>60</td>\n",
" <td>12</td>\n",
" <td>1372</td>\n",
" <td>7.6</td>\n",
" <td>15.0</td>\n",
" <td>...</td>\n",
" <td>2.3</td>\n",
" <td>2.1</td>\n",
" <td>1.1</td>\n",
" <td>1.9</td>\n",
" <td>3.8</td>\n",
" <td>20.1</td>\n",
" <td>NaN</td>\n",
" <td>119.0</td>\n",
" <td>108</td>\n",
" <td>4</td>\n",
" </tr>\n",
" <tr>\n",
" <th>564</th>\n",
" <td>404</td>\n",
" <td>Larry Nance Jr.</td>\n",
" <td>PF</td>\n",
" <td>29</td>\n",
" <td>TOT</td>\n",
" <td>46</td>\n",
" <td>11</td>\n",
" <td>1040</td>\n",
" <td>6.1</td>\n",
" <td>11.6</td>\n",
" <td>...</td>\n",
" <td>3.8</td>\n",
" <td>2.0</td>\n",
" <td>0.9</td>\n",
" <td>1.7</td>\n",
" <td>4.0</td>\n",
" <td>15.1</td>\n",
" <td>NaN</td>\n",
" <td>121.0</td>\n",
" <td>114</td>\n",
" <td>4</td>\n",
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" <tr>\n",
" <th>565</th>\n",
" <td>404</td>\n",
" <td>Larry Nance Jr.</td>\n",
" <td>PF</td>\n",
" <td>29</td>\n",
" <td>POR</td>\n",
" <td>37</td>\n",
" <td>11</td>\n",
" <td>858</td>\n",
" <td>5.8</td>\n",
" <td>11.3</td>\n",
" <td>...</td>\n",
" <td>4.2</td>\n",
" <td>2.2</td>\n",
" <td>0.7</td>\n",
" <td>1.5</td>\n",
" <td>3.8</td>\n",
" <td>14.5</td>\n",
" <td>NaN</td>\n",
" <td>122.0</td>\n",
" <td>115</td>\n",
" <td>4</td>\n",
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" <tr>\n",
" <th>607</th>\n",
" <td>441</td>\n",
" <td>Gary Payton II</td>\n",
" <td>PG</td>\n",
" <td>29</td>\n",
" <td>GSW</td>\n",
" <td>71</td>\n",
" <td>16</td>\n",
" <td>1247</td>\n",
" <td>8.3</td>\n",
" <td>13.5</td>\n",
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" <td>2.5</td>\n",
" <td>3.8</td>\n",
" <td>0.9</td>\n",
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" <td>19.6</td>\n",
" <td>NaN</td>\n",
" <td>129.0</td>\n",
" <td>103</td>\n",
" <td>4</td>\n",
" </tr>\n",
" <tr>\n",
" <th>756</th>\n",
" <td>540</td>\n",
" <td>Matisse Thybulle</td>\n",
" <td>SG</td>\n",
" <td>24</td>\n",
" <td>PHI</td>\n",
" <td>66</td>\n",
" <td>50</td>\n",
" <td>1685</td>\n",
" <td>4.4</td>\n",
" <td>8.9</td>\n",
" <td>...</td>\n",
" <td>2.2</td>\n",
" <td>3.4</td>\n",
" <td>2.1</td>\n",
" <td>1.2</td>\n",
" <td>4.7</td>\n",
" <td>11.2</td>\n",
" <td>NaN</td>\n",
" <td>116.0</td>\n",
" <td>108</td>\n",
" <td>4</td>\n",
" </tr>\n",
" <tr>\n",
" <th>762</th>\n",
" <td>545</td>\n",
" <td>Juan Toscano-Anderson</td>\n",
" <td>SF</td>\n",
" <td>28</td>\n",
" <td>GSW</td>\n",
" <td>73</td>\n",
" <td>6</td>\n",
" <td>994</td>\n",
" <td>5.6</td>\n",
" <td>11.5</td>\n",
" <td>...</td>\n",
" <td>6.2</td>\n",
" <td>2.4</td>\n",
" <td>0.8</td>\n",
" <td>3.3</td>\n",
" <td>5.6</td>\n",
" <td>14.6</td>\n",
" <td>NaN</td>\n",
" <td>106.0</td>\n",
" <td>106</td>\n",
" <td>4</td>\n",
" </tr>\n",
" <tr>\n",
" <th>774</th>\n",
" <td>553</td>\n",
" <td>Jarred Vanderbilt</td>\n",
" <td>PF</td>\n",
" <td>22</td>\n",
" <td>MIN</td>\n",
" <td>74</td>\n",
" <td>67</td>\n",
" <td>1880</td>\n",
" <td>5.4</td>\n",
" <td>9.1</td>\n",
" <td>...</td>\n",
" <td>2.4</td>\n",
" <td>2.5</td>\n",
" <td>1.2</td>\n",
" <td>1.8</td>\n",
" <td>4.6</td>\n",
" <td>13.0</td>\n",
" <td>NaN</td>\n",
" <td>127.0</td>\n",
" <td>108</td>\n",
" <td>4</td>\n",
" </tr>\n",
" <tr>\n",
" <th>835</th>\n",
" <td>601</td>\n",
" <td>Thaddeus Young</td>\n",
" <td>PF</td>\n",
" <td>33</td>\n",
" <td>TOT</td>\n",
" <td>52</td>\n",
" <td>1</td>\n",
" <td>845</td>\n",
" <td>8.2</td>\n",
" <td>15.8</td>\n",
" <td>...</td>\n",
" <td>6.0</td>\n",
" <td>3.1</td>\n",
" <td>1.0</td>\n",
" <td>3.0</td>\n",
" <td>4.7</td>\n",
" <td>18.7</td>\n",
" <td>NaN</td>\n",
" <td>113.0</td>\n",
" <td>108</td>\n",
" <td>4</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>15 rows × 33 columns</p>\n",
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" Age G GS MP FG FGA \\\n",
"count 15.000000 15.000000 15.000000 15.000000 15.000000 15.000000 \n",
"mean 26.266667 61.533333 27.000000 1322.133333 6.553333 12.466667 \n",
"std 3.261609 11.897579 22.668417 435.899377 1.426718 2.907544 \n",
"min 21.000000 37.000000 1.000000 845.000000 4.400000 8.900000 \n",
"25% 23.500000 54.000000 11.000000 1010.000000 5.750000 10.650000 \n",
"50% 27.000000 65.000000 20.000000 1247.000000 6.100000 11.600000 \n",
"75% 28.500000 71.500000 45.000000 1602.000000 7.300000 13.650000 \n",
"max 33.000000 78.000000 69.000000 2335.000000 10.000000 20.200000 \n",
"\n",
" FG% 3P 3PA 3P% ... AST STL \\\n",
"count 15.000000 15.000000 15.000000 15.000000 ... 15.000000 15.000000 \n",
"mean 0.527400 1.146667 3.286667 0.338333 ... 3.453333 2.540000 \n",
"std 0.039431 0.486778 1.313592 0.071801 ... 1.285561 0.522084 \n",
"min 0.476000 0.100000 0.400000 0.143000 ... 1.900000 2.000000 \n",
"25% 0.503000 0.950000 2.700000 0.317500 ... 2.450000 2.200000 \n",
"50% 0.515000 1.100000 3.500000 0.354000 ... 3.100000 2.400000 \n",
"75% 0.551500 1.350000 4.050000 0.381500 ... 3.900000 2.700000 \n",
"max 0.616000 2.300000 5.700000 0.417000 ... 6.200000 3.800000 \n",
"\n",
" BLK TOV PF PTS Unnamed: 29 ORtg \\\n",
"count 15.000000 15.000000 15.0000 15.000000 0.0 15.00000 \n",
"mean 1.086667 1.860000 4.8000 16.186667 NaN 118.60000 \n",
"std 0.364234 0.620829 0.6245 3.381434 NaN 7.22891 \n",
"min 0.700000 1.000000 3.8000 11.200000 NaN 106.00000 \n",
"25% 0.850000 1.500000 4.4000 14.350000 NaN 114.00000 \n",
"50% 1.000000 1.700000 4.8000 15.100000 NaN 119.00000 \n",
"75% 1.250000 2.100000 5.3000 18.200000 NaN 121.50000 \n",
"max 2.100000 3.300000 5.6000 24.500000 NaN 131.00000 \n",
"\n",
" DRtg Clusters \n",
"count 15.000000 15.0 \n",
"mean 109.866667 4.0 \n",
"std 3.136574 0.0 \n",
"min 103.000000 4.0 \n",
"25% 108.000000 4.0 \n",
"50% 111.000000 4.0 \n",
"75% 112.000000 4.0 \n",
"max 115.000000 4.0 \n",
"\n",
"[8 rows x 29 columns]"
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" <th></th>\n",
" <th>Age</th>\n",
" <th>G</th>\n",
" <th>GS</th>\n",
" <th>MP</th>\n",
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" <td>15.000000</td>\n",
" <td>15.000000</td>\n",
" <td>15.000000</td>\n",
" <td>15.000000</td>\n",
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" <td>15.000000</td>\n",
" <td>15.000000</td>\n",
" <td>15.0000</td>\n",
" <td>15.000000</td>\n",
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" <td>15.000000</td>\n",
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" <td>6.553333</td>\n",
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" <td>3.286667</td>\n",
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" <td>2.540000</td>\n",
" <td>1.086667</td>\n",
" <td>1.860000</td>\n",
" <td>4.8000</td>\n",
" <td>16.186667</td>\n",
" <td>NaN</td>\n",
" <td>118.60000</td>\n",
" <td>109.866667</td>\n",
" <td>4.0</td>\n",
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" <td>435.899377</td>\n",
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" <td>1.285561</td>\n",
" <td>0.522084</td>\n",
" <td>0.364234</td>\n",
" <td>0.620829</td>\n",
" <td>0.6245</td>\n",
" <td>3.381434</td>\n",
" <td>NaN</td>\n",
" <td>7.22891</td>\n",
" <td>3.136574</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>min</th>\n",
" <td>21.000000</td>\n",
" <td>37.000000</td>\n",
" <td>1.000000</td>\n",
" <td>845.000000</td>\n",
" <td>4.400000</td>\n",
" <td>8.900000</td>\n",
" <td>0.476000</td>\n",
" <td>0.100000</td>\n",
" <td>0.400000</td>\n",
" <td>0.143000</td>\n",
" <td>...</td>\n",
" <td>1.900000</td>\n",
" <td>2.000000</td>\n",
" <td>0.700000</td>\n",
" <td>1.000000</td>\n",
" <td>3.8000</td>\n",
" <td>11.200000</td>\n",
" <td>NaN</td>\n",
" <td>106.00000</td>\n",
" <td>103.000000</td>\n",
" <td>4.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>25%</th>\n",
" <td>23.500000</td>\n",
" <td>54.000000</td>\n",
" <td>11.000000</td>\n",
" <td>1010.000000</td>\n",
" <td>5.750000</td>\n",
" <td>10.650000</td>\n",
" <td>0.503000</td>\n",
" <td>0.950000</td>\n",
" <td>2.700000</td>\n",
" <td>0.317500</td>\n",
" <td>...</td>\n",
" <td>2.450000</td>\n",
" <td>2.200000</td>\n",
" <td>0.850000</td>\n",
" <td>1.500000</td>\n",
" <td>4.4000</td>\n",
" <td>14.350000</td>\n",
" <td>NaN</td>\n",
" <td>114.00000</td>\n",
" <td>108.000000</td>\n",
" <td>4.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>50%</th>\n",
" <td>27.000000</td>\n",
" <td>65.000000</td>\n",
" <td>20.000000</td>\n",
" <td>1247.000000</td>\n",
" <td>6.100000</td>\n",
" <td>11.600000</td>\n",
" <td>0.515000</td>\n",
" <td>1.100000</td>\n",
" <td>3.500000</td>\n",
" <td>0.354000</td>\n",
" <td>...</td>\n",
" <td>3.100000</td>\n",
" <td>2.400000</td>\n",
" <td>1.000000</td>\n",
" <td>1.700000</td>\n",
" <td>4.8000</td>\n",
" <td>15.100000</td>\n",
" <td>NaN</td>\n",
" <td>119.00000</td>\n",
" <td>111.000000</td>\n",
" <td>4.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>75%</th>\n",
" <td>28.500000</td>\n",
" <td>71.500000</td>\n",
" <td>45.000000</td>\n",
" <td>1602.000000</td>\n",
" <td>7.300000</td>\n",
" <td>13.650000</td>\n",
" <td>0.551500</td>\n",
" <td>1.350000</td>\n",
" <td>4.050000</td>\n",
" <td>0.381500</td>\n",
" <td>...</td>\n",
" <td>3.900000</td>\n",
" <td>2.700000</td>\n",
" <td>1.250000</td>\n",
" <td>2.100000</td>\n",
" <td>5.3000</td>\n",
" <td>18.200000</td>\n",
" <td>NaN</td>\n",
" <td>121.50000</td>\n",
" <td>112.000000</td>\n",
" <td>4.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>max</th>\n",
" <td>33.000000</td>\n",
" <td>78.000000</td>\n",
" <td>69.000000</td>\n",
" <td>2335.000000</td>\n",
" <td>10.000000</td>\n",
" <td>20.200000</td>\n",
" <td>0.616000</td>\n",
" <td>2.300000</td>\n",
" <td>5.700000</td>\n",
" <td>0.417000</td>\n",
" <td>...</td>\n",
" <td>6.200000</td>\n",
" <td>3.800000</td>\n",
" <td>2.100000</td>\n",
" <td>3.300000</td>\n",
" <td>5.6000</td>\n",
" <td>24.500000</td>\n",
" <td>NaN</td>\n",
" <td>131.00000</td>\n",
" <td>115.000000</td>\n",
" <td>4.0</td>\n",
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" Rk Player Pos Age Tm G GS MP FG FGA \\\n",
"50 41 Bradley Beal SG 28 WAS 40 40 1439 12.0 26.5 \n",
"72 59 Devin Booker SG 25 PHO 68 68 2345 13.6 29.2 \n",
"96 76 Jaylen Brown SF 25 BOS 66 66 2220 12.9 27.2 \n",
"110 87 Jimmy Butler SF 32 MIA 57 57 1931 10.3 21.5 \n",
"173 134 DeMar DeRozan PF 32 CHI 76 76 2743 13.8 27.3 \n",
"185 141 Luka Dončić PG 22 DAL 65 65 2301 14.0 30.7 \n",
"205 154 Kevin Durant PF 33 BRK 55 55 2047 13.7 26.4 \n",
"238 175 De'Aaron Fox PG 24 SAC 59 59 2083 11.9 25.2 \n",
"263 192 Shai Gilgeous-Alexander PG 23 OKC 56 56 1942 12.0 26.4 \n",
"368 265 Brandon Ingram SF 24 NOP 55 55 1869 12.0 26.0 \n",
"381 274 LeBron James SF 37 LAL 56 56 2084 14.7 28.1 \n",
"458 324 Zach LaVine SF 26 CHI 67 67 2328 11.8 24.9 \n",
"545 390 Ja Morant PG 22 MEM 57 57 1889 14.7 29.8 \n",
"640 467 Julius Randle PF 27 NYK 72 72 2544 10.1 24.5 \n",
"734 526 Jayson Tatum SF 23 BOS 76 76 2731 12.9 28.5 \n",
"838 602 Trae Young PG 23 ATL 76 76 2652 13.2 28.6 \n",
"\n",
" ... AST STL BLK TOV PF PTS Unnamed: 29 ORtg DRtg Clusters \n",
"50 ... 9.1 1.2 0.5 4.6 3.3 31.9 NaN 106.0 117 5 \n",
"72 ... 6.8 1.6 0.5 3.3 3.7 37.4 NaN 113.0 109 5 \n",
"96 ... 5.2 1.6 0.4 4.0 3.6 34.9 NaN 109.0 108 5 \n",
"110 ... 8.1 2.4 0.7 3.1 2.3 31.6 NaN 124.0 108 5 \n",
"173 ... 6.7 1.2 0.4 3.2 3.2 37.7 NaN 117.0 115 5 \n",
"185 ... 12.4 1.6 0.8 6.4 3.2 40.4 NaN 110.0 107 5 \n",
"205 ... 8.3 1.1 1.2 4.5 2.7 38.9 NaN 121.0 112 5 \n",
"238 ... 7.6 1.6 0.6 3.9 4.0 31.6 NaN 107.0 117 5 \n",
"263 ... 8.3 1.8 1.2 3.9 3.6 34.4 NaN 111.0 113 5 \n",
"368 ... 8.1 0.9 0.7 4.0 3.1 32.9 NaN 111.0 115 5 \n",
"381 ... 8.0 1.7 1.4 4.5 2.8 39.0 NaN 117.0 111 5 \n",
"458 ... 6.4 0.9 0.5 3.6 2.5 34.3 NaN 115.0 116 5 \n",
"545 ... 9.7 1.7 0.6 5.0 2.2 39.6 NaN 116.0 111 5 \n",
"640 ... 7.3 1.0 0.8 4.8 4.0 28.5 NaN 102.0 109 5 \n",
"734 ... 6.1 1.4 0.9 3.9 3.2 37.2 NaN 113.0 106 5 \n",
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" <th></th>\n",
" <th>Rk</th>\n",
" <th>Player</th>\n",
" <th>Pos</th>\n",
" <th>Age</th>\n",
" <th>Tm</th>\n",
" <th>G</th>\n",
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" <th>50</th>\n",
" <td>41</td>\n",
" <td>Bradley Beal</td>\n",
" <td>SG</td>\n",
" <td>28</td>\n",
" <td>WAS</td>\n",
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" <td>26.5</td>\n",
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" <td>9.1</td>\n",
" <td>1.2</td>\n",
" <td>0.5</td>\n",
" <td>4.6</td>\n",
" <td>3.3</td>\n",
" <td>31.9</td>\n",
" <td>NaN</td>\n",
" <td>106.0</td>\n",
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" <td>59</td>\n",
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" <td>SG</td>\n",
" <td>25</td>\n",
" <td>PHO</td>\n",
" <td>68</td>\n",
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" <td>2345</td>\n",
" <td>13.6</td>\n",
" <td>29.2</td>\n",
" <td>...</td>\n",
" <td>6.8</td>\n",
" <td>1.6</td>\n",
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" <td>3.3</td>\n",
" <td>3.7</td>\n",
" <td>37.4</td>\n",
" <td>NaN</td>\n",
" <td>113.0</td>\n",
" <td>109</td>\n",
" <td>5</td>\n",
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" <th>96</th>\n",
" <td>76</td>\n",
" <td>Jaylen Brown</td>\n",
" <td>SF</td>\n",
" <td>25</td>\n",
" <td>BOS</td>\n",
" <td>66</td>\n",
" <td>66</td>\n",
" <td>2220</td>\n",
" <td>12.9</td>\n",
" <td>27.2</td>\n",
" <td>...</td>\n",
" <td>5.2</td>\n",
" <td>1.6</td>\n",
" <td>0.4</td>\n",
" <td>4.0</td>\n",
" <td>3.6</td>\n",
" <td>34.9</td>\n",
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" <td>109.0</td>\n",
" <td>108</td>\n",
" <td>5</td>\n",
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" <th>110</th>\n",
" <td>87</td>\n",
" <td>Jimmy Butler</td>\n",
" <td>SF</td>\n",
" <td>32</td>\n",
" <td>MIA</td>\n",
" <td>57</td>\n",
" <td>57</td>\n",
" <td>1931</td>\n",
" <td>10.3</td>\n",
" <td>21.5</td>\n",
" <td>...</td>\n",
" <td>8.1</td>\n",
" <td>2.4</td>\n",
" <td>0.7</td>\n",
" <td>3.1</td>\n",
" <td>2.3</td>\n",
" <td>31.6</td>\n",
" <td>NaN</td>\n",
" <td>124.0</td>\n",
" <td>108</td>\n",
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" <th>173</th>\n",
" <td>134</td>\n",
" <td>DeMar DeRozan</td>\n",
" <td>PF</td>\n",
" <td>32</td>\n",
" <td>CHI</td>\n",
" <td>76</td>\n",
" <td>76</td>\n",
" <td>2743</td>\n",
" <td>13.8</td>\n",
" <td>27.3</td>\n",
" <td>...</td>\n",
" <td>6.7</td>\n",
" <td>1.2</td>\n",
" <td>0.4</td>\n",
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" <td>3.2</td>\n",
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" <td>117.0</td>\n",
" <td>115</td>\n",
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" <tr>\n",
" <th>185</th>\n",
" <td>141</td>\n",
" <td>Luka Dončić</td>\n",
" <td>PG</td>\n",
" <td>22</td>\n",
" <td>DAL</td>\n",
" <td>65</td>\n",
" <td>65</td>\n",
" <td>2301</td>\n",
" <td>14.0</td>\n",
" <td>30.7</td>\n",
" <td>...</td>\n",
" <td>12.4</td>\n",
" <td>1.6</td>\n",
" <td>0.8</td>\n",
" <td>6.4</td>\n",
" <td>3.2</td>\n",
" <td>40.4</td>\n",
" <td>NaN</td>\n",
" <td>110.0</td>\n",
" <td>107</td>\n",
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" <th>205</th>\n",
" <td>154</td>\n",
" <td>Kevin Durant</td>\n",
" <td>PF</td>\n",
" <td>33</td>\n",
" <td>BRK</td>\n",
" <td>55</td>\n",
" <td>55</td>\n",
" <td>2047</td>\n",
" <td>13.7</td>\n",
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" <td>2.7</td>\n",
" <td>38.9</td>\n",
" <td>NaN</td>\n",
" <td>121.0</td>\n",
" <td>112</td>\n",
" <td>5</td>\n",
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" <th>238</th>\n",
" <td>175</td>\n",
" <td>De'Aaron Fox</td>\n",
" <td>PG</td>\n",
" <td>24</td>\n",
" <td>SAC</td>\n",
" <td>59</td>\n",
" <td>59</td>\n",
" <td>2083</td>\n",
" <td>11.9</td>\n",
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" <td>107.0</td>\n",
" <td>117</td>\n",
" <td>5</td>\n",
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" <tr>\n",
" <th>263</th>\n",
" <td>192</td>\n",
" <td>Shai Gilgeous-Alexander</td>\n",
" <td>PG</td>\n",
" <td>23</td>\n",
" <td>OKC</td>\n",
" <td>56</td>\n",
" <td>56</td>\n",
" <td>1942</td>\n",
" <td>12.0</td>\n",
" <td>26.4</td>\n",
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" <td>8.3</td>\n",
" <td>1.8</td>\n",
" <td>1.2</td>\n",
" <td>3.9</td>\n",
" <td>3.6</td>\n",
" <td>34.4</td>\n",
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" <td>111.0</td>\n",
" <td>113</td>\n",
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" <tr>\n",
" <th>368</th>\n",
" <td>265</td>\n",
" <td>Brandon Ingram</td>\n",
" <td>SF</td>\n",
" <td>24</td>\n",
" <td>NOP</td>\n",
" <td>55</td>\n",
" <td>55</td>\n",
" <td>1869</td>\n",
" <td>12.0</td>\n",
" <td>26.0</td>\n",
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" <td>115</td>\n",
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" <tr>\n",
" <th>381</th>\n",
" <td>274</td>\n",
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" <td>SF</td>\n",
" <td>37</td>\n",
" <td>LAL</td>\n",
" <td>56</td>\n",
" <td>56</td>\n",
" <td>2084</td>\n",
" <td>14.7</td>\n",
" <td>28.1</td>\n",
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" <td>26</td>\n",
" <td>CHI</td>\n",
" <td>67</td>\n",
" <td>67</td>\n",
" <td>2328</td>\n",
" <td>11.8</td>\n",
" <td>24.9</td>\n",
" <td>...</td>\n",
" <td>6.4</td>\n",
" <td>0.9</td>\n",
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" <td>3.6</td>\n",
" <td>2.5</td>\n",
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" <td>NaN</td>\n",
" <td>115.0</td>\n",
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" <td>5</td>\n",
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" <tr>\n",
" <th>545</th>\n",
" <td>390</td>\n",
" <td>Ja Morant</td>\n",
" <td>PG</td>\n",
" <td>22</td>\n",
" <td>MEM</td>\n",
" <td>57</td>\n",
" <td>57</td>\n",
" <td>1889</td>\n",
" <td>14.7</td>\n",
" <td>29.8</td>\n",
" <td>...</td>\n",
" <td>9.7</td>\n",
" <td>1.7</td>\n",
" <td>0.6</td>\n",
" <td>5.0</td>\n",
" <td>2.2</td>\n",
" <td>39.6</td>\n",
" <td>NaN</td>\n",
" <td>116.0</td>\n",
" <td>111</td>\n",
" <td>5</td>\n",
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" <tr>\n",
" <th>640</th>\n",
" <td>467</td>\n",
" <td>Julius Randle</td>\n",
" <td>PF</td>\n",
" <td>27</td>\n",
" <td>NYK</td>\n",
" <td>72</td>\n",
" <td>72</td>\n",
" <td>2544</td>\n",
" <td>10.1</td>\n",
" <td>24.5</td>\n",
" <td>...</td>\n",
" <td>7.3</td>\n",
" <td>1.0</td>\n",
" <td>0.8</td>\n",
" <td>4.8</td>\n",
" <td>4.0</td>\n",
" <td>28.5</td>\n",
" <td>NaN</td>\n",
" <td>102.0</td>\n",
" <td>109</td>\n",
" <td>5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>734</th>\n",
" <td>526</td>\n",
" <td>Jayson Tatum</td>\n",
" <td>SF</td>\n",
" <td>23</td>\n",
" <td>BOS</td>\n",
" <td>76</td>\n",
" <td>76</td>\n",
" <td>2731</td>\n",
" <td>12.9</td>\n",
" <td>28.5</td>\n",
" <td>...</td>\n",
" <td>6.1</td>\n",
" <td>1.4</td>\n",
" <td>0.9</td>\n",
" <td>3.9</td>\n",
" <td>3.2</td>\n",
" <td>37.2</td>\n",
" <td>NaN</td>\n",
" <td>113.0</td>\n",
" <td>106</td>\n",
" <td>5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>838</th>\n",
" <td>602</td>\n",
" <td>Trae Young</td>\n",
" <td>PG</td>\n",
" <td>23</td>\n",
" <td>ATL</td>\n",
" <td>76</td>\n",
" <td>76</td>\n",
" <td>2652</td>\n",
" <td>13.2</td>\n",
" <td>28.6</td>\n",
" <td>...</td>\n",
" <td>13.7</td>\n",
" <td>1.3</td>\n",
" <td>0.1</td>\n",
" <td>5.6</td>\n",
" <td>2.4</td>\n",
" <td>39.9</td>\n",
" <td>NaN</td>\n",
" <td>119.0</td>\n",
" <td>118</td>\n",
" <td>5</td>\n",
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" Age G GS MP FG FGA \\\n",
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"25% 23.000000 56.000000 56.000000 1939.250000 11.975000 25.800000 \n",
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"75% 29.000000 69.000000 69.000000 2394.750000 13.725000 28.525000 \n",
"max 37.000000 76.000000 76.000000 2743.000000 14.700000 30.700000 \n",
"\n",
" FG% 3P 3PA 3P% ... AST STL \\\n",
"count 16.000000 16.000000 16.000000 16.000000 ... 16.000000 16.000000 \n",
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"std 0.028020 1.203259 2.956687 0.042201 ... 2.206619 0.393065 \n",
"min 0.411000 0.700000 2.500000 0.233000 ... 5.200000 0.900000 \n",
"25% 0.456000 2.150000 6.375000 0.306000 ... 6.775000 1.175000 \n",
"50% 0.469500 2.550000 7.550000 0.352500 ... 8.050000 1.500000 \n",
"75% 0.483250 3.825000 10.325000 0.364750 ... 8.500000 1.625000 \n",
"max 0.524000 4.400000 12.400000 0.389000 ... 13.700000 2.400000 \n",
"\n",
" BLK TOV PF PTS Unnamed: 29 ORtg \\\n",
"count 16.000000 16.000000 16.000000 16.000000 0.0 16.000000 \n",
"mean 0.706250 4.268750 3.112500 35.637500 NaN 113.187500 \n",
"std 0.339546 0.886731 0.582952 3.625626 NaN 5.799066 \n",
"min 0.100000 3.100000 2.200000 28.500000 NaN 102.000000 \n",
"25% 0.500000 3.825000 2.650000 32.650000 NaN 109.750000 \n",
"50% 0.650000 4.000000 3.200000 36.050000 NaN 113.000000 \n",
"75% 0.825000 4.650000 3.600000 38.925000 NaN 117.000000 \n",
"max 1.400000 6.400000 4.000000 40.400000 NaN 124.000000 \n",
"\n",
" DRtg Clusters \n",
"count 16.000000 16.0 \n",
"mean 112.000000 5.0 \n",
"std 3.949684 0.0 \n",
"min 106.000000 5.0 \n",
"25% 108.750000 5.0 \n",
"50% 111.500000 5.0 \n",
"75% 115.250000 5.0 \n",
"max 118.000000 5.0 \n",
"\n",
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" <td>21.500000</td>\n",
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" google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
"\n",
" async function convertToInteractive(key) {\n",
" const element = document.querySelector('#df-565f0cea-9bd9-4b2d-a5e0-d46e5e368b31');\n",
" const dataTable =\n",
" await google.colab.kernel.invokeFunction('convertToInteractive',\n",
" [key], {});\n",
" if (!dataTable) return;\n",
"\n",
" const docLinkHtml = 'Like what you see? Visit the ' +\n",
" '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
" + ' to learn more about interactive tables.';\n",
" element.innerHTML = '';\n",
" dataTable['output_type'] = 'display_data';\n",
" await google.colab.output.renderOutput(dataTable, element);\n",
" const docLink = document.createElement('div');\n",
" docLink.innerHTML = docLinkHtml;\n",
" element.appendChild(docLink);\n",
" }\n",
" </script>\n",
" </div>\n",
" </div>\n",
" "
]
},
"metadata": {}
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"----\n",
"\n",
"\n"
]
},
{
"output_type": "display_data",
"data": {
"text/plain": [
" Rk Player Pos Age Tm G GS MP FG FGA ... \\\n",
"10 9 Jose Alvarado PG 23 NOP 54 1 834 7.8 17.4 ... \n",
"34 26 Lonzo Ball PG 24 CHI 35 35 1212 6.5 15.4 ... \n",
"59 46 Patrick Beverley PG 33 MIN 58 54 1476 5.7 14.1 ... \n",
"65 52 Eric Bledsoe PG 32 LAC 54 29 1361 7.1 16.8 ... \n",
"113 90 Facundo Campazzo PG 30 DEN 65 4 1184 4.4 12.3 ... \n",
"124 97 Alex Caruso SG 27 CHI 41 18 1147 4.3 10.9 ... \n",
"134 104 Josh Christopher SG 20 HOU 74 2 1334 8.0 17.8 ... \n",
"143 113 Mike Conley PG 34 UTA 72 72 2058 8.3 19.0 ... \n",
"181 140 Donte DiVincenzo SG 25 TOT 42 1 1006 5.6 16.1 ... \n",
"312 231 Killian Hayes PG 20 DET 66 40 1647 5.2 13.6 ... \n",
"333 244 Aaron Holiday PG 25 TOT 63 15 1021 7.2 16.2 ... \n",
"346 251 Talen Horton-Tucker SG 21 LAL 60 19 1511 7.1 17.1 ... \n",
"415 298 Tre Jones PG 22 SAS 69 11 1148 6.9 14.2 ... \n",
"478 340 Kyle Lowry PG 35 MIA 63 63 2133 6.5 14.7 ... \n",
"520 372 Jordan McLaughlin PG 25 MIN 62 3 902 4.6 10.5 ... \n",
"522 374 De'Anthony Melton SG 23 MEM 73 15 1657 8.1 20.1 ... \n",
"569 407 Raul Neto PG 29 WAS 70 19 1372 7.4 15.9 ... \n",
"675 490 Tomáš Satoranský SG 30 TOT 55 13 906 3.9 10.4 ... \n",
"704 509 Marcus Smart PG 27 BOS 71 71 2296 6.5 15.5 ... \n",
"777 556 Gabe Vincent PG 25 MIA 68 27 1589 6.7 16.2 ... \n",
"\n",
" AST STL BLK TOV PF PTS Unnamed: 29 ORtg DRtg Clusters \n",
"10 9.0 4.2 0.4 2.4 4.3 19.5 NaN 114.0 109 6 \n",
"34 7.2 2.6 1.2 3.3 3.4 18.3 NaN 110.0 111 6 \n",
"59 8.6 2.2 1.7 2.4 5.6 17.2 NaN 119.0 111 6 \n",
"65 8.1 2.5 0.7 4.2 3.1 19.2 NaN 100.0 110 6 \n",
"113 9.1 2.6 1.0 2.8 5.1 13.8 NaN 109.0 111 6 \n",
"124 7.0 3.0 0.6 2.4 4.5 12.9 NaN 110.0 112 6 \n",
"134 5.4 2.3 0.5 4.1 3.5 20.9 NaN 101.0 117 6 \n",
"143 9.2 2.3 0.5 3.0 3.4 23.7 NaN 120.0 111 6 \n",
"181 5.6 2.3 0.4 3.4 3.3 18.2 NaN 102.0 113 6 \n",
"312 8.2 2.3 1.0 3.3 5.4 13.4 NaN 97.0 113 6 \n",
"333 7.3 2.0 0.4 3.2 4.4 19.2 NaN 108.0 113 6 \n",
"346 5.0 1.9 0.9 2.6 4.7 18.9 NaN 102.0 114 6 \n",
"415 9.7 1.8 0.3 1.9 3.3 17.3 NaN 120.0 114 6 \n",
"478 11.1 1.6 0.4 3.9 4.2 19.8 NaN 118.0 110 6 \n",
"520 9.5 3.0 0.5 2.0 2.8 12.3 NaN 122.0 112 6 \n",
"522 5.6 3.0 1.1 3.2 3.7 22.8 NaN 108.0 107 6 \n",
"569 7.8 2.0 0.1 2.8 3.7 19.0 NaN 108.0 116 6 \n",
"675 10.0 1.6 0.3 2.5 3.9 10.8 NaN 109.0 115 6 \n",
"704 9.0 2.6 0.4 3.4 3.5 18.6 NaN 110.0 107 6 \n",
"777 6.6 2.0 0.4 3.1 5.0 18.6 NaN 107.0 111 6 \n",
"\n",
"[20 rows x 33 columns]"
],
"text/html": [
"\n",
" <div id=\"df-4cedbffe-364b-4499-bcdf-31274ecf7920\">\n",
" <div class=\"colab-df-container\">\n",
" <div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Rk</th>\n",
" <th>Player</th>\n",
" <th>Pos</th>\n",
" <th>Age</th>\n",
" <th>Tm</th>\n",
" <th>G</th>\n",
" <th>GS</th>\n",
" <th>MP</th>\n",
" <th>FG</th>\n",
" <th>FGA</th>\n",
" <th>...</th>\n",
" <th>AST</th>\n",
" <th>STL</th>\n",
" <th>BLK</th>\n",
" <th>TOV</th>\n",
" <th>PF</th>\n",
" <th>PTS</th>\n",
" <th>Unnamed: 29</th>\n",
" <th>ORtg</th>\n",
" <th>DRtg</th>\n",
" <th>Clusters</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>10</th>\n",
" <td>9</td>\n",
" <td>Jose Alvarado</td>\n",
" <td>PG</td>\n",
" <td>23</td>\n",
" <td>NOP</td>\n",
" <td>54</td>\n",
" <td>1</td>\n",
" <td>834</td>\n",
" <td>7.8</td>\n",
" <td>17.4</td>\n",
" <td>...</td>\n",
" <td>9.0</td>\n",
" <td>4.2</td>\n",
" <td>0.4</td>\n",
" <td>2.4</td>\n",
" <td>4.3</td>\n",
" <td>19.5</td>\n",
" <td>NaN</td>\n",
" <td>114.0</td>\n",
" <td>109</td>\n",
" <td>6</td>\n",
" </tr>\n",
" <tr>\n",
" <th>34</th>\n",
" <td>26</td>\n",
" <td>Lonzo Ball</td>\n",
" <td>PG</td>\n",
" <td>24</td>\n",
" <td>CHI</td>\n",
" <td>35</td>\n",
" <td>35</td>\n",
" <td>1212</td>\n",
" <td>6.5</td>\n",
" <td>15.4</td>\n",
" <td>...</td>\n",
" <td>7.2</td>\n",
" <td>2.6</td>\n",
" <td>1.2</td>\n",
" <td>3.3</td>\n",
" <td>3.4</td>\n",
" <td>18.3</td>\n",
" <td>NaN</td>\n",
" <td>110.0</td>\n",
" <td>111</td>\n",
" <td>6</td>\n",
" </tr>\n",
" <tr>\n",
" <th>59</th>\n",
" <td>46</td>\n",
" <td>Patrick Beverley</td>\n",
" <td>PG</td>\n",
" <td>33</td>\n",
" <td>MIN</td>\n",
" <td>58</td>\n",
" <td>54</td>\n",
" <td>1476</td>\n",
" <td>5.7</td>\n",
" <td>14.1</td>\n",
" <td>...</td>\n",
" <td>8.6</td>\n",
" <td>2.2</td>\n",
" <td>1.7</td>\n",
" <td>2.4</td>\n",
" <td>5.6</td>\n",
" <td>17.2</td>\n",
" <td>NaN</td>\n",
" <td>119.0</td>\n",
" <td>111</td>\n",
" <td>6</td>\n",
" </tr>\n",
" <tr>\n",
" <th>65</th>\n",
" <td>52</td>\n",
" <td>Eric Bledsoe</td>\n",
" <td>PG</td>\n",
" <td>32</td>\n",
" <td>LAC</td>\n",
" <td>54</td>\n",
" <td>29</td>\n",
" <td>1361</td>\n",
" <td>7.1</td>\n",
" <td>16.8</td>\n",
" <td>...</td>\n",
" <td>8.1</td>\n",
" <td>2.5</td>\n",
" <td>0.7</td>\n",
" <td>4.2</td>\n",
" <td>3.1</td>\n",
" <td>19.2</td>\n",
" <td>NaN</td>\n",
" <td>100.0</td>\n",
" <td>110</td>\n",
" <td>6</td>\n",
" </tr>\n",
" <tr>\n",
" <th>113</th>\n",
" <td>90</td>\n",
" <td>Facundo Campazzo</td>\n",
" <td>PG</td>\n",
" <td>30</td>\n",
" <td>DEN</td>\n",
" <td>65</td>\n",
" <td>4</td>\n",
" <td>1184</td>\n",
" <td>4.4</td>\n",
" <td>12.3</td>\n",
" <td>...</td>\n",
" <td>9.1</td>\n",
" <td>2.6</td>\n",
" <td>1.0</td>\n",
" <td>2.8</td>\n",
" <td>5.1</td>\n",
" <td>13.8</td>\n",
" <td>NaN</td>\n",
" <td>109.0</td>\n",
" <td>111</td>\n",
" <td>6</td>\n",
" </tr>\n",
" <tr>\n",
" <th>124</th>\n",
" <td>97</td>\n",
" <td>Alex Caruso</td>\n",
" <td>SG</td>\n",
" <td>27</td>\n",
" <td>CHI</td>\n",
" <td>41</td>\n",
" <td>18</td>\n",
" <td>1147</td>\n",
" <td>4.3</td>\n",
" <td>10.9</td>\n",
" <td>...</td>\n",
" <td>7.0</td>\n",
" <td>3.0</td>\n",
" <td>0.6</td>\n",
" <td>2.4</td>\n",
" <td>4.5</td>\n",
" <td>12.9</td>\n",
" <td>NaN</td>\n",
" <td>110.0</td>\n",
" <td>112</td>\n",
" <td>6</td>\n",
" </tr>\n",
" <tr>\n",
" <th>134</th>\n",
" <td>104</td>\n",
" <td>Josh Christopher</td>\n",
" <td>SG</td>\n",
" <td>20</td>\n",
" <td>HOU</td>\n",
" <td>74</td>\n",
" <td>2</td>\n",
" <td>1334</td>\n",
" <td>8.0</td>\n",
" <td>17.8</td>\n",
" <td>...</td>\n",
" <td>5.4</td>\n",
" <td>2.3</td>\n",
" <td>0.5</td>\n",
" <td>4.1</td>\n",
" <td>3.5</td>\n",
" <td>20.9</td>\n",
" <td>NaN</td>\n",
" <td>101.0</td>\n",
" <td>117</td>\n",
" <td>6</td>\n",
" </tr>\n",
" <tr>\n",
" <th>143</th>\n",
" <td>113</td>\n",
" <td>Mike Conley</td>\n",
" <td>PG</td>\n",
" <td>34</td>\n",
" <td>UTA</td>\n",
" <td>72</td>\n",
" <td>72</td>\n",
" <td>2058</td>\n",
" <td>8.3</td>\n",
" <td>19.0</td>\n",
" <td>...</td>\n",
" <td>9.2</td>\n",
" <td>2.3</td>\n",
" <td>0.5</td>\n",
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" <td>3.4</td>\n",
" <td>23.7</td>\n",
" <td>NaN</td>\n",
" <td>120.0</td>\n",
" <td>111</td>\n",
" <td>6</td>\n",
" </tr>\n",
" <tr>\n",
" <th>181</th>\n",
" <td>140</td>\n",
" <td>Donte DiVincenzo</td>\n",
" <td>SG</td>\n",
" <td>25</td>\n",
" <td>TOT</td>\n",
" <td>42</td>\n",
" <td>1</td>\n",
" <td>1006</td>\n",
" <td>5.6</td>\n",
" <td>16.1</td>\n",
" <td>...</td>\n",
" <td>5.6</td>\n",
" <td>2.3</td>\n",
" <td>0.4</td>\n",
" <td>3.4</td>\n",
" <td>3.3</td>\n",
" <td>18.2</td>\n",
" <td>NaN</td>\n",
" <td>102.0</td>\n",
" <td>113</td>\n",
" <td>6</td>\n",
" </tr>\n",
" <tr>\n",
" <th>312</th>\n",
" <td>231</td>\n",
" <td>Killian Hayes</td>\n",
" <td>PG</td>\n",
" <td>20</td>\n",
" <td>DET</td>\n",
" <td>66</td>\n",
" <td>40</td>\n",
" <td>1647</td>\n",
" <td>5.2</td>\n",
" <td>13.6</td>\n",
" <td>...</td>\n",
" <td>8.2</td>\n",
" <td>2.3</td>\n",
" <td>1.0</td>\n",
" <td>3.3</td>\n",
" <td>5.4</td>\n",
" <td>13.4</td>\n",
" <td>NaN</td>\n",
" <td>97.0</td>\n",
" <td>113</td>\n",
" <td>6</td>\n",
" </tr>\n",
" <tr>\n",
" <th>333</th>\n",
" <td>244</td>\n",
" <td>Aaron Holiday</td>\n",
" <td>PG</td>\n",
" <td>25</td>\n",
" <td>TOT</td>\n",
" <td>63</td>\n",
" <td>15</td>\n",
" <td>1021</td>\n",
" <td>7.2</td>\n",
" <td>16.2</td>\n",
" <td>...</td>\n",
" <td>7.3</td>\n",
" <td>2.0</td>\n",
" <td>0.4</td>\n",
" <td>3.2</td>\n",
" <td>4.4</td>\n",
" <td>19.2</td>\n",
" <td>NaN</td>\n",
" <td>108.0</td>\n",
" <td>113</td>\n",
" <td>6</td>\n",
" </tr>\n",
" <tr>\n",
" <th>346</th>\n",
" <td>251</td>\n",
" <td>Talen Horton-Tucker</td>\n",
" <td>SG</td>\n",
" <td>21</td>\n",
" <td>LAL</td>\n",
" <td>60</td>\n",
" <td>19</td>\n",
" <td>1511</td>\n",
" <td>7.1</td>\n",
" <td>17.1</td>\n",
" <td>...</td>\n",
" <td>5.0</td>\n",
" <td>1.9</td>\n",
" <td>0.9</td>\n",
" <td>2.6</td>\n",
" <td>4.7</td>\n",
" <td>18.9</td>\n",
" <td>NaN</td>\n",
" <td>102.0</td>\n",
" <td>114</td>\n",
" <td>6</td>\n",
" </tr>\n",
" <tr>\n",
" <th>415</th>\n",
" <td>298</td>\n",
" <td>Tre Jones</td>\n",
" <td>PG</td>\n",
" <td>22</td>\n",
" <td>SAS</td>\n",
" <td>69</td>\n",
" <td>11</td>\n",
" <td>1148</td>\n",
" <td>6.9</td>\n",
" <td>14.2</td>\n",
" <td>...</td>\n",
" <td>9.7</td>\n",
" <td>1.8</td>\n",
" <td>0.3</td>\n",
" <td>1.9</td>\n",
" <td>3.3</td>\n",
" <td>17.3</td>\n",
" <td>NaN</td>\n",
" <td>120.0</td>\n",
" <td>114</td>\n",
" <td>6</td>\n",
" </tr>\n",
" <tr>\n",
" <th>478</th>\n",
" <td>340</td>\n",
" <td>Kyle Lowry</td>\n",
" <td>PG</td>\n",
" <td>35</td>\n",
" <td>MIA</td>\n",
" <td>63</td>\n",
" <td>63</td>\n",
" <td>2133</td>\n",
" <td>6.5</td>\n",
" <td>14.7</td>\n",
" <td>...</td>\n",
" <td>11.1</td>\n",
" <td>1.6</td>\n",
" <td>0.4</td>\n",
" <td>3.9</td>\n",
" <td>4.2</td>\n",
" <td>19.8</td>\n",
" <td>NaN</td>\n",
" <td>118.0</td>\n",
" <td>110</td>\n",
" <td>6</td>\n",
" </tr>\n",
" <tr>\n",
" <th>520</th>\n",
" <td>372</td>\n",
" <td>Jordan McLaughlin</td>\n",
" <td>PG</td>\n",
" <td>25</td>\n",
" <td>MIN</td>\n",
" <td>62</td>\n",
" <td>3</td>\n",
" <td>902</td>\n",
" <td>4.6</td>\n",
" <td>10.5</td>\n",
" <td>...</td>\n",
" <td>9.5</td>\n",
" <td>3.0</td>\n",
" <td>0.5</td>\n",
" <td>2.0</td>\n",
" <td>2.8</td>\n",
" <td>12.3</td>\n",
" <td>NaN</td>\n",
" <td>122.0</td>\n",
" <td>112</td>\n",
" <td>6</td>\n",
" </tr>\n",
" <tr>\n",
" <th>522</th>\n",
" <td>374</td>\n",
" <td>De'Anthony Melton</td>\n",
" <td>SG</td>\n",
" <td>23</td>\n",
" <td>MEM</td>\n",
" <td>73</td>\n",
" <td>15</td>\n",
" <td>1657</td>\n",
" <td>8.1</td>\n",
" <td>20.1</td>\n",
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" <td>5.6</td>\n",
" <td>3.0</td>\n",
" <td>1.1</td>\n",
" <td>3.2</td>\n",
" <td>3.7</td>\n",
" <td>22.8</td>\n",
" <td>NaN</td>\n",
" <td>108.0</td>\n",
" <td>107</td>\n",
" <td>6</td>\n",
" </tr>\n",
" <tr>\n",
" <th>569</th>\n",
" <td>407</td>\n",
" <td>Raul Neto</td>\n",
" <td>PG</td>\n",
" <td>29</td>\n",
" <td>WAS</td>\n",
" <td>70</td>\n",
" <td>19</td>\n",
" <td>1372</td>\n",
" <td>7.4</td>\n",
" <td>15.9</td>\n",
" <td>...</td>\n",
" <td>7.8</td>\n",
" <td>2.0</td>\n",
" <td>0.1</td>\n",
" <td>2.8</td>\n",
" <td>3.7</td>\n",
" <td>19.0</td>\n",
" <td>NaN</td>\n",
" <td>108.0</td>\n",
" <td>116</td>\n",
" <td>6</td>\n",
" </tr>\n",
" <tr>\n",
" <th>675</th>\n",
" <td>490</td>\n",
" <td>Tomáš Satoranský</td>\n",
" <td>SG</td>\n",
" <td>30</td>\n",
" <td>TOT</td>\n",
" <td>55</td>\n",
" <td>13</td>\n",
" <td>906</td>\n",
" <td>3.9</td>\n",
" <td>10.4</td>\n",
" <td>...</td>\n",
" <td>10.0</td>\n",
" <td>1.6</td>\n",
" <td>0.3</td>\n",
" <td>2.5</td>\n",
" <td>3.9</td>\n",
" <td>10.8</td>\n",
" <td>NaN</td>\n",
" <td>109.0</td>\n",
" <td>115</td>\n",
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" <tr>\n",
" <th>704</th>\n",
" <td>509</td>\n",
" <td>Marcus Smart</td>\n",
" <td>PG</td>\n",
" <td>27</td>\n",
" <td>BOS</td>\n",
" <td>71</td>\n",
" <td>71</td>\n",
" <td>2296</td>\n",
" <td>6.5</td>\n",
" <td>15.5</td>\n",
" <td>...</td>\n",
" <td>9.0</td>\n",
" <td>2.6</td>\n",
" <td>0.4</td>\n",
" <td>3.4</td>\n",
" <td>3.5</td>\n",
" <td>18.6</td>\n",
" <td>NaN</td>\n",
" <td>110.0</td>\n",
" <td>107</td>\n",
" <td>6</td>\n",
" </tr>\n",
" <tr>\n",
" <th>777</th>\n",
" <td>556</td>\n",
" <td>Gabe Vincent</td>\n",
" <td>PG</td>\n",
" <td>25</td>\n",
" <td>MIA</td>\n",
" <td>68</td>\n",
" <td>27</td>\n",
" <td>1589</td>\n",
" <td>6.7</td>\n",
" <td>16.2</td>\n",
" <td>...</td>\n",
" <td>6.6</td>\n",
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" Rk Player Pos Age Tm G GS MP FG FGA ... \\\n",
"81 67 Miles Bridges PF 23 CHO 80 80 2837 10.1 20.5 ... \n",
"123 96 Wendell Carter Jr. C 22 ORL 62 61 1852 9.4 17.9 ... \n",
"140 110 John Collins PF 24 ATL 54 53 1663 10.0 19.0 ... \n",
"269 198 Aaron Gordon PF 26 DEN 75 75 2376 9.0 17.2 ... \n",
"305 226 Josh Hart SG-SF 26 TOT 54 53 1791 7.9 15.6 ... \n",
"306 226 Josh Hart SG 26 NOP 41 40 1374 7.0 13.9 ... \n",
"447 318 Jonathan Kuminga SF 19 GSW 70 12 1185 9.7 18.9 ... \n",
"448 319 Kyle Kuzma PF 26 WAS 66 66 2204 9.5 21.0 ... \n",
"477 339 Kevin Love PF 33 CLE 74 4 1665 9.8 22.8 ... \n",
"482 343 Trey Lyles PF 26 TOT 75 23 1537 8.3 17.8 ... \n",
"483 343 Trey Lyles PF 26 DET 51 3 990 8.6 18.9 ... \n",
"761 544 Obi Toppin PF 23 NYK 72 10 1230 10.2 19.2 ... \n",
"778 557 Nikola Vučević C 31 CHI 73 73 2418 11.0 23.3 ... \n",
"781 560 Moritz Wagner C 24 ORL 63 3 960 9.9 20.0 ... \n",
"826 595 Christian Wood C 26 HOU 68 67 2094 10.0 20.0 ... \n",
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" <td>15.000000</td>\n",
" <td>15.000000</td>\n",
" <td>15.000000</td>\n",
" <td>15.000000</td>\n",
" <td>15.000000</td>\n",
" <td>15.000000</td>\n",
" <td>15.000000</td>\n",
" <td>15.000000</td>\n",
" <td>15.000000</td>\n",
" <td>...</td>\n",
" <td>15.000000</td>\n",
" <td>15.000000</td>\n",
" <td>15.000000</td>\n",
" <td>15.000000</td>\n",
" <td>15.0000</td>\n",
" <td>15.000000</td>\n",
" <td>0.0</td>\n",
" <td>15.000000</td>\n",
" <td>15.000000</td>\n",
" <td>15.0</td>\n",
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" <th>mean</th>\n",
" <td>25.400000</td>\n",
" <td>65.200000</td>\n",
" <td>41.533333</td>\n",
" <td>1745.066667</td>\n",
" <td>9.360000</td>\n",
" <td>19.066667</td>\n",
" <td>0.492667</td>\n",
" <td>2.466667</td>\n",
" <td>7.240000</td>\n",
" <td>0.336933</td>\n",
" <td>...</td>\n",
" <td>4.180000</td>\n",
" <td>1.133333</td>\n",
" <td>1.033333</td>\n",
" <td>2.766667</td>\n",
" <td>4.1400</td>\n",
" <td>25.633333</td>\n",
" <td>NaN</td>\n",
" <td>114.933333</td>\n",
" <td>111.933333</td>\n",
" <td>7.0</td>\n",
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" <th>std</th>\n",
" <td>3.376389</td>\n",
" <td>10.955755</td>\n",
" <td>29.361945</td>\n",
" <td>557.334532</td>\n",
" <td>1.032196</td>\n",
" <td>2.458707</td>\n",
" <td>0.030684</td>\n",
" <td>0.999047</td>\n",
" <td>2.398452</td>\n",
" <td>0.026666</td>\n",
" <td>...</td>\n",
" <td>1.182733</td>\n",
" <td>0.274296</td>\n",
" <td>0.401189</td>\n",
" <td>0.451453</td>\n",
" <td>0.9738</td>\n",
" <td>2.583925</td>\n",
" <td>NaN</td>\n",
" <td>4.832430</td>\n",
" <td>2.086236</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>min</th>\n",
" <td>19.000000</td>\n",
" <td>41.000000</td>\n",
" <td>3.000000</td>\n",
" <td>960.000000</td>\n",
" <td>7.000000</td>\n",
" <td>13.900000</td>\n",
" <td>0.430000</td>\n",
" <td>1.500000</td>\n",
" <td>4.700000</td>\n",
" <td>0.301000</td>\n",
" <td>...</td>\n",
" <td>2.600000</td>\n",
" <td>0.800000</td>\n",
" <td>0.400000</td>\n",
" <td>1.800000</td>\n",
" <td>2.9000</td>\n",
" <td>19.700000</td>\n",
" <td>NaN</td>\n",
" <td>103.000000</td>\n",
" <td>108.000000</td>\n",
" <td>7.0</td>\n",
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" <tr>\n",
" <th>25%</th>\n",
" <td>23.500000</td>\n",
" <td>58.000000</td>\n",
" <td>11.000000</td>\n",
" <td>1302.000000</td>\n",
" <td>8.800000</td>\n",
" <td>17.850000</td>\n",
" <td>0.469500</td>\n",
" <td>1.950000</td>\n",
" <td>5.750000</td>\n",
" <td>0.322000</td>\n",
" <td>...</td>\n",
" <td>3.000000</td>\n",
" <td>0.900000</td>\n",
" <td>0.800000</td>\n",
" <td>2.600000</td>\n",
" <td>3.5000</td>\n",
" <td>24.550000</td>\n",
" <td>NaN</td>\n",
" <td>113.500000</td>\n",
" <td>110.500000</td>\n",
" <td>7.0</td>\n",
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" <tr>\n",
" <th>50%</th>\n",
" <td>26.000000</td>\n",
" <td>68.000000</td>\n",
" <td>53.000000</td>\n",
" <td>1665.000000</td>\n",
" <td>9.700000</td>\n",
" <td>19.000000</td>\n",
" <td>0.501000</td>\n",
" <td>2.100000</td>\n",
" <td>6.700000</td>\n",
" <td>0.331000</td>\n",
" <td>...</td>\n",
" <td>4.400000</td>\n",
" <td>1.000000</td>\n",
" <td>1.100000</td>\n",
" <td>2.800000</td>\n",
" <td>4.1000</td>\n",
" <td>26.000000</td>\n",
" <td>NaN</td>\n",
" <td>116.000000</td>\n",
" <td>113.000000</td>\n",
" <td>7.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>75%</th>\n",
" <td>26.000000</td>\n",
" <td>73.500000</td>\n",
" <td>66.500000</td>\n",
" <td>2149.000000</td>\n",
" <td>10.000000</td>\n",
" <td>20.250000</td>\n",
" <td>0.516500</td>\n",
" <td>2.750000</td>\n",
" <td>7.750000</td>\n",
" <td>0.342000</td>\n",
" <td>...</td>\n",
" <td>4.950000</td>\n",
" <td>1.300000</td>\n",
" <td>1.300000</td>\n",
" <td>2.950000</td>\n",
" <td>4.4500</td>\n",
" <td>27.050000</td>\n",
" <td>NaN</td>\n",
" <td>117.500000</td>\n",
" <td>113.500000</td>\n",
" <td>7.0</td>\n",
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" <tr>\n",
" <th>max</th>\n",
" <td>33.000000</td>\n",
" <td>80.000000</td>\n",
" <td>80.000000</td>\n",
" <td>2837.000000</td>\n",
" <td>11.000000</td>\n",
" <td>23.300000</td>\n",
" <td>0.531000</td>\n",
" <td>5.600000</td>\n",
" <td>14.300000</td>\n",
" <td>0.392000</td>\n",
" <td>...</td>\n",
" <td>6.200000</td>\n",
" <td>1.700000</td>\n",
" <td>1.700000</td>\n",
" <td>3.800000</td>\n",
" <td>6.2000</td>\n",
" <td>30.200000</td>\n",
" <td>NaN</td>\n",
" <td>122.000000</td>\n",
" <td>114.000000</td>\n",
" <td>7.0</td>\n",
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" </tbody>\n",
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"text/plain": [
" Rk Player Pos Age Tm G GS MP FG FGA ... AST \\\n",
"250 181 Daniel Gafford C 23 WAS 72 53 1444 9.8 14.1 ... 2.3 \n",
"587 422 Onyeka Okongwu C 21 ATL 48 6 992 7.7 11.2 ... 2.6 \n",
"658 478 Mitchell Robinson C 23 NYK 72 62 1848 7.1 9.3 ... 1.0 \n",
"769 550 Myles Turner C 25 IND 42 42 1235 7.9 15.6 ... 1.7 \n",
"807 579 Hassan Whiteside C 32 UTA 65 8 1162 9.1 14.0 ... 1.1 \n",
"818 589 Robert Williams C 24 BOS 61 61 1804 7.5 10.1 ... 3.3 \n",
"\n",
" STL BLK TOV PF PTS Unnamed: 29 ORtg DRtg Clusters \n",
"250 1.0 3.4 2.2 5.8 23.2 NaN 134.0 111 8 \n",
"587 1.5 3.0 2.2 7.4 19.4 NaN 138.0 111 8 \n",
"658 1.6 3.6 1.6 5.3 16.5 NaN 143.0 106 8 \n",
"769 1.1 4.7 2.1 4.7 21.4 NaN 117.0 111 8 \n",
"807 0.9 4.4 2.3 7.6 22.7 NaN 132.0 104 8 \n",
"818 1.5 3.7 1.7 3.8 16.7 NaN 148.0 102 8 \n",
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" if (!dataTable) return;\n",
"\n",
" const docLinkHtml = 'Like what you see? Visit the ' +\n",
" '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
" + ' to learn more about interactive tables.';\n",
" element.innerHTML = '';\n",
" dataTable['output_type'] = 'display_data';\n",
" await google.colab.output.renderOutput(dataTable, element);\n",
" const docLink = document.createElement('div');\n",
" docLink.innerHTML = docLinkHtml;\n",
" element.appendChild(docLink);\n",
" }\n",
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" Age G GS MP FG FGA \\\n",
"count 6.000000 6.000000 6.000000 6.000000 6.000000 6.000000 \n",
"mean 24.666667 60.000000 38.666667 1414.166667 8.183333 12.383333 \n",
"std 3.829708 12.505999 25.562994 350.709234 1.040032 2.530942 \n",
"min 21.000000 42.000000 6.000000 992.000000 7.100000 9.300000 \n",
"25% 23.000000 51.250000 16.500000 1180.250000 7.550000 10.375000 \n",
"50% 23.500000 63.000000 47.500000 1339.500000 7.800000 12.600000 \n",
"75% 24.750000 70.250000 59.000000 1714.000000 8.800000 14.075000 \n",
"max 32.000000 72.000000 62.000000 1848.000000 9.800000 15.600000 \n",
"\n",
" FG% 3P 3PA 3P% ... AST STL \\\n",
"count 6.000000 6.000000 6.000000 3.000000 ... 6.000000 6.000000 \n",
"mean 0.673500 0.400000 1.216667 0.111000 ... 2.000000 1.266667 \n",
"std 0.089149 0.979796 2.980213 0.192258 ... 0.898888 0.301109 \n",
"min 0.509000 0.000000 0.000000 0.000000 ... 1.000000 0.900000 \n",
"25% 0.661500 0.000000 0.000000 0.000000 ... 1.250000 1.025000 \n",
"50% 0.691500 0.000000 0.000000 0.000000 ... 2.000000 1.300000 \n",
"75% 0.725250 0.000000 0.000000 0.166500 ... 2.525000 1.500000 \n",
"max 0.761000 2.400000 7.300000 0.333000 ... 3.300000 1.600000 \n",
"\n",
" BLK TOV PF PTS Unnamed: 29 ORtg \\\n",
"count 6.00000 6.000000 6.000000 6.000000 0.0 6.000000 \n",
"mean 3.80000 2.016667 5.766667 19.983333 NaN 135.333333 \n",
"std 0.63561 0.292689 1.500222 2.932178 NaN 10.726913 \n",
"min 3.00000 1.600000 3.800000 16.500000 NaN 117.000000 \n",
"25% 3.45000 1.800000 4.850000 17.375000 NaN 132.500000 \n",
"50% 3.65000 2.150000 5.550000 20.400000 NaN 136.000000 \n",
"75% 4.22500 2.200000 7.000000 22.375000 NaN 141.750000 \n",
"max 4.70000 2.300000 7.600000 23.200000 NaN 148.000000 \n",
"\n",
" DRtg Clusters \n",
"count 6.000000 6.0 \n",
"mean 107.500000 8.0 \n",
"std 4.037326 0.0 \n",
"min 102.000000 8.0 \n",
"25% 104.500000 8.0 \n",
"50% 108.500000 8.0 \n",
"75% 111.000000 8.0 \n",
"max 111.000000 8.0 \n",
"\n",
"[8 rows x 29 columns]"
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" <td>10.726913</td>\n",
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" <td>0.0</td>\n",
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" <td>117.000000</td>\n",
" <td>102.000000</td>\n",
" <td>8.0</td>\n",
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" <tr>\n",
" <th>25%</th>\n",
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"text/plain": [
" Rk Player Pos Age Tm G GS MP FG FGA ... AST \\\n",
"1 2 Steven Adams C 28 MEM 76 75 1999 5.0 9.2 ... 6.1 \n",
"75 61 Chris Boucher PF 29 TOR 80 9 1690 7.9 17.1 ... 0.7 \n",
"116 93 Clint Capela C 27 ATL 74 73 2042 8.9 14.5 ... 2.2 \n",
"138 108 Nic Claxton C 22 BRK 47 19 974 8.9 13.1 ... 2.1 \n",
"170 131 Dewayne Dedmon C 32 MIA 67 15 1065 7.7 13.6 ... 2.2 \n",
"219 164 Drew Eubanks C 24 TOT 71 31 1245 8.6 14.4 ... 3.3 \n",
"266 195 Rudy Gobert C 29 UTA 66 66 2120 8.4 11.8 ... 1.7 \n",
"319 235 Willy Hernangómez C 27 NOP 50 8 839 10.0 19.2 ... 3.7 \n",
"340 247 Richaun Holmes C 28 SAC 45 37 1074 8.9 13.4 ... 2.2 \n",
"351 253 Dwight Howard C 36 LAL 60 27 971 6.6 10.8 ... 1.7 \n",
"471 335 Kevon Looney C 25 GSW 82 80 1732 5.9 10.2 ... 4.6 \n",
"515 367 JaVale McGee C 34 PHO 74 17 1172 11.8 18.8 ... 1.7 \n",
"615 447 Jakob Poeltl C 26 SAS 68 67 1970 10.0 16.1 ... 4.6 \n",
"709 512 Jalen Smith PF 21 TOT 51 8 925 9.3 18.4 ... 1.3 \n",
"727 520 Isaiah Stewart C 20 DET 71 71 1816 6.7 13.2 ... 2.2 \n",
"751 538 Tristan Thompson PF 30 TOT 57 6 897 7.6 14.4 ... 1.8 \n",
"841 605 Ivica Zubac C 24 LAC 76 76 1852 8.2 13.1 ... 3.2 \n",
"\n",
" STL BLK TOV PF PTS Unnamed: 29 ORtg DRtg Clusters \n",
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" <td>Clint Capela</td>\n",
" <td>C</td>\n",
" <td>27</td>\n",
" <td>ATL</td>\n",
" <td>74</td>\n",
" <td>73</td>\n",
" <td>2042</td>\n",
" <td>8.9</td>\n",
" <td>14.5</td>\n",
" <td>...</td>\n",
" <td>2.2</td>\n",
" <td>1.3</td>\n",
" <td>2.2</td>\n",
" <td>1.1</td>\n",
" <td>4.0</td>\n",
" <td>19.7</td>\n",
" <td>NaN</td>\n",
" <td>132.0</td>\n",
" <td>109</td>\n",
" <td>9</td>\n",
" </tr>\n",
" <tr>\n",
" <th>138</th>\n",
" <td>108</td>\n",
" <td>Nic Claxton</td>\n",
" <td>C</td>\n",
" <td>22</td>\n",
" <td>BRK</td>\n",
" <td>47</td>\n",
" <td>19</td>\n",
" <td>974</td>\n",
" <td>8.9</td>\n",
" <td>13.1</td>\n",
" <td>...</td>\n",
" <td>2.1</td>\n",
" <td>1.2</td>\n",
" <td>2.5</td>\n",
" <td>1.9</td>\n",
" <td>5.5</td>\n",
" <td>20.4</td>\n",
" <td>NaN</td>\n",
" <td>130.0</td>\n",
" <td>111</td>\n",
" <td>9</td>\n",
" </tr>\n",
" <tr>\n",
" <th>170</th>\n",
" <td>131</td>\n",
" <td>Dewayne Dedmon</td>\n",
" <td>C</td>\n",
" <td>32</td>\n",
" <td>MIA</td>\n",
" <td>67</td>\n",
" <td>15</td>\n",
" <td>1065</td>\n",
" <td>7.7</td>\n",
" <td>13.6</td>\n",
" <td>...</td>\n",
" <td>2.2</td>\n",
" <td>1.1</td>\n",
" <td>2.0</td>\n",
" <td>3.3</td>\n",
" <td>8.2</td>\n",
" <td>19.8</td>\n",
" <td>NaN</td>\n",
" <td>117.0</td>\n",
" <td>105</td>\n",
" <td>9</td>\n",
" </tr>\n",
" <tr>\n",
" <th>219</th>\n",
" <td>164</td>\n",
" <td>Drew Eubanks</td>\n",
" <td>C</td>\n",
" <td>24</td>\n",
" <td>TOT</td>\n",
" <td>71</td>\n",
" <td>31</td>\n",
" <td>1245</td>\n",
" <td>8.6</td>\n",
" <td>14.4</td>\n",
" <td>...</td>\n",
" <td>3.3</td>\n",
" <td>1.2</td>\n",
" <td>1.6</td>\n",
" <td>3.2</td>\n",
" <td>4.7</td>\n",
" <td>21.2</td>\n",
" <td>NaN</td>\n",
" <td>120.0</td>\n",
" <td>113</td>\n",
" <td>9</td>\n",
" </tr>\n",
" <tr>\n",
" <th>266</th>\n",
" <td>195</td>\n",
" <td>Rudy Gobert</td>\n",
" <td>C</td>\n",
" <td>29</td>\n",
" <td>UTA</td>\n",
" <td>66</td>\n",
" <td>66</td>\n",
" <td>2120</td>\n",
" <td>8.4</td>\n",
" <td>11.8</td>\n",
" <td>...</td>\n",
" <td>1.7</td>\n",
" <td>1.0</td>\n",
" <td>3.2</td>\n",
" <td>2.8</td>\n",
" <td>4.1</td>\n",
" <td>23.9</td>\n",
" <td>NaN</td>\n",
" <td>137.0</td>\n",
" <td>103</td>\n",
" <td>9</td>\n",
" </tr>\n",
" <tr>\n",
" <th>319</th>\n",
" <td>235</td>\n",
" <td>Willy Hernangómez</td>\n",
" <td>C</td>\n",
" <td>27</td>\n",
" <td>NOP</td>\n",
" <td>50</td>\n",
" <td>8</td>\n",
" <td>839</td>\n",
" <td>10.0</td>\n",
" <td>19.2</td>\n",
" <td>...</td>\n",
" <td>3.7</td>\n",
" <td>1.2</td>\n",
" <td>1.1</td>\n",
" <td>3.0</td>\n",
" <td>5.7</td>\n",
" <td>26.7</td>\n",
" <td>NaN</td>\n",
" <td>122.0</td>\n",
" <td>111</td>\n",
" <td>9</td>\n",
" </tr>\n",
" <tr>\n",
" <th>340</th>\n",
" <td>247</td>\n",
" <td>Richaun Holmes</td>\n",
" <td>C</td>\n",
" <td>28</td>\n",
" <td>SAC</td>\n",
" <td>45</td>\n",
" <td>37</td>\n",
" <td>1074</td>\n",
" <td>8.9</td>\n",
" <td>13.4</td>\n",
" <td>...</td>\n",
" <td>2.2</td>\n",
" <td>0.8</td>\n",
" <td>1.8</td>\n",
" <td>2.5</td>\n",
" <td>5.7</td>\n",
" <td>21.0</td>\n",
" <td>NaN</td>\n",
" <td>127.0</td>\n",
" <td>114</td>\n",
" <td>9</td>\n",
" </tr>\n",
" <tr>\n",
" <th>351</th>\n",
" <td>253</td>\n",
" <td>Dwight Howard</td>\n",
" <td>C</td>\n",
" <td>36</td>\n",
" <td>LAL</td>\n",
" <td>60</td>\n",
" <td>27</td>\n",
" <td>971</td>\n",
" <td>6.6</td>\n",
" <td>10.8</td>\n",
" <td>...</td>\n",
" <td>1.7</td>\n",
" <td>1.7</td>\n",
" <td>1.8</td>\n",
" <td>2.3</td>\n",
" <td>5.7</td>\n",
" <td>18.4</td>\n",
" <td>NaN</td>\n",
" <td>128.0</td>\n",
" <td>109</td>\n",
" <td>9</td>\n",
" </tr>\n",
" <tr>\n",
" <th>471</th>\n",
" <td>335</td>\n",
" <td>Kevon Looney</td>\n",
" <td>C</td>\n",
" <td>25</td>\n",
" <td>GSW</td>\n",
" <td>82</td>\n",
" <td>80</td>\n",
" <td>1732</td>\n",
" <td>5.9</td>\n",
" <td>10.2</td>\n",
" <td>...</td>\n",
" <td>4.6</td>\n",
" <td>1.4</td>\n",
" <td>1.5</td>\n",
" <td>1.9</td>\n",
" <td>6.1</td>\n",
" <td>13.8</td>\n",
" <td>NaN</td>\n",
" <td>128.0</td>\n",
" <td>105</td>\n",
" <td>9</td>\n",
" </tr>\n",
" <tr>\n",
" <th>515</th>\n",
" <td>367</td>\n",
" <td>JaVale McGee</td>\n",
" <td>C</td>\n",
" <td>34</td>\n",
" <td>PHO</td>\n",
" <td>74</td>\n",
" <td>17</td>\n",
" <td>1172</td>\n",
" <td>11.8</td>\n",
" <td>18.8</td>\n",
" <td>...</td>\n",
" <td>1.7</td>\n",
" <td>0.9</td>\n",
" <td>3.3</td>\n",
" <td>4.0</td>\n",
" <td>7.4</td>\n",
" <td>27.9</td>\n",
" <td>NaN</td>\n",
" <td>118.0</td>\n",
" <td>102</td>\n",
" <td>9</td>\n",
" </tr>\n",
" <tr>\n",
" <th>615</th>\n",
" <td>447</td>\n",
" <td>Jakob Poeltl</td>\n",
" <td>C</td>\n",
" <td>26</td>\n",
" <td>SAS</td>\n",
" <td>68</td>\n",
" <td>67</td>\n",
" <td>1970</td>\n",
" <td>10.0</td>\n",
" <td>16.1</td>\n",
" <td>...</td>\n",
" <td>4.6</td>\n",
" <td>1.1</td>\n",
" <td>2.9</td>\n",
" <td>2.7</td>\n",
" <td>5.2</td>\n",
" <td>22.3</td>\n",
" <td>NaN</td>\n",
" <td>123.0</td>\n",
" <td>110</td>\n",
" <td>9</td>\n",
" </tr>\n",
" <tr>\n",
" <th>709</th>\n",
" <td>512</td>\n",
" <td>Jalen Smith</td>\n",
" <td>PF</td>\n",
" <td>21</td>\n",
" <td>TOT</td>\n",
" <td>51</td>\n",
" <td>8</td>\n",
" <td>925</td>\n",
" <td>9.3</td>\n",
" <td>18.4</td>\n",
" <td>...</td>\n",
" <td>1.3</td>\n",
" <td>0.8</td>\n",
" <td>2.2</td>\n",
" <td>2.2</td>\n",
" <td>5.0</td>\n",
" <td>24.7</td>\n",
" <td>NaN</td>\n",
" <td>119.0</td>\n",
" <td>111</td>\n",
" <td>9</td>\n",
" </tr>\n",
" <tr>\n",
" <th>727</th>\n",
" <td>520</td>\n",
" <td>Isaiah Stewart</td>\n",
" <td>C</td>\n",
" <td>20</td>\n",
" <td>DET</td>\n",
" <td>71</td>\n",
" <td>71</td>\n",
" <td>1816</td>\n",
" <td>6.7</td>\n",
" <td>13.2</td>\n",
" <td>...</td>\n",
" <td>2.2</td>\n",
" <td>0.6</td>\n",
" <td>2.1</td>\n",
" <td>2.3</td>\n",
" <td>5.7</td>\n",
" <td>15.8</td>\n",
" <td>NaN</td>\n",
" <td>113.0</td>\n",
" <td>112</td>\n",
" <td>9</td>\n",
" </tr>\n",
" <tr>\n",
" <th>751</th>\n",
" <td>538</td>\n",
" <td>Tristan Thompson</td>\n",
" <td>PF</td>\n",
" <td>30</td>\n",
" <td>TOT</td>\n",
" <td>57</td>\n",
" <td>6</td>\n",
" <td>897</td>\n",
" <td>7.6</td>\n",
" <td>14.4</td>\n",
" <td>...</td>\n",
" <td>1.8</td>\n",
" <td>1.2</td>\n",
" <td>1.1</td>\n",
" <td>2.4</td>\n",
" <td>5.3</td>\n",
" <td>18.6</td>\n",
" <td>NaN</td>\n",
" <td>112.0</td>\n",
" <td>114</td>\n",
" <td>9</td>\n",
" </tr>\n",
" <tr>\n",
" <th>841</th>\n",
" <td>605</td>\n",
" <td>Ivica Zubac</td>\n",
" <td>C</td>\n",
" <td>24</td>\n",
" <td>LAC</td>\n",
" <td>76</td>\n",
" <td>76</td>\n",
" <td>1852</td>\n",
" <td>8.2</td>\n",
" <td>13.1</td>\n",
" <td>...</td>\n",
" <td>3.2</td>\n",
" <td>1.0</td>\n",
" <td>2.0</td>\n",
" <td>3.0</td>\n",
" <td>5.4</td>\n",
" <td>20.8</td>\n",
" <td>NaN</td>\n",
" <td>126.0</td>\n",
" <td>107</td>\n",
" <td>9</td>\n",
" </tr>\n",
" </tbody>\n",
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" Age G GS MP FG FGA \\\n",
"count 17.000000 17.000000 17.000000 17.000000 17.000000 17.000000 \n",
"mean 27.176471 65.588235 40.294118 1434.294118 8.258824 14.194118 \n",
"std 4.376575 11.811323 29.147823 475.613914 1.645091 2.944586 \n",
"min 20.000000 45.000000 6.000000 839.000000 5.000000 9.200000 \n",
"25% 24.000000 57.000000 15.000000 974.000000 7.600000 13.100000 \n",
"50% 27.000000 68.000000 31.000000 1245.000000 8.400000 13.600000 \n",
"75% 29.000000 74.000000 71.000000 1852.000000 8.900000 16.100000 \n",
"max 36.000000 82.000000 80.000000 2120.000000 11.800000 19.200000 \n",
"\n",
" FG% 3P 3PA 3P% ... AST STL \\\n",
"count 17.000000 17.000000 17.000000 15.000000 ... 17.000000 17.000000 \n",
"mean 0.585294 0.382353 1.164706 0.292867 ... 2.664706 1.147059 \n",
"std 0.067423 0.669174 2.128069 0.259252 ... 1.403095 0.287484 \n",
"min 0.464000 0.000000 0.000000 0.000000 ... 0.700000 0.600000 \n",
"25% 0.528000 0.000000 0.000000 0.108500 ... 1.700000 1.000000 \n",
"50% 0.596000 0.100000 0.200000 0.326000 ... 2.200000 1.200000 \n",
"75% 0.626000 0.400000 0.900000 0.366500 ... 3.300000 1.300000 \n",
"max 0.713000 2.100000 6.800000 1.000000 ... 6.100000 1.700000 \n",
"\n",
" BLK TOV PF PTS Unnamed: 29 ORtg \\\n",
"count 17.000000 17.000000 17.000000 17.000000 0.0 17.000000 \n",
"mean 2.052941 2.505882 5.441176 20.582353 NaN 123.588235 \n",
"std 0.649151 0.735247 1.118067 4.093781 NaN 6.652620 \n",
"min 1.100000 1.100000 3.700000 12.600000 NaN 112.000000 \n",
"25% 1.600000 2.200000 5.000000 18.600000 NaN 119.000000 \n",
"50% 2.000000 2.500000 5.400000 20.800000 NaN 124.000000 \n",
"75% 2.200000 3.000000 5.700000 22.300000 NaN 128.000000 \n",
"max 3.300000 4.000000 8.200000 27.900000 NaN 137.000000 \n",
"\n",
" DRtg Clusters \n",
"count 17.000000 17.0 \n",
"mean 108.941176 9.0 \n",
"std 3.630954 0.0 \n",
"min 102.000000 9.0 \n",
"25% 107.000000 9.0 \n",
"50% 109.000000 9.0 \n",
"75% 111.000000 9.0 \n",
"max 114.000000 9.0 \n",
"\n",
"[8 rows x 29 columns]"
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" <td>8.258824</td>\n",
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" <td>1.164706</td>\n",
" <td>0.292867</td>\n",
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" <td>2.664706</td>\n",
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" <td>2.052941</td>\n",
" <td>2.505882</td>\n",
" <td>5.441176</td>\n",
" <td>20.582353</td>\n",
" <td>NaN</td>\n",
" <td>123.588235</td>\n",
" <td>108.941176</td>\n",
" <td>9.0</td>\n",
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" <th>std</th>\n",
" <td>4.376575</td>\n",
" <td>11.811323</td>\n",
" <td>29.147823</td>\n",
" <td>475.613914</td>\n",
" <td>1.645091</td>\n",
" <td>2.944586</td>\n",
" <td>0.067423</td>\n",
" <td>0.669174</td>\n",
" <td>2.128069</td>\n",
" <td>0.259252</td>\n",
" <td>...</td>\n",
" <td>1.403095</td>\n",
" <td>0.287484</td>\n",
" <td>0.649151</td>\n",
" <td>0.735247</td>\n",
" <td>1.118067</td>\n",
" <td>4.093781</td>\n",
" <td>NaN</td>\n",
" <td>6.652620</td>\n",
" <td>3.630954</td>\n",
" <td>0.0</td>\n",
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" <th>min</th>\n",
" <td>20.000000</td>\n",
" <td>45.000000</td>\n",
" <td>6.000000</td>\n",
" <td>839.000000</td>\n",
" <td>5.000000</td>\n",
" <td>9.200000</td>\n",
" <td>0.464000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>...</td>\n",
" <td>0.700000</td>\n",
" <td>0.600000</td>\n",
" <td>1.100000</td>\n",
" <td>1.100000</td>\n",
" <td>3.700000</td>\n",
" <td>12.600000</td>\n",
" <td>NaN</td>\n",
" <td>112.000000</td>\n",
" <td>102.000000</td>\n",
" <td>9.0</td>\n",
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" <th>25%</th>\n",
" <td>24.000000</td>\n",
" <td>57.000000</td>\n",
" <td>15.000000</td>\n",
" <td>974.000000</td>\n",
" <td>7.600000</td>\n",
" <td>13.100000</td>\n",
" <td>0.528000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.108500</td>\n",
" <td>...</td>\n",
" <td>1.700000</td>\n",
" <td>1.000000</td>\n",
" <td>1.600000</td>\n",
" <td>2.200000</td>\n",
" <td>5.000000</td>\n",
" <td>18.600000</td>\n",
" <td>NaN</td>\n",
" <td>119.000000</td>\n",
" <td>107.000000</td>\n",
" <td>9.0</td>\n",
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" <td>27.000000</td>\n",
" <td>68.000000</td>\n",
" <td>31.000000</td>\n",
" <td>1245.000000</td>\n",
" <td>8.400000</td>\n",
" <td>13.600000</td>\n",
" <td>0.596000</td>\n",
" <td>0.100000</td>\n",
" <td>0.200000</td>\n",
" <td>0.326000</td>\n",
" <td>...</td>\n",
" <td>2.200000</td>\n",
" <td>1.200000</td>\n",
" <td>2.000000</td>\n",
" <td>2.500000</td>\n",
" <td>5.400000</td>\n",
" <td>20.800000</td>\n",
" <td>NaN</td>\n",
" <td>124.000000</td>\n",
" <td>109.000000</td>\n",
" <td>9.0</td>\n",
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" <th>75%</th>\n",
" <td>29.000000</td>\n",
" <td>74.000000</td>\n",
" <td>71.000000</td>\n",
" <td>1852.000000</td>\n",
" <td>8.900000</td>\n",
" <td>16.100000</td>\n",
" <td>0.626000</td>\n",
" <td>0.400000</td>\n",
" <td>0.900000</td>\n",
" <td>0.366500</td>\n",
" <td>...</td>\n",
" <td>3.300000</td>\n",
" <td>1.300000</td>\n",
" <td>2.200000</td>\n",
" <td>3.000000</td>\n",
" <td>5.700000</td>\n",
" <td>22.300000</td>\n",
" <td>NaN</td>\n",
" <td>128.000000</td>\n",
" <td>111.000000</td>\n",
" <td>9.0</td>\n",
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" <th>max</th>\n",
" <td>36.000000</td>\n",
" <td>82.000000</td>\n",
" <td>80.000000</td>\n",
" <td>2120.000000</td>\n",
" <td>11.800000</td>\n",
" <td>19.200000</td>\n",
" <td>0.713000</td>\n",
" <td>2.100000</td>\n",
" <td>6.800000</td>\n",
" <td>1.000000</td>\n",
" <td>...</td>\n",
" <td>6.100000</td>\n",
" <td>1.700000</td>\n",
" <td>3.300000</td>\n",
" <td>4.000000</td>\n",
" <td>8.200000</td>\n",
" <td>27.900000</td>\n",
" <td>NaN</td>\n",
" <td>137.000000</td>\n",
" <td>114.000000</td>\n",
" <td>9.0</td>\n",
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" Rk Player Pos Age Tm G GS MP FG FGA ... \\\n",
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" <td>2250.500000</td>\n",
" <td>14.750000</td>\n",
" <td>28.050000</td>\n",
" <td>0.526000</td>\n",
" <td>1.750000</td>\n",
" <td>5.400000</td>\n",
" <td>0.332000</td>\n",
" <td>...</td>\n",
" <td>7.350000</td>\n",
" <td>1.650000</td>\n",
" <td>2.050000</td>\n",
" <td>4.700000</td>\n",
" <td>4.250000</td>\n",
" <td>44.35000</td>\n",
" <td>NaN</td>\n",
" <td>121.500000</td>\n",
" <td>105.500000</td>\n",
" <td>10.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>std</th>\n",
" <td>0.0</td>\n",
" <td>0.707107</td>\n",
" <td>0.707107</td>\n",
" <td>65.760931</td>\n",
" <td>0.353553</td>\n",
" <td>1.343503</td>\n",
" <td>0.038184</td>\n",
" <td>0.353553</td>\n",
" <td>0.141421</td>\n",
" <td>0.055154</td>\n",
" <td>...</td>\n",
" <td>1.626346</td>\n",
" <td>0.070711</td>\n",
" <td>0.070711</td>\n",
" <td>0.141421</td>\n",
" <td>0.494975</td>\n",
" <td>1.06066</td>\n",
" <td>NaN</td>\n",
" <td>3.535534</td>\n",
" <td>0.707107</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>min</th>\n",
" <td>27.0</td>\n",
" <td>67.000000</td>\n",
" <td>67.000000</td>\n",
" <td>2204.000000</td>\n",
" <td>14.500000</td>\n",
" <td>27.100000</td>\n",
" <td>0.499000</td>\n",
" <td>1.500000</td>\n",
" <td>5.300000</td>\n",
" <td>0.293000</td>\n",
" <td>...</td>\n",
" <td>6.200000</td>\n",
" <td>1.600000</td>\n",
" <td>2.000000</td>\n",
" <td>4.600000</td>\n",
" <td>3.900000</td>\n",
" <td>43.60000</td>\n",
" <td>NaN</td>\n",
" <td>119.000000</td>\n",
" <td>105.000000</td>\n",
" <td>10.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>25%</th>\n",
" <td>27.0</td>\n",
" <td>67.250000</td>\n",
" <td>67.250000</td>\n",
" <td>2227.250000</td>\n",
" <td>14.625000</td>\n",
" <td>27.575000</td>\n",
" <td>0.512500</td>\n",
" <td>1.625000</td>\n",
" <td>5.350000</td>\n",
" <td>0.312500</td>\n",
" <td>...</td>\n",
" <td>6.775000</td>\n",
" <td>1.625000</td>\n",
" <td>2.025000</td>\n",
" <td>4.650000</td>\n",
" <td>4.075000</td>\n",
" <td>43.97500</td>\n",
" <td>NaN</td>\n",
" <td>120.250000</td>\n",
" <td>105.250000</td>\n",
" <td>10.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>50%</th>\n",
" <td>27.0</td>\n",
" <td>67.500000</td>\n",
" <td>67.500000</td>\n",
" <td>2250.500000</td>\n",
" <td>14.750000</td>\n",
" <td>28.050000</td>\n",
" <td>0.526000</td>\n",
" <td>1.750000</td>\n",
" <td>5.400000</td>\n",
" <td>0.332000</td>\n",
" <td>...</td>\n",
" <td>7.350000</td>\n",
" <td>1.650000</td>\n",
" <td>2.050000</td>\n",
" <td>4.700000</td>\n",
" <td>4.250000</td>\n",
" <td>44.35000</td>\n",
" <td>NaN</td>\n",
" <td>121.500000</td>\n",
" <td>105.500000</td>\n",
" <td>10.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>75%</th>\n",
" <td>27.0</td>\n",
" <td>67.750000</td>\n",
" <td>67.750000</td>\n",
" <td>2273.750000</td>\n",
" <td>14.875000</td>\n",
" <td>28.525000</td>\n",
" <td>0.539500</td>\n",
" <td>1.875000</td>\n",
" <td>5.450000</td>\n",
" <td>0.351500</td>\n",
" <td>...</td>\n",
" <td>7.925000</td>\n",
" <td>1.675000</td>\n",
" <td>2.075000</td>\n",
" <td>4.750000</td>\n",
" <td>4.425000</td>\n",
" <td>44.72500</td>\n",
" <td>NaN</td>\n",
" <td>122.750000</td>\n",
" <td>105.750000</td>\n",
" <td>10.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>max</th>\n",
" <td>27.0</td>\n",
" <td>68.000000</td>\n",
" <td>68.000000</td>\n",
" <td>2297.000000</td>\n",
" <td>15.000000</td>\n",
" <td>29.000000</td>\n",
" <td>0.553000</td>\n",
" <td>2.000000</td>\n",
" <td>5.500000</td>\n",
" <td>0.371000</td>\n",
" <td>...</td>\n",
" <td>8.500000</td>\n",
" <td>1.700000</td>\n",
" <td>2.100000</td>\n",
" <td>4.800000</td>\n",
" <td>4.600000</td>\n",
" <td>45.10000</td>\n",
" <td>NaN</td>\n",
" <td>124.000000</td>\n",
" <td>106.000000</td>\n",
" <td>10.0</td>\n",
" </tr>\n",
" </tbody>\n",
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" Rk Player Pos Age Tm G GS MP FG FGA ... \\\n",
"46 38 Nicolas Batum PF 33 LAC 59 54 1462 6.0 13.0 ... \n",
"77 63 Avery Bradley SG 31 LAL 62 45 1406 5.0 11.9 ... \n",
"101 79 Troy Brown Jr. SF 22 CHI 66 7 1055 5.0 11.9 ... \n",
"151 119 Robert Covington PF-SF 31 TOT 71 42 1940 5.3 12.6 ... \n",
"152 119 Robert Covington PF 31 POR 48 40 1431 4.4 11.5 ... \n",
"158 121 Jae Crowder PF 31 PHO 67 67 1886 5.5 13.9 ... \n",
"209 158 Kessler Edwards SF 21 BRK 48 23 987 5.4 13.1 ... \n",
"275 203 Danny Green SF 34 PHI 62 28 1353 4.6 11.8 ... \n",
"325 239 George Hill SG 35 MIL 54 17 1253 4.5 10.5 ... \n",
"439 313 John Konchar SG 25 MEM 72 7 1292 5.0 9.7 ... \n",
"493 352 Cody Martin SF 26 CHO 71 11 1866 5.2 10.9 ... \n",
"580 418 Royce O'Neale SF 28 UTA 77 77 2406 4.2 9.1 ... \n",
"584 420 Chuma Okeke PF 23 ORL 70 20 1749 6.0 15.9 ... \n",
"621 453 Otto Porter Jr. PF 28 GSW 63 15 1396 6.7 14.5 ... \n",
"736 528 Garrett Temple SG 35 NOP 59 16 1098 5.0 13.3 ... \n",
"815 586 Kenrich Williams SF 27 OKC 49 0 1072 6.6 14.4 ... \n",
"828 597 Delon Wright SG 29 ATL 77 8 1452 4.1 9.1 ... \n",
"\n",
" AST STL BLK TOV PF PTS Unnamed: 29 ORtg DRtg Clusters \n",
"46 3.4 1.9 1.4 1.3 2.7 16.5 NaN 118.0 109 11 \n",
"77 1.6 1.8 0.3 1.3 4.0 13.4 NaN 106.0 116 11 \n",
"101 3.1 1.7 0.2 1.2 2.9 13.1 NaN 110.0 114 11 \n",
"151 2.3 2.6 2.3 1.9 4.8 15.2 NaN 108.0 110 11 \n",
"152 2.3 2.5 2.2 2.0 4.5 12.5 NaN 100.0 113 11 \n",
"158 3.2 2.4 0.8 1.4 4.4 16.1 NaN 109.0 105 11 \n",
"209 1.5 1.4 1.2 2.1 4.2 13.9 NaN 100.0 113 11 \n",
"275 2.4 2.2 1.4 1.7 3.9 13.5 NaN 106.0 111 11 \n",
"325 4.6 1.6 0.2 1.6 2.7 12.8 NaN 117.0 114 11 \n",
"439 4.0 1.7 0.8 1.1 3.3 12.9 NaN 133.0 109 11 \n",
"493 4.6 2.3 0.8 1.6 3.0 14.0 NaN 120.0 114 11 \n",
"580 3.9 1.8 0.7 1.6 3.8 11.7 NaN 122.0 111 11 \n",
"584 3.3 2.7 1.2 1.6 2.6 16.7 NaN 101.0 109 11 \n",
"621 3.3 2.4 1.0 1.3 2.9 18.0 NaN 121.0 104 11 \n",
"736 3.3 1.9 1.0 1.9 3.6 13.9 NaN 101.0 113 11 \n",
"815 4.9 2.0 0.5 2.1 3.7 16.5 NaN 111.0 113 11 \n",
"828 6.4 3.1 0.6 1.5 1.9 11.6 NaN 126.0 112 11 \n",
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" <th></th>\n",
" <th>Rk</th>\n",
" <th>Player</th>\n",
" <th>Pos</th>\n",
" <th>Age</th>\n",
" <th>Tm</th>\n",
" <th>G</th>\n",
" <th>GS</th>\n",
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" <th>...</th>\n",
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" <tr>\n",
" <th>46</th>\n",
" <td>38</td>\n",
" <td>Nicolas Batum</td>\n",
" <td>PF</td>\n",
" <td>33</td>\n",
" <td>LAC</td>\n",
" <td>59</td>\n",
" <td>54</td>\n",
" <td>1462</td>\n",
" <td>6.0</td>\n",
" <td>13.0</td>\n",
" <td>...</td>\n",
" <td>3.4</td>\n",
" <td>1.9</td>\n",
" <td>1.4</td>\n",
" <td>1.3</td>\n",
" <td>2.7</td>\n",
" <td>16.5</td>\n",
" <td>NaN</td>\n",
" <td>118.0</td>\n",
" <td>109</td>\n",
" <td>11</td>\n",
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" <th>77</th>\n",
" <td>63</td>\n",
" <td>Avery Bradley</td>\n",
" <td>SG</td>\n",
" <td>31</td>\n",
" <td>LAL</td>\n",
" <td>62</td>\n",
" <td>45</td>\n",
" <td>1406</td>\n",
" <td>5.0</td>\n",
" <td>11.9</td>\n",
" <td>...</td>\n",
" <td>1.6</td>\n",
" <td>1.8</td>\n",
" <td>0.3</td>\n",
" <td>1.3</td>\n",
" <td>4.0</td>\n",
" <td>13.4</td>\n",
" <td>NaN</td>\n",
" <td>106.0</td>\n",
" <td>116</td>\n",
" <td>11</td>\n",
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" <tr>\n",
" <th>101</th>\n",
" <td>79</td>\n",
" <td>Troy Brown Jr.</td>\n",
" <td>SF</td>\n",
" <td>22</td>\n",
" <td>CHI</td>\n",
" <td>66</td>\n",
" <td>7</td>\n",
" <td>1055</td>\n",
" <td>5.0</td>\n",
" <td>11.9</td>\n",
" <td>...</td>\n",
" <td>3.1</td>\n",
" <td>1.7</td>\n",
" <td>0.2</td>\n",
" <td>1.2</td>\n",
" <td>2.9</td>\n",
" <td>13.1</td>\n",
" <td>NaN</td>\n",
" <td>110.0</td>\n",
" <td>114</td>\n",
" <td>11</td>\n",
" </tr>\n",
" <tr>\n",
" <th>151</th>\n",
" <td>119</td>\n",
" <td>Robert Covington</td>\n",
" <td>PF-SF</td>\n",
" <td>31</td>\n",
" <td>TOT</td>\n",
" <td>71</td>\n",
" <td>42</td>\n",
" <td>1940</td>\n",
" <td>5.3</td>\n",
" <td>12.6</td>\n",
" <td>...</td>\n",
" <td>2.3</td>\n",
" <td>2.6</td>\n",
" <td>2.3</td>\n",
" <td>1.9</td>\n",
" <td>4.8</td>\n",
" <td>15.2</td>\n",
" <td>NaN</td>\n",
" <td>108.0</td>\n",
" <td>110</td>\n",
" <td>11</td>\n",
" </tr>\n",
" <tr>\n",
" <th>152</th>\n",
" <td>119</td>\n",
" <td>Robert Covington</td>\n",
" <td>PF</td>\n",
" <td>31</td>\n",
" <td>POR</td>\n",
" <td>48</td>\n",
" <td>40</td>\n",
" <td>1431</td>\n",
" <td>4.4</td>\n",
" <td>11.5</td>\n",
" <td>...</td>\n",
" <td>2.3</td>\n",
" <td>2.5</td>\n",
" <td>2.2</td>\n",
" <td>2.0</td>\n",
" <td>4.5</td>\n",
" <td>12.5</td>\n",
" <td>NaN</td>\n",
" <td>100.0</td>\n",
" <td>113</td>\n",
" <td>11</td>\n",
" </tr>\n",
" <tr>\n",
" <th>158</th>\n",
" <td>121</td>\n",
" <td>Jae Crowder</td>\n",
" <td>PF</td>\n",
" <td>31</td>\n",
" <td>PHO</td>\n",
" <td>67</td>\n",
" <td>67</td>\n",
" <td>1886</td>\n",
" <td>5.5</td>\n",
" <td>13.9</td>\n",
" <td>...</td>\n",
" <td>3.2</td>\n",
" <td>2.4</td>\n",
" <td>0.8</td>\n",
" <td>1.4</td>\n",
" <td>4.4</td>\n",
" <td>16.1</td>\n",
" <td>NaN</td>\n",
" <td>109.0</td>\n",
" <td>105</td>\n",
" <td>11</td>\n",
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" <tr>\n",
" <th>209</th>\n",
" <td>158</td>\n",
" <td>Kessler Edwards</td>\n",
" <td>SF</td>\n",
" <td>21</td>\n",
" <td>BRK</td>\n",
" <td>48</td>\n",
" <td>23</td>\n",
" <td>987</td>\n",
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" <td>1.5</td>\n",
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" <td>1.2</td>\n",
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" <td>4.2</td>\n",
" <td>13.9</td>\n",
" <td>NaN</td>\n",
" <td>100.0</td>\n",
" <td>113</td>\n",
" <td>11</td>\n",
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" <th>275</th>\n",
" <td>203</td>\n",
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" <td>34</td>\n",
" <td>PHI</td>\n",
" <td>62</td>\n",
" <td>28</td>\n",
" <td>1353</td>\n",
" <td>4.6</td>\n",
" <td>11.8</td>\n",
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" <td>1.7</td>\n",
" <td>3.9</td>\n",
" <td>13.5</td>\n",
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" <td>106.0</td>\n",
" <td>111</td>\n",
" <td>11</td>\n",
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" <tr>\n",
" <th>325</th>\n",
" <td>239</td>\n",
" <td>George Hill</td>\n",
" <td>SG</td>\n",
" <td>35</td>\n",
" <td>MIL</td>\n",
" <td>54</td>\n",
" <td>17</td>\n",
" <td>1253</td>\n",
" <td>4.5</td>\n",
" <td>10.5</td>\n",
" <td>...</td>\n",
" <td>4.6</td>\n",
" <td>1.6</td>\n",
" <td>0.2</td>\n",
" <td>1.6</td>\n",
" <td>2.7</td>\n",
" <td>12.8</td>\n",
" <td>NaN</td>\n",
" <td>117.0</td>\n",
" <td>114</td>\n",
" <td>11</td>\n",
" </tr>\n",
" <tr>\n",
" <th>439</th>\n",
" <td>313</td>\n",
" <td>John Konchar</td>\n",
" <td>SG</td>\n",
" <td>25</td>\n",
" <td>MEM</td>\n",
" <td>72</td>\n",
" <td>7</td>\n",
" <td>1292</td>\n",
" <td>5.0</td>\n",
" <td>9.7</td>\n",
" <td>...</td>\n",
" <td>4.0</td>\n",
" <td>1.7</td>\n",
" <td>0.8</td>\n",
" <td>1.1</td>\n",
" <td>3.3</td>\n",
" <td>12.9</td>\n",
" <td>NaN</td>\n",
" <td>133.0</td>\n",
" <td>109</td>\n",
" <td>11</td>\n",
" </tr>\n",
" <tr>\n",
" <th>493</th>\n",
" <td>352</td>\n",
" <td>Cody Martin</td>\n",
" <td>SF</td>\n",
" <td>26</td>\n",
" <td>CHO</td>\n",
" <td>71</td>\n",
" <td>11</td>\n",
" <td>1866</td>\n",
" <td>5.2</td>\n",
" <td>10.9</td>\n",
" <td>...</td>\n",
" <td>4.6</td>\n",
" <td>2.3</td>\n",
" <td>0.8</td>\n",
" <td>1.6</td>\n",
" <td>3.0</td>\n",
" <td>14.0</td>\n",
" <td>NaN</td>\n",
" <td>120.0</td>\n",
" <td>114</td>\n",
" <td>11</td>\n",
" </tr>\n",
" <tr>\n",
" <th>580</th>\n",
" <td>418</td>\n",
" <td>Royce O'Neale</td>\n",
" <td>SF</td>\n",
" <td>28</td>\n",
" <td>UTA</td>\n",
" <td>77</td>\n",
" <td>77</td>\n",
" <td>2406</td>\n",
" <td>4.2</td>\n",
" <td>9.1</td>\n",
" <td>...</td>\n",
" <td>3.9</td>\n",
" <td>1.8</td>\n",
" <td>0.7</td>\n",
" <td>1.6</td>\n",
" <td>3.8</td>\n",
" <td>11.7</td>\n",
" <td>NaN</td>\n",
" <td>122.0</td>\n",
" <td>111</td>\n",
" <td>11</td>\n",
" </tr>\n",
" <tr>\n",
" <th>584</th>\n",
" <td>420</td>\n",
" <td>Chuma Okeke</td>\n",
" <td>PF</td>\n",
" <td>23</td>\n",
" <td>ORL</td>\n",
" <td>70</td>\n",
" <td>20</td>\n",
" <td>1749</td>\n",
" <td>6.0</td>\n",
" <td>15.9</td>\n",
" <td>...</td>\n",
" <td>3.3</td>\n",
" <td>2.7</td>\n",
" <td>1.2</td>\n",
" <td>1.6</td>\n",
" <td>2.6</td>\n",
" <td>16.7</td>\n",
" <td>NaN</td>\n",
" <td>101.0</td>\n",
" <td>109</td>\n",
" <td>11</td>\n",
" </tr>\n",
" <tr>\n",
" <th>621</th>\n",
" <td>453</td>\n",
" <td>Otto Porter Jr.</td>\n",
" <td>PF</td>\n",
" <td>28</td>\n",
" <td>GSW</td>\n",
" <td>63</td>\n",
" <td>15</td>\n",
" <td>1396</td>\n",
" <td>6.7</td>\n",
" <td>14.5</td>\n",
" <td>...</td>\n",
" <td>3.3</td>\n",
" <td>2.4</td>\n",
" <td>1.0</td>\n",
" <td>1.3</td>\n",
" <td>2.9</td>\n",
" <td>18.0</td>\n",
" <td>NaN</td>\n",
" <td>121.0</td>\n",
" <td>104</td>\n",
" <td>11</td>\n",
" </tr>\n",
" <tr>\n",
" <th>736</th>\n",
" <td>528</td>\n",
" <td>Garrett Temple</td>\n",
" <td>SG</td>\n",
" <td>35</td>\n",
" <td>NOP</td>\n",
" <td>59</td>\n",
" <td>16</td>\n",
" <td>1098</td>\n",
" <td>5.0</td>\n",
" <td>13.3</td>\n",
" <td>...</td>\n",
" <td>3.3</td>\n",
" <td>1.9</td>\n",
" <td>1.0</td>\n",
" <td>1.9</td>\n",
" <td>3.6</td>\n",
" <td>13.9</td>\n",
" <td>NaN</td>\n",
" <td>101.0</td>\n",
" <td>113</td>\n",
" <td>11</td>\n",
" </tr>\n",
" <tr>\n",
" <th>815</th>\n",
" <td>586</td>\n",
" <td>Kenrich Williams</td>\n",
" <td>SF</td>\n",
" <td>27</td>\n",
" <td>OKC</td>\n",
" <td>49</td>\n",
" <td>0</td>\n",
" <td>1072</td>\n",
" <td>6.6</td>\n",
" <td>14.4</td>\n",
" <td>...</td>\n",
" <td>4.9</td>\n",
" <td>2.0</td>\n",
" <td>0.5</td>\n",
" <td>2.1</td>\n",
" <td>3.7</td>\n",
" <td>16.5</td>\n",
" <td>NaN</td>\n",
" <td>111.0</td>\n",
" <td>113</td>\n",
" <td>11</td>\n",
" </tr>\n",
" <tr>\n",
" <th>828</th>\n",
" <td>597</td>\n",
" <td>Delon Wright</td>\n",
" <td>SG</td>\n",
" <td>29</td>\n",
" <td>ATL</td>\n",
" <td>77</td>\n",
" <td>8</td>\n",
" <td>1452</td>\n",
" <td>4.1</td>\n",
" <td>9.1</td>\n",
" <td>...</td>\n",
" <td>6.4</td>\n",
" <td>3.1</td>\n",
" <td>0.6</td>\n",
" <td>1.5</td>\n",
" <td>1.9</td>\n",
" <td>11.6</td>\n",
" <td>NaN</td>\n",
" <td>126.0</td>\n",
" <td>112</td>\n",
" <td>11</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>17 rows × 33 columns</p>\n",
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" Age G GS MP FG FGA \\\n",
"count 17.000000 17.000000 17.000000 17.000000 17.000000 17.000000 \n",
"mean 28.823529 63.235294 28.058824 1476.705882 5.205882 12.182353 \n",
"std 4.390833 9.470543 22.506862 379.982691 0.770122 1.943012 \n",
"min 21.000000 48.000000 0.000000 987.000000 4.100000 9.100000 \n",
"25% 26.000000 59.000000 11.000000 1253.000000 4.600000 10.900000 \n",
"50% 29.000000 63.000000 20.000000 1406.000000 5.000000 11.900000 \n",
"75% 31.000000 71.000000 42.000000 1749.000000 5.500000 13.300000 \n",
"max 35.000000 77.000000 77.000000 2406.000000 6.700000 15.900000 \n",
"\n",
" FG% 3P 3PA 3P% ... AST STL \\\n",
"count 17.000000 17.000000 17.000000 17.000000 ... 17.000000 17.000000 \n",
"mean 0.430882 2.564706 7.088235 0.362471 ... 3.417647 2.117647 \n",
"std 0.039931 0.714091 2.007449 0.030761 ... 1.254111 0.455844 \n",
"min 0.376000 1.500000 3.900000 0.306000 ... 1.500000 1.400000 \n",
"25% 0.399000 1.900000 5.500000 0.343000 ... 2.400000 1.800000 \n",
"50% 0.423000 2.700000 7.200000 0.370000 ... 3.300000 2.000000 \n",
"75% 0.461000 3.200000 8.500000 0.384000 ... 4.000000 2.400000 \n",
"max 0.515000 3.800000 10.300000 0.413000 ... 6.400000 3.100000 \n",
"\n",
" BLK TOV PF PTS Unnamed: 29 ORtg \\\n",
"count 17.000000 17.000000 17.000000 17.000000 0.0 17.000000 \n",
"mean 0.976471 1.600000 3.464706 14.252941 NaN 112.294118 \n",
"std 0.607793 0.314245 0.797607 1.902997 NaN 9.916934 \n",
"min 0.200000 1.100000 1.900000 11.600000 NaN 100.000000 \n",
"25% 0.600000 1.300000 2.900000 12.900000 NaN 106.000000 \n",
"50% 0.800000 1.600000 3.600000 13.900000 NaN 110.000000 \n",
"75% 1.200000 1.900000 4.000000 16.100000 NaN 120.000000 \n",
"max 2.300000 2.100000 4.800000 18.000000 NaN 133.000000 \n",
"\n",
" DRtg Clusters \n",
"count 17.000000 17.0 \n",
"mean 111.176471 11.0 \n",
"std 3.225587 0.0 \n",
"min 104.000000 11.0 \n",
"25% 109.000000 11.0 \n",
"50% 112.000000 11.0 \n",
"75% 113.000000 11.0 \n",
"max 116.000000 11.0 \n",
"\n",
"[8 rows x 29 columns]"
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" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Age</th>\n",
" <th>G</th>\n",
" <th>GS</th>\n",
" <th>MP</th>\n",
" <th>FG</th>\n",
" <th>FGA</th>\n",
" <th>FG%</th>\n",
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" <tr>\n",
" <th>count</th>\n",
" <td>17.000000</td>\n",
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" <td>17.000000</td>\n",
" <td>17.000000</td>\n",
" <td>17.000000</td>\n",
" <td>17.000000</td>\n",
" <td>17.000000</td>\n",
" <td>17.000000</td>\n",
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" <td>17.000000</td>\n",
" <td>17.000000</td>\n",
" <td>17.000000</td>\n",
" <td>17.000000</td>\n",
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" <td>5.205882</td>\n",
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" <td>3.464706</td>\n",
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" <td>112.294118</td>\n",
" <td>111.176471</td>\n",
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" <td>22.506862</td>\n",
" <td>379.982691</td>\n",
" <td>0.770122</td>\n",
" <td>1.943012</td>\n",
" <td>0.039931</td>\n",
" <td>0.714091</td>\n",
" <td>2.007449</td>\n",
" <td>0.030761</td>\n",
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" <td>1.254111</td>\n",
" <td>0.455844</td>\n",
" <td>0.607793</td>\n",
" <td>0.314245</td>\n",
" <td>0.797607</td>\n",
" <td>1.902997</td>\n",
" <td>NaN</td>\n",
" <td>9.916934</td>\n",
" <td>3.225587</td>\n",
" <td>0.0</td>\n",
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" <td>21.000000</td>\n",
" <td>48.000000</td>\n",
" <td>0.000000</td>\n",
" <td>987.000000</td>\n",
" <td>4.100000</td>\n",
" <td>9.100000</td>\n",
" <td>0.376000</td>\n",
" <td>1.500000</td>\n",
" <td>3.900000</td>\n",
" <td>0.306000</td>\n",
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" <td>1.500000</td>\n",
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" <td>0.200000</td>\n",
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" <td>1.900000</td>\n",
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" <td>100.000000</td>\n",
" <td>104.000000</td>\n",
" <td>11.0</td>\n",
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" <th>25%</th>\n",
" <td>26.000000</td>\n",
" <td>59.000000</td>\n",
" <td>11.000000</td>\n",
" <td>1253.000000</td>\n",
" <td>4.600000</td>\n",
" <td>10.900000</td>\n",
" <td>0.399000</td>\n",
" <td>1.900000</td>\n",
" <td>5.500000</td>\n",
" <td>0.343000</td>\n",
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" <td>2.400000</td>\n",
" <td>1.800000</td>\n",
" <td>0.600000</td>\n",
" <td>1.300000</td>\n",
" <td>2.900000</td>\n",
" <td>12.900000</td>\n",
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" <td>106.000000</td>\n",
" <td>109.000000</td>\n",
" <td>11.0</td>\n",
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" <th>50%</th>\n",
" <td>29.000000</td>\n",
" <td>63.000000</td>\n",
" <td>20.000000</td>\n",
" <td>1406.000000</td>\n",
" <td>5.000000</td>\n",
" <td>11.900000</td>\n",
" <td>0.423000</td>\n",
" <td>2.700000</td>\n",
" <td>7.200000</td>\n",
" <td>0.370000</td>\n",
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" <td>3.300000</td>\n",
" <td>2.000000</td>\n",
" <td>0.800000</td>\n",
" <td>1.600000</td>\n",
" <td>3.600000</td>\n",
" <td>13.900000</td>\n",
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" <td>110.000000</td>\n",
" <td>112.000000</td>\n",
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" <th>75%</th>\n",
" <td>31.000000</td>\n",
" <td>71.000000</td>\n",
" <td>42.000000</td>\n",
" <td>1749.000000</td>\n",
" <td>5.500000</td>\n",
" <td>13.300000</td>\n",
" <td>0.461000</td>\n",
" <td>3.200000</td>\n",
" <td>8.500000</td>\n",
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" <td>4.000000</td>\n",
" <td>2.400000</td>\n",
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" <td>1.900000</td>\n",
" <td>4.000000</td>\n",
" <td>16.100000</td>\n",
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" <td>120.000000</td>\n",
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" <td>15.900000</td>\n",
" <td>0.515000</td>\n",
" <td>3.800000</td>\n",
" <td>10.300000</td>\n",
" <td>0.413000</td>\n",
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" <td>6.400000</td>\n",
" <td>3.100000</td>\n",
" <td>2.300000</td>\n",
" <td>2.100000</td>\n",
" <td>4.800000</td>\n",
" <td>18.000000</td>\n",
" <td>NaN</td>\n",
" <td>133.000000</td>\n",
" <td>116.000000</td>\n",
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" Rk Player Pos Age Tm G GS MP FG FGA ... AST \\\n",
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" <td>0.3</td>\n",
" <td>2.0</td>\n",
" <td>3.0</td>\n",
" <td>21.9</td>\n",
" <td>NaN</td>\n",
" <td>120.0</td>\n",
" <td>110</td>\n",
" <td>12</td>\n",
" </tr>\n",
" <tr>\n",
" <th>666</th>\n",
" <td>483</td>\n",
" <td>Terrence Ross</td>\n",
" <td>SG</td>\n",
" <td>30</td>\n",
" <td>ORL</td>\n",
" <td>63</td>\n",
" <td>0</td>\n",
" <td>1448</td>\n",
" <td>7.3</td>\n",
" <td>18.5</td>\n",
" <td>...</td>\n",
" <td>3.9</td>\n",
" <td>0.9</td>\n",
" <td>0.4</td>\n",
" <td>2.5</td>\n",
" <td>2.3</td>\n",
" <td>21.0</td>\n",
" <td>NaN</td>\n",
" <td>100.0</td>\n",
" <td>116</td>\n",
" <td>12</td>\n",
" </tr>\n",
" <tr>\n",
" <th>784</th>\n",
" <td>562</td>\n",
" <td>Kemba Walker</td>\n",
" <td>PG</td>\n",
" <td>31</td>\n",
" <td>NYK</td>\n",
" <td>37</td>\n",
" <td>37</td>\n",
" <td>948</td>\n",
" <td>7.9</td>\n",
" <td>19.5</td>\n",
" <td>...</td>\n",
" <td>6.9</td>\n",
" <td>1.4</td>\n",
" <td>0.4</td>\n",
" <td>2.5</td>\n",
" <td>2.0</td>\n",
" <td>22.7</td>\n",
" <td>NaN</td>\n",
" <td>112.0</td>\n",
" <td>113</td>\n",
" <td>12</td>\n",
" </tr>\n",
" <tr>\n",
" <th>803</th>\n",
" <td>577</td>\n",
" <td>Coby White</td>\n",
" <td>PG</td>\n",
" <td>21</td>\n",
" <td>CHI</td>\n",
" <td>61</td>\n",
" <td>17</td>\n",
" <td>1675</td>\n",
" <td>8.1</td>\n",
" <td>18.8</td>\n",
" <td>...</td>\n",
" <td>5.1</td>\n",
" <td>0.8</td>\n",
" <td>0.3</td>\n",
" <td>2.0</td>\n",
" <td>4.0</td>\n",
" <td>22.5</td>\n",
" <td>NaN</td>\n",
" <td>111.0</td>\n",
" <td>117</td>\n",
" <td>12</td>\n",
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" </tbody>\n",
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" Age G GS MP FG FGA \\\n",
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"75% 31.000000 73.250000 49.500000 2136.000000 8.200000 18.525000 \n",
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" FG% 3P 3PA 3P% ... AST STL \\\n",
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"50% 0.431000 3.300000 8.750000 0.387000 ... 5.800000 1.200000 \n",
"75% 0.458750 3.750000 9.525000 0.403000 ... 6.975000 1.325000 \n",
"max 0.487000 5.000000 12.900000 0.422000 ... 10.000000 2.000000 \n",
"\n",
" BLK TOV PF PTS Unnamed: 29 ORtg \\\n",
"count 20.000000 20.000000 20.000000 20.000000 0.0 20.000000 \n",
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"std 0.230503 0.484388 0.972192 2.608059 NaN 7.870498 \n",
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"25% 0.300000 2.000000 2.075000 18.750000 NaN 107.000000 \n",
"50% 0.400000 2.500000 3.050000 20.650000 NaN 111.500000 \n",
"75% 0.600000 2.700000 3.600000 22.000000 NaN 113.500000 \n",
"max 1.100000 3.100000 4.500000 23.500000 NaN 125.000000 \n",
"\n",
" DRtg Clusters \n",
"count 20.000000 20.0 \n",
"mean 115.350000 12.0 \n",
"std 2.518876 0.0 \n",
"min 110.000000 12.0 \n",
"25% 114.000000 12.0 \n",
"50% 115.000000 12.0 \n",
"75% 116.250000 12.0 \n",
"max 121.000000 12.0 \n",
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" Rk Player Pos Age Tm G GS MP FG FGA ... \\\n",
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" Age G GS MP FG FGA \\\n",
"count 4.000000 4.000000 4.000000 4.000000 4.000000 4.000000 \n",
"mean 25.500000 50.750000 50.750000 1503.250000 11.425000 24.600000 \n",
"std 2.516611 19.482898 19.482898 465.265068 1.236595 1.290994 \n",
"min 22.000000 34.000000 34.000000 1002.000000 9.700000 23.300000 \n",
"25% 25.000000 38.500000 38.500000 1303.500000 11.050000 23.600000 \n",
"50% 26.000000 45.500000 45.500000 1442.500000 11.700000 24.600000 \n",
"75% 26.500000 57.750000 57.750000 1642.250000 12.075000 25.600000 \n",
"max 28.000000 78.000000 78.000000 2126.000000 12.600000 25.900000 \n",
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" FG% 3P 3PA 3P% ... AST STL \\\n",
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"std 0.049054 1.146008 3.173326 0.060951 ... 1.042433 0.206155 \n",
"min 0.415000 0.400000 2.400000 0.186000 ... 1.900000 1.300000 \n",
"25% 0.442000 1.975000 6.975000 0.258750 ... 3.100000 1.300000 \n",
"50% 0.455000 2.550000 8.600000 0.296500 ... 3.750000 1.450000 \n",
"75% 0.477250 2.675000 8.775000 0.312250 ... 4.050000 1.625000 \n",
"max 0.532000 2.900000 9.000000 0.319000 ... 4.200000 1.700000 \n",
"\n",
" BLK TOV PF PTS Unnamed: 29 ORtg \\\n",
"count 4.000000 4.000000 4.00000 4.000000 0.0 4.000000 \n",
"mean 3.225000 2.775000 4.60000 31.975000 NaN 113.250000 \n",
"std 0.531507 0.095743 1.15181 2.605603 NaN 3.095696 \n",
"min 2.800000 2.700000 3.30000 28.600000 NaN 109.000000 \n",
"25% 2.950000 2.700000 4.12500 30.850000 NaN 112.000000 \n",
"50% 3.050000 2.750000 4.50000 32.250000 NaN 114.000000 \n",
"75% 3.325000 2.825000 4.97500 33.375000 NaN 115.250000 \n",
"max 4.000000 2.900000 6.10000 34.800000 NaN 116.000000 \n",
"\n",
" DRtg Clusters \n",
"count 4.000000 4.0 \n",
"mean 107.000000 13.0 \n",
"std 1.414214 0.0 \n",
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"25% 106.000000 13.0 \n",
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" <td>3.095696</td>\n",
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" <td>0.400000</td>\n",
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" <td>2.700000</td>\n",
" <td>4.12500</td>\n",
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" <td>45.500000</td>\n",
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" <td>11.700000</td>\n",
" <td>24.600000</td>\n",
" <td>0.455000</td>\n",
" <td>2.550000</td>\n",
" <td>8.600000</td>\n",
" <td>0.296500</td>\n",
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" <td>3.750000</td>\n",
" <td>1.450000</td>\n",
" <td>3.050000</td>\n",
" <td>2.750000</td>\n",
" <td>4.50000</td>\n",
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" <td>57.750000</td>\n",
" <td>1642.250000</td>\n",
" <td>12.075000</td>\n",
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" <td>25.900000</td>\n",
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" <td>6.10000</td>\n",
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" Rk Player Pos Age Tm G GS MP FG FGA \\\n",
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"137 107 Jordan Clarkson SG 29 UTA 79 1 2141 10.8 25.7 \n",
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"321 237 Buddy Hield SG 29 TOT 81 32 2499 8.6 21.3 \n",
"322 237 Buddy Hield SG 29 SAC 55 6 1574 8.1 21.2 \n",
"323 237 Buddy Hield SG 29 IND 26 26 925 9.6 21.4 \n",
"362 261 Bones Hyland PG 21 DEN 69 4 1310 8.6 21.4 \n",
"488 347 Tre Mann PG 20 OKC 60 26 1367 8.2 21.0 \n",
"509 362 CJ McCollum SG 30 POR 36 36 1267 11.2 25.6 \n",
"521 373 Ben McLemore SG 28 POR 64 6 1285 8.2 20.5 \n",
"595 430 Cedi Osman SF 26 CLE 66 3 1462 8.4 19.5 \n",
"597 432 Kelly Oubre Jr. SF 26 CHO 76 13 1999 9.8 22.4 \n",
"638 465 Immanuel Quickley PG 22 NYK 78 3 1802 7.9 20.1 \n",
"642 469 Cam Reddish SF 22 TOT 49 7 1012 8.0 19.9 \n",
"667 484 Terry Rozier SG 27 CHO 73 73 2458 10.1 22.8 \n",
"697 504 Anfernee Simons SG 22 POR 57 30 1681 10.3 23.2 \n",
"750 537 Klay Thompson SG 31 GSW 32 32 941 12.7 29.7 \n",
"764 547 Gary Trent Jr. SG 23 TOR 70 69 2448 9.2 22.2 \n",
"792 568 Duane Washington Jr. PG 21 IND 48 7 968 8.8 21.6 \n",
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" <td>OG Anunoby</td>\n",
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" <td>23.8</td>\n",
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" <td>112.0</td>\n",
" <td>111</td>\n",
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" <th>36</th>\n",
" <td>28</td>\n",
" <td>Desmond Bane</td>\n",
" <td>SF</td>\n",
" <td>23</td>\n",
" <td>MEM</td>\n",
" <td>76</td>\n",
" <td>76</td>\n",
" <td>2266</td>\n",
" <td>10.7</td>\n",
" <td>23.2</td>\n",
" <td>...</td>\n",
" <td>4.4</td>\n",
" <td>1.9</td>\n",
" <td>0.6</td>\n",
" <td>2.3</td>\n",
" <td>4.1</td>\n",
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" <th>67</th>\n",
" <td>54</td>\n",
" <td>Bogdan Bogdanović</td>\n",
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" <td>ATL</td>\n",
" <td>63</td>\n",
" <td>27</td>\n",
" <td>1848</td>\n",
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" <th>137</th>\n",
" <td>107</td>\n",
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" <td>29</td>\n",
" <td>UTA</td>\n",
" <td>79</td>\n",
" <td>1</td>\n",
" <td>2141</td>\n",
" <td>10.8</td>\n",
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" <td>111.0</td>\n",
" <td>112</td>\n",
" <td>14</td>\n",
" </tr>\n",
" <tr>\n",
" <th>597</th>\n",
" <td>432</td>\n",
" <td>Kelly Oubre Jr.</td>\n",
" <td>SF</td>\n",
" <td>26</td>\n",
" <td>CHO</td>\n",
" <td>76</td>\n",
" <td>13</td>\n",
" <td>1999</td>\n",
" <td>9.8</td>\n",
" <td>22.4</td>\n",
" <td>...</td>\n",
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" <td>1.8</td>\n",
" <td>0.7</td>\n",
" <td>1.6</td>\n",
" <td>4.5</td>\n",
" <td>27.3</td>\n",
" <td>NaN</td>\n",
" <td>111.0</td>\n",
" <td>115</td>\n",
" <td>14</td>\n",
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" <tr>\n",
" <th>638</th>\n",
" <td>465</td>\n",
" <td>Immanuel Quickley</td>\n",
" <td>PG</td>\n",
" <td>22</td>\n",
" <td>NYK</td>\n",
" <td>78</td>\n",
" <td>3</td>\n",
" <td>1802</td>\n",
" <td>7.9</td>\n",
" <td>20.1</td>\n",
" <td>...</td>\n",
" <td>7.6</td>\n",
" <td>1.5</td>\n",
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" <td>24.5</td>\n",
" <td>NaN</td>\n",
" <td>114.0</td>\n",
" <td>112</td>\n",
" <td>14</td>\n",
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" <tr>\n",
" <th>642</th>\n",
" <td>469</td>\n",
" <td>Cam Reddish</td>\n",
" <td>SF</td>\n",
" <td>22</td>\n",
" <td>TOT</td>\n",
" <td>49</td>\n",
" <td>7</td>\n",
" <td>1012</td>\n",
" <td>8.0</td>\n",
" <td>19.9</td>\n",
" <td>...</td>\n",
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" <td>0.7</td>\n",
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" <td>2.9</td>\n",
" <td>24.2</td>\n",
" <td>NaN</td>\n",
" <td>105.0</td>\n",
" <td>114</td>\n",
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" <tr>\n",
" <th>667</th>\n",
" <td>484</td>\n",
" <td>Terry Rozier</td>\n",
" <td>SG</td>\n",
" <td>27</td>\n",
" <td>CHO</td>\n",
" <td>73</td>\n",
" <td>73</td>\n",
" <td>2458</td>\n",
" <td>10.1</td>\n",
" <td>22.8</td>\n",
" <td>...</td>\n",
" <td>6.4</td>\n",
" <td>1.8</td>\n",
" <td>0.5</td>\n",
" <td>1.9</td>\n",
" <td>2.3</td>\n",
" <td>27.5</td>\n",
" <td>NaN</td>\n",
" <td>117.0</td>\n",
" <td>115</td>\n",
" <td>14</td>\n",
" </tr>\n",
" <tr>\n",
" <th>697</th>\n",
" <td>504</td>\n",
" <td>Anfernee Simons</td>\n",
" <td>SG</td>\n",
" <td>22</td>\n",
" <td>POR</td>\n",
" <td>57</td>\n",
" <td>30</td>\n",
" <td>1681</td>\n",
" <td>10.3</td>\n",
" <td>23.2</td>\n",
" <td>...</td>\n",
" <td>6.4</td>\n",
" <td>0.9</td>\n",
" <td>0.2</td>\n",
" <td>3.3</td>\n",
" <td>3.2</td>\n",
" <td>28.7</td>\n",
" <td>NaN</td>\n",
" <td>112.0</td>\n",
" <td>121</td>\n",
" <td>14</td>\n",
" </tr>\n",
" <tr>\n",
" <th>750</th>\n",
" <td>537</td>\n",
" <td>Klay Thompson</td>\n",
" <td>SG</td>\n",
" <td>31</td>\n",
" <td>GSW</td>\n",
" <td>32</td>\n",
" <td>32</td>\n",
" <td>941</td>\n",
" <td>12.7</td>\n",
" <td>29.7</td>\n",
" <td>...</td>\n",
" <td>4.6</td>\n",
" <td>0.8</td>\n",
" <td>0.9</td>\n",
" <td>2.2</td>\n",
" <td>2.8</td>\n",
" <td>33.8</td>\n",
" <td>NaN</td>\n",
" <td>107.0</td>\n",
" <td>110</td>\n",
" <td>14</td>\n",
" </tr>\n",
" <tr>\n",
" <th>764</th>\n",
" <td>547</td>\n",
" <td>Gary Trent Jr.</td>\n",
" <td>SG</td>\n",
" <td>23</td>\n",
" <td>TOR</td>\n",
" <td>70</td>\n",
" <td>69</td>\n",
" <td>2448</td>\n",
" <td>9.2</td>\n",
" <td>22.2</td>\n",
" <td>...</td>\n",
" <td>2.9</td>\n",
" <td>2.5</td>\n",
" <td>0.4</td>\n",
" <td>1.5</td>\n",
" <td>2.9</td>\n",
" <td>26.2</td>\n",
" <td>NaN</td>\n",
" <td>114.0</td>\n",
" <td>112</td>\n",
" <td>14</td>\n",
" </tr>\n",
" <tr>\n",
" <th>792</th>\n",
" <td>568</td>\n",
" <td>Duane Washington Jr.</td>\n",
" <td>PG</td>\n",
" <td>21</td>\n",
" <td>IND</td>\n",
" <td>48</td>\n",
" <td>7</td>\n",
" <td>968</td>\n",
" <td>8.8</td>\n",
" <td>21.6</td>\n",
" <td>...</td>\n",
" <td>4.3</td>\n",
" <td>1.3</td>\n",
" <td>0.2</td>\n",
" <td>2.9</td>\n",
" <td>3.3</td>\n",
" <td>23.9</td>\n",
" <td>NaN</td>\n",
" <td>101.0</td>\n",
" <td>119</td>\n",
" <td>14</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
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" Age G GS MP FG FGA \\\n",
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" FG% 3P 3PA 3P% ... AST STL \\\n",
"count 24.000000 24.000000 24.000000 24.000000 ... 24.000000 24.000000 \n",
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"50% 0.415500 4.350000 11.650000 0.364500 ... 4.450000 1.500000 \n",
"75% 0.437000 4.950000 13.325000 0.378500 ... 5.550000 1.800000 \n",
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"\n",
" BLK TOV PF PTS Unnamed: 29 ORtg \\\n",
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"50% 0.500000 2.650000 3.550000 24.950000 NaN 108.500000 \n",
"75% 0.700000 3.000000 3.950000 27.350000 NaN 112.000000 \n",
"max 0.900000 3.300000 5.700000 33.800000 NaN 119.000000 \n",
"\n",
" DRtg Clusters \n",
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"mean 114.750000 14.0 \n",
"std 3.110291 0.0 \n",
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"25% 112.000000 14.0 \n",
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" <td>114.750000</td>\n",
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" <td>0.384387</td>\n",
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" <td>0.529903</td>\n",
" <td>0.716865</td>\n",
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" <td>5.963658</td>\n",
" <td>3.110291</td>\n",
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" <td>925.000000</td>\n",
" <td>7.90000</td>\n",
" <td>19.500000</td>\n",
" <td>0.372000</td>\n",
" <td>3.200000</td>\n",
" <td>9.000000</td>\n",
" <td>0.311000</td>\n",
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" <td>0.100000</td>\n",
" <td>1.500000</td>\n",
" <td>2.300000</td>\n",
" <td>22.300000</td>\n",
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" <td>8.47500</td>\n",
" <td>20.875000</td>\n",
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" <td>3.800000</td>\n",
" <td>11.075000</td>\n",
" <td>0.354250</td>\n",
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" <td>2.200000</td>\n",
" <td>3.275000</td>\n",
" <td>24.125000</td>\n",
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" <td>104.750000</td>\n",
" <td>112.000000</td>\n",
" <td>14.0</td>\n",
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" <td>25.000000</td>\n",
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" <td>26.000000</td>\n",
" <td>1619.500000</td>\n",
" <td>8.85000</td>\n",
" <td>21.400000</td>\n",
" <td>0.415500</td>\n",
" <td>4.350000</td>\n",
" <td>11.650000</td>\n",
" <td>0.364500</td>\n",
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" <td>4.450000</td>\n",
" <td>1.500000</td>\n",
" <td>0.500000</td>\n",
" <td>2.650000</td>\n",
" <td>3.550000</td>\n",
" <td>24.950000</td>\n",
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" <td>108.500000</td>\n",
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" <td>9.87500</td>\n",
" <td>22.975000</td>\n",
" <td>0.437000</td>\n",
" <td>4.950000</td>\n",
" <td>13.325000</td>\n",
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" <td>3.950000</td>\n",
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" <td>15.900000</td>\n",
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" <td>2.500000</td>\n",
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" <td>5.700000</td>\n",
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" <td>119.000000</td>\n",
" <td>121.000000</td>\n",
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" Rk Player Pos Age Tm G GS MP FG FGA ... \\\n",
"39 31 Harrison Barnes PF 29 SAC 77 77 2587 7.3 15.5 ... \n",
"41 33 RJ Barrett SF 21 NYK 70 70 2417 10.1 24.7 ... \n",
"68 55 Bojan Bogdanović PF 32 UTA 69 69 2131 9.8 21.5 ... \n",
"87 71 Dillon Brooks SF 26 MEM 32 31 885 12.3 28.4 ... \n",
"102 80 Jalen Brunson PG 25 DAL 79 61 2524 10.1 20.1 ... \n",
"178 139 Spencer Dinwiddie PG 28 TOT 67 51 1980 7.7 18.5 ... \n",
"179 139 Spencer Dinwiddie PG 28 WAS 44 44 1330 6.9 18.3 ... \n",
"202 151 Chris Duarte SG 24 IND 55 39 1541 8.5 19.7 ... \n",
"273 201 Jerami Grant PF 27 DET 47 47 1500 9.7 22.7 ... \n",
"277 205 Jalen Green SG 19 HOU 67 67 2138 9.0 21.2 ... \n",
"285 213 Rui Hachimura PF 23 WAS 42 13 943 9.8 20.0 ... \n",
"303 224 Tobias Harris PF 29 PHI 73 73 2543 9.7 20.0 ... \n",
"313 232 Gordon Hayward SF 31 CHO 49 48 1564 8.7 18.9 ... \n",
"359 259 De'Andre Hunter SF 24 ATL 53 52 1577 7.9 17.9 ... \n",
"397 286 Keldon Johnson SF 22 SAS 75 74 2392 9.4 20.3 ... \n",
"463 329 Caris LeVert SG 27 TOT 58 49 1781 10.5 23.6 ... \n",
"464 329 Caris LeVert SG 27 IND 39 39 1214 11.2 25.1 ... \n",
"485 344 Théo Maledon PG 20 OKC 51 7 908 6.4 17.0 ... \n",
"501 358 Tyrese Maxey PG 21 PHI 75 74 2650 9.1 18.7 ... \n",
"550 393 Marcus Morris PF 32 LAC 54 54 1564 9.4 21.6 ... \n",
"575 413 Jaylen Nowell SG 22 MIN 62 1 975 9.6 20.2 ... \n",
"629 459 Norman Powell SF-SG 28 TOT 45 41 1458 9.4 20.3 ... \n",
"630 459 Norman Powell SF 28 POR 40 39 1333 9.1 19.9 ... \n",
"682 493 Dennis Schröder SG 28 BOS 49 25 1433 8.9 20.3 ... \n",
"744 534 Cam Thomas SG 20 BRK 67 2 1176 9.0 20.7 ... \n",
"780 559 Franz Wagner SF 20 ORL 79 79 2429 9.1 19.4 ... \n",
"785 563 Lonnie Walker IV SG 23 SAS 70 6 1612 9.3 22.7 ... \n",
"804 578 Derrick White SG 27 TOT 75 52 2199 7.4 17.7 ... \n",
"805 578 Derrick White SG 27 SAS 49 48 1486 7.8 18.4 ... \n",
"811 582 Andrew Wiggins SF 26 GSW 73 73 2329 9.9 21.3 ... \n",
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"39 3.5 1.0 0.3 2.2 1.7 23.5 NaN 121.0 118 15 \n",
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"359 2.1 1.1 0.7 2.2 4.8 22.1 NaN 106.0 117 15 \n",
"397 3.2 1.2 0.3 1.8 3.0 25.6 NaN 114.0 114 15 \n",
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" <th>39</th>\n",
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" <td>0.9</td>\n",
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" <td>29.0</td>\n",
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" <td>103.0</td>\n",
" <td>113</td>\n",
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" <th>68</th>\n",
" <td>55</td>\n",
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" <td>69</td>\n",
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" <td>9.8</td>\n",
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" <td>2.8</td>\n",
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" <td>71</td>\n",
" <td>Dillon Brooks</td>\n",
" <td>SF</td>\n",
" <td>26</td>\n",
" <td>MEM</td>\n",
" <td>32</td>\n",
" <td>31</td>\n",
" <td>885</td>\n",
" <td>12.3</td>\n",
" <td>28.4</td>\n",
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" <td>4.8</td>\n",
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" <td>25</td>\n",
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" <th>178</th>\n",
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" <td>329</td>\n",
" <td>Caris LeVert</td>\n",
" <td>SG</td>\n",
" <td>27</td>\n",
" <td>TOT</td>\n",
" <td>58</td>\n",
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" <td>39</td>\n",
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" <td>1214</td>\n",
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" <td>20</td>\n",
" <td>OKC</td>\n",
" <td>51</td>\n",
" <td>7</td>\n",
" <td>908</td>\n",
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" <td>115</td>\n",
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" <td>28</td>\n",
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" <td>45</td>\n",
" <td>41</td>\n",
" <td>1458</td>\n",
" <td>9.4</td>\n",
" <td>20.3</td>\n",
" <td>...</td>\n",
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" <th>780</th>\n",
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" <td>79</td>\n",
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" <th>785</th>\n",
" <td>563</td>\n",
" <td>Lonnie Walker IV</td>\n",
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" <td>23</td>\n",
" <td>SAS</td>\n",
" <td>70</td>\n",
" <td>6</td>\n",
" <td>1612</td>\n",
" <td>9.3</td>\n",
" <td>22.7</td>\n",
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" <td>115</td>\n",
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" <th>804</th>\n",
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" <td>27</td>\n",
" <td>TOT</td>\n",
" <td>75</td>\n",
" <td>52</td>\n",
" <td>2199</td>\n",
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" <td>17.7</td>\n",
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" <tr>\n",
" <th>805</th>\n",
" <td>578</td>\n",
" <td>Derrick White</td>\n",
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" <td>1486</td>\n",
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" <td>18.4</td>\n",
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" <td>113</td>\n",
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" <th>811</th>\n",
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" <td>26</td>\n",
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" <td>3.3</td>\n",
" <td>26.3</td>\n",
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" <td>109.0</td>\n",
" <td>109</td>\n",
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" Age G GS MP FG FGA \\\n",
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"75% 0.466000 3.175000 8.400000 0.392500 ... 6.750000 1.400000 \n",
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"\n",
" BLK TOV PF PTS Unnamed: 29 ORtg \\\n",
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"75% 0.700000 2.80000 3.675000 27.050000 NaN 114.000000 \n",
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"\n",
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"mean 114.8000 15.0 \n",
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"min 109.0000 15.0 \n",
"25% 113.0000 15.0 \n",
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"max 120.0000 15.0 \n",
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" <td>20.486667</td>\n",
" <td>0.444000</td>\n",
" <td>2.760000</td>\n",
" <td>7.720000</td>\n",
" <td>0.358700</td>\n",
" <td>...</td>\n",
" <td>5.066667</td>\n",
" <td>1.290000</td>\n",
" <td>0.583333</td>\n",
" <td>2.52000</td>\n",
" <td>3.356667</td>\n",
" <td>25.280000</td>\n",
" <td>NaN</td>\n",
" <td>110.700000</td>\n",
" <td>114.8000</td>\n",
" <td>15.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>std</th>\n",
" <td>3.702127</td>\n",
" <td>13.902989</td>\n",
" <td>23.502140</td>\n",
" <td>560.128935</td>\n",
" <td>1.251757</td>\n",
" <td>2.612006</td>\n",
" <td>0.030783</td>\n",
" <td>0.554356</td>\n",
" <td>1.418936</td>\n",
" <td>0.042854</td>\n",
" <td>...</td>\n",
" <td>2.090757</td>\n",
" <td>0.279593</td>\n",
" <td>0.369607</td>\n",
" <td>0.48023</td>\n",
" <td>0.742634</td>\n",
" <td>2.827135</td>\n",
" <td>NaN</td>\n",
" <td>5.718391</td>\n",
" <td>2.6704</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>min</th>\n",
" <td>19.000000</td>\n",
" <td>32.000000</td>\n",
" <td>1.000000</td>\n",
" <td>885.000000</td>\n",
" <td>6.400000</td>\n",
" <td>15.500000</td>\n",
" <td>0.375000</td>\n",
" <td>1.900000</td>\n",
" <td>5.000000</td>\n",
" <td>0.270000</td>\n",
" <td>...</td>\n",
" <td>2.100000</td>\n",
" <td>0.800000</td>\n",
" <td>0.000000</td>\n",
" <td>1.70000</td>\n",
" <td>1.700000</td>\n",
" <td>19.400000</td>\n",
" <td>NaN</td>\n",
" <td>99.000000</td>\n",
" <td>109.0000</td>\n",
" <td>15.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>25%</th>\n",
" <td>22.250000</td>\n",
" <td>49.000000</td>\n",
" <td>39.000000</td>\n",
" <td>1358.000000</td>\n",
" <td>8.550000</td>\n",
" <td>18.750000</td>\n",
" <td>0.426000</td>\n",
" <td>2.425000</td>\n",
" <td>6.725000</td>\n",
" <td>0.320750</td>\n",
" <td>...</td>\n",
" <td>3.425000</td>\n",
" <td>1.025000</td>\n",
" <td>0.300000</td>\n",
" <td>2.22500</td>\n",
" <td>2.900000</td>\n",
" <td>23.500000</td>\n",
" <td>NaN</td>\n",
" <td>108.000000</td>\n",
" <td>113.0000</td>\n",
" <td>15.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>50%</th>\n",
" <td>26.500000</td>\n",
" <td>60.000000</td>\n",
" <td>48.500000</td>\n",
" <td>1570.500000</td>\n",
" <td>9.200000</td>\n",
" <td>20.150000</td>\n",
" <td>0.443000</td>\n",
" <td>2.600000</td>\n",
" <td>8.050000</td>\n",
" <td>0.362500</td>\n",
" <td>...</td>\n",
" <td>4.550000</td>\n",
" <td>1.350000</td>\n",
" <td>0.600000</td>\n",
" <td>2.50000</td>\n",
" <td>3.350000</td>\n",
" <td>25.100000</td>\n",
" <td>NaN</td>\n",
" <td>109.500000</td>\n",
" <td>115.0000</td>\n",
" <td>15.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>75%</th>\n",
" <td>28.000000</td>\n",
" <td>72.250000</td>\n",
" <td>68.500000</td>\n",
" <td>2296.500000</td>\n",
" <td>9.775000</td>\n",
" <td>21.450000</td>\n",
" <td>0.466000</td>\n",
" <td>3.175000</td>\n",
" <td>8.400000</td>\n",
" <td>0.392500</td>\n",
" <td>...</td>\n",
" <td>6.750000</td>\n",
" <td>1.400000</td>\n",
" <td>0.700000</td>\n",
" <td>2.80000</td>\n",
" <td>3.675000</td>\n",
" <td>27.050000</td>\n",
" <td>NaN</td>\n",
" <td>114.000000</td>\n",
" <td>116.7500</td>\n",
" <td>15.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>max</th>\n",
" <td>32.000000</td>\n",
" <td>79.000000</td>\n",
" <td>79.000000</td>\n",
" <td>2650.000000</td>\n",
" <td>12.300000</td>\n",
" <td>28.400000</td>\n",
" <td>0.502000</td>\n",
" <td>4.200000</td>\n",
" <td>10.900000</td>\n",
" <td>0.447000</td>\n",
" <td>...</td>\n",
" <td>9.500000</td>\n",
" <td>1.900000</td>\n",
" <td>1.600000</td>\n",
" <td>3.60000</td>\n",
" <td>5.700000</td>\n",
" <td>31.900000</td>\n",
" <td>NaN</td>\n",
" <td>121.000000</td>\n",
" <td>120.0000</td>\n",
" <td>15.0</td>\n",
" </tr>\n",
" </tbody>\n",
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" Rk Player Pos Age Tm G GS MP FG FGA ... \\\n",
"0 1 Precious Achiuwa C 22 TOR 73 28 1725 7.7 17.5 ... \n",
"14 11 Kyle Anderson PF 28 MEM 69 11 1484 6.7 15.1 ... \n",
"25 20 Deni Avdija SF 21 WAS 82 8 1984 6.2 14.4 ... \n",
"35 27 Mo Bamba C 23 ORL 71 69 1824 7.8 16.4 ... \n",
"40 32 Scottie Barnes PF 20 TOR 74 74 2617 8.8 17.8 ... \n",
"45 37 Keita Bates-Diop SF 26 SAS 59 14 956 6.8 13.2 ... \n",
"48 40 Darius Bazley PF 21 OKC 69 53 1924 6.9 16.4 ... \n",
"64 51 Nemanja Bjelica C 33 GSW 71 0 1142 6.8 14.6 ... \n",
"82 68 Oshae Brissett SF 23 IND 67 25 1564 6.5 15.8 ... \n",
"211 160 CJ Elleby SF 21 POR 58 28 1174 5.0 12.8 ... \n",
"259 188 Rudy Gay PF 35 UTA 55 1 1038 7.5 18.0 ... \n",
"282 210 Blake Griffin PF 32 BRK 56 24 958 6.7 15.8 ... \n",
"345 250 Al Horford C 35 BOS 69 69 2005 6.6 14.1 ... \n",
"374 271 Josh Jackson SF 24 TOT 51 3 830 7.0 17.6 ... \n",
"433 309 Maxi Kleber PF 30 DAL 59 21 1450 4.9 12.3 ... \n",
"469 333 Nassir Little SF 21 POR 42 23 1088 6.5 14.1 ... \n",
"524 376 Chimezie Metu C 24 SAC 60 20 1279 7.6 16.9 ... \n",
"616 448 Aleksej Pokusevski PF 20 OKC 61 12 1233 7.3 18.0 ... \n",
"622 454 Bobby Portis C 26 MIL 72 59 2028 9.9 20.6 ... \n",
"659 479 Jeremiah Robinson-Earl C 21 OKC 49 36 1087 6.0 14.5 ... \n",
"\n",
" AST STL BLK TOV PF PTS Unnamed: 29 ORtg DRtg Clusters \n",
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"35 2.3 1.0 3.1 2.0 4.8 20.0 NaN 113.0 108 16 \n",
"40 4.9 1.5 1.1 2.6 3.7 21.7 NaN 116.0 111 16 \n",
"45 2.1 1.4 0.7 2.3 3.1 16.8 NaN 111.0 112 16 \n",
"48 2.5 1.5 1.8 2.3 1.7 18.9 NaN 101.0 111 16 \n",
"64 6.8 1.8 1.1 3.7 5.5 18.5 NaN 111.0 105 16 \n",
"82 2.3 1.4 0.9 1.7 3.6 19.2 NaN 112.0 116 16 \n",
"211 3.6 1.5 0.8 2.3 4.8 14.1 NaN 102.0 117 16 \n",
"259 2.7 1.2 0.9 2.2 4.5 21.2 NaN 110.0 110 16 \n",
"282 5.3 1.4 0.7 1.6 4.8 18.2 NaN 115.0 113 16 \n",
"345 5.7 1.2 2.3 1.6 3.2 17.4 NaN 124.0 104 16 \n",
"374 3.2 1.5 1.3 2.8 5.2 19.2 NaN 95.0 114 16 \n",
"433 2.4 1.0 2.0 1.6 4.8 14.3 NaN 109.0 107 16 \n",
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"524 2.3 1.9 1.2 2.3 3.5 20.1 NaN 104.0 111 16 \n",
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" <th>0</th>\n",
" <td>1</td>\n",
" <td>Precious Achiuwa</td>\n",
" <td>C</td>\n",
" <td>22</td>\n",
" <td>TOR</td>\n",
" <td>73</td>\n",
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" <td>69</td>\n",
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" <td>110.0</td>\n",
" <td>106</td>\n",
" <td>16</td>\n",
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" <th>25</th>\n",
" <td>20</td>\n",
" <td>Deni Avdija</td>\n",
" <td>SF</td>\n",
" <td>21</td>\n",
" <td>WAS</td>\n",
" <td>82</td>\n",
" <td>8</td>\n",
" <td>1984</td>\n",
" <td>6.2</td>\n",
" <td>14.4</td>\n",
" <td>...</td>\n",
" <td>4.2</td>\n",
" <td>1.5</td>\n",
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" <td>4.7</td>\n",
" <td>17.1</td>\n",
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" <td>106.0</td>\n",
" <td>113</td>\n",
" <td>16</td>\n",
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" <th>35</th>\n",
" <td>27</td>\n",
" <td>Mo Bamba</td>\n",
" <td>C</td>\n",
" <td>23</td>\n",
" <td>ORL</td>\n",
" <td>71</td>\n",
" <td>69</td>\n",
" <td>1824</td>\n",
" <td>7.8</td>\n",
" <td>16.4</td>\n",
" <td>...</td>\n",
" <td>2.3</td>\n",
" <td>1.0</td>\n",
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" <td>4.8</td>\n",
" <td>20.0</td>\n",
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" <td>113.0</td>\n",
" <td>108</td>\n",
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" <td>32</td>\n",
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" <td>20</td>\n",
" <td>TOR</td>\n",
" <td>74</td>\n",
" <td>74</td>\n",
" <td>2617</td>\n",
" <td>8.8</td>\n",
" <td>17.8</td>\n",
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" <td>4.9</td>\n",
" <td>1.5</td>\n",
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" <td>2.6</td>\n",
" <td>3.7</td>\n",
" <td>21.7</td>\n",
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" <td>116.0</td>\n",
" <td>111</td>\n",
" <td>16</td>\n",
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" <th>45</th>\n",
" <td>37</td>\n",
" <td>Keita Bates-Diop</td>\n",
" <td>SF</td>\n",
" <td>26</td>\n",
" <td>SAS</td>\n",
" <td>59</td>\n",
" <td>14</td>\n",
" <td>956</td>\n",
" <td>6.8</td>\n",
" <td>13.2</td>\n",
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" <td>1.4</td>\n",
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" <td>111.0</td>\n",
" <td>112</td>\n",
" <td>16</td>\n",
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" <th>48</th>\n",
" <td>40</td>\n",
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" <td>21</td>\n",
" <td>OKC</td>\n",
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" <th>64</th>\n",
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" <td>C</td>\n",
" <td>33</td>\n",
" <td>GSW</td>\n",
" <td>71</td>\n",
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" <th>82</th>\n",
" <td>68</td>\n",
" <td>Oshae Brissett</td>\n",
" <td>SF</td>\n",
" <td>23</td>\n",
" <td>IND</td>\n",
" <td>67</td>\n",
" <td>25</td>\n",
" <td>1564</td>\n",
" <td>6.5</td>\n",
" <td>15.8</td>\n",
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" <td>2.3</td>\n",
" <td>1.4</td>\n",
" <td>0.9</td>\n",
" <td>1.7</td>\n",
" <td>3.6</td>\n",
" <td>19.2</td>\n",
" <td>NaN</td>\n",
" <td>112.0</td>\n",
" <td>116</td>\n",
" <td>16</td>\n",
" </tr>\n",
" <tr>\n",
" <th>211</th>\n",
" <td>160</td>\n",
" <td>CJ Elleby</td>\n",
" <td>SF</td>\n",
" <td>21</td>\n",
" <td>POR</td>\n",
" <td>58</td>\n",
" <td>28</td>\n",
" <td>1174</td>\n",
" <td>5.0</td>\n",
" <td>12.8</td>\n",
" <td>...</td>\n",
" <td>3.6</td>\n",
" <td>1.5</td>\n",
" <td>0.8</td>\n",
" <td>2.3</td>\n",
" <td>4.8</td>\n",
" <td>14.1</td>\n",
" <td>NaN</td>\n",
" <td>102.0</td>\n",
" <td>117</td>\n",
" <td>16</td>\n",
" </tr>\n",
" <tr>\n",
" <th>259</th>\n",
" <td>188</td>\n",
" <td>Rudy Gay</td>\n",
" <td>PF</td>\n",
" <td>35</td>\n",
" <td>UTA</td>\n",
" <td>55</td>\n",
" <td>1</td>\n",
" <td>1038</td>\n",
" <td>7.5</td>\n",
" <td>18.0</td>\n",
" <td>...</td>\n",
" <td>2.7</td>\n",
" <td>1.2</td>\n",
" <td>0.9</td>\n",
" <td>2.2</td>\n",
" <td>4.5</td>\n",
" <td>21.2</td>\n",
" <td>NaN</td>\n",
" <td>110.0</td>\n",
" <td>110</td>\n",
" <td>16</td>\n",
" </tr>\n",
" <tr>\n",
" <th>282</th>\n",
" <td>210</td>\n",
" <td>Blake Griffin</td>\n",
" <td>PF</td>\n",
" <td>32</td>\n",
" <td>BRK</td>\n",
" <td>56</td>\n",
" <td>24</td>\n",
" <td>958</td>\n",
" <td>6.7</td>\n",
" <td>15.8</td>\n",
" <td>...</td>\n",
" <td>5.3</td>\n",
" <td>1.4</td>\n",
" <td>0.7</td>\n",
" <td>1.6</td>\n",
" <td>4.8</td>\n",
" <td>18.2</td>\n",
" <td>NaN</td>\n",
" <td>115.0</td>\n",
" <td>113</td>\n",
" <td>16</td>\n",
" </tr>\n",
" <tr>\n",
" <th>345</th>\n",
" <td>250</td>\n",
" <td>Al Horford</td>\n",
" <td>C</td>\n",
" <td>35</td>\n",
" <td>BOS</td>\n",
" <td>69</td>\n",
" <td>69</td>\n",
" <td>2005</td>\n",
" <td>6.6</td>\n",
" <td>14.1</td>\n",
" <td>...</td>\n",
" <td>5.7</td>\n",
" <td>1.2</td>\n",
" <td>2.3</td>\n",
" <td>1.6</td>\n",
" <td>3.2</td>\n",
" <td>17.4</td>\n",
" <td>NaN</td>\n",
" <td>124.0</td>\n",
" <td>104</td>\n",
" <td>16</td>\n",
" </tr>\n",
" <tr>\n",
" <th>374</th>\n",
" <td>271</td>\n",
" <td>Josh Jackson</td>\n",
" <td>SF</td>\n",
" <td>24</td>\n",
" <td>TOT</td>\n",
" <td>51</td>\n",
" <td>3</td>\n",
" <td>830</td>\n",
" <td>7.0</td>\n",
" <td>17.6</td>\n",
" <td>...</td>\n",
" <td>3.2</td>\n",
" <td>1.5</td>\n",
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" <td>5.2</td>\n",
" <td>19.2</td>\n",
" <td>NaN</td>\n",
" <td>95.0</td>\n",
" <td>114</td>\n",
" <td>16</td>\n",
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" <tr>\n",
" <th>433</th>\n",
" <td>309</td>\n",
" <td>Maxi Kleber</td>\n",
" <td>PF</td>\n",
" <td>30</td>\n",
" <td>DAL</td>\n",
" <td>59</td>\n",
" <td>21</td>\n",
" <td>1450</td>\n",
" <td>4.9</td>\n",
" <td>12.3</td>\n",
" <td>...</td>\n",
" <td>2.4</td>\n",
" <td>1.0</td>\n",
" <td>2.0</td>\n",
" <td>1.6</td>\n",
" <td>4.8</td>\n",
" <td>14.3</td>\n",
" <td>NaN</td>\n",
" <td>109.0</td>\n",
" <td>107</td>\n",
" <td>16</td>\n",
" </tr>\n",
" <tr>\n",
" <th>469</th>\n",
" <td>333</td>\n",
" <td>Nassir Little</td>\n",
" <td>SF</td>\n",
" <td>21</td>\n",
" <td>POR</td>\n",
" <td>42</td>\n",
" <td>23</td>\n",
" <td>1088</td>\n",
" <td>6.5</td>\n",
" <td>14.1</td>\n",
" <td>...</td>\n",
" <td>2.4</td>\n",
" <td>1.1</td>\n",
" <td>1.6</td>\n",
" <td>1.8</td>\n",
" <td>3.7</td>\n",
" <td>18.4</td>\n",
" <td>NaN</td>\n",
" <td>115.0</td>\n",
" <td>116</td>\n",
" <td>16</td>\n",
" </tr>\n",
" <tr>\n",
" <th>524</th>\n",
" <td>376</td>\n",
" <td>Chimezie Metu</td>\n",
" <td>C</td>\n",
" <td>24</td>\n",
" <td>SAC</td>\n",
" <td>60</td>\n",
" <td>20</td>\n",
" <td>1279</td>\n",
" <td>7.6</td>\n",
" <td>16.9</td>\n",
" <td>...</td>\n",
" <td>2.3</td>\n",
" <td>1.9</td>\n",
" <td>1.2</td>\n",
" <td>2.3</td>\n",
" <td>3.5</td>\n",
" <td>20.1</td>\n",
" <td>NaN</td>\n",
" <td>104.0</td>\n",
" <td>111</td>\n",
" <td>16</td>\n",
" </tr>\n",
" <tr>\n",
" <th>616</th>\n",
" <td>448</td>\n",
" <td>Aleksej Pokusevski</td>\n",
" <td>PF</td>\n",
" <td>20</td>\n",
" <td>OKC</td>\n",
" <td>61</td>\n",
" <td>12</td>\n",
" <td>1233</td>\n",
" <td>7.3</td>\n",
" <td>18.0</td>\n",
" <td>...</td>\n",
" <td>5.2</td>\n",
" <td>1.5</td>\n",
" <td>1.5</td>\n",
" <td>3.7</td>\n",
" <td>3.5</td>\n",
" <td>18.3</td>\n",
" <td>NaN</td>\n",
" <td>96.0</td>\n",
" <td>111</td>\n",
" <td>16</td>\n",
" </tr>\n",
" <tr>\n",
" <th>622</th>\n",
" <td>454</td>\n",
" <td>Bobby Portis</td>\n",
" <td>C</td>\n",
" <td>26</td>\n",
" <td>MIL</td>\n",
" <td>72</td>\n",
" <td>59</td>\n",
" <td>2028</td>\n",
" <td>9.9</td>\n",
" <td>20.6</td>\n",
" <td>...</td>\n",
" <td>2.0</td>\n",
" <td>1.3</td>\n",
" <td>1.2</td>\n",
" <td>2.1</td>\n",
" <td>4.1</td>\n",
" <td>24.9</td>\n",
" <td>NaN</td>\n",
" <td>115.0</td>\n",
" <td>110</td>\n",
" <td>16</td>\n",
" </tr>\n",
" <tr>\n",
" <th>659</th>\n",
" <td>479</td>\n",
" <td>Jeremiah Robinson-Earl</td>\n",
" <td>C</td>\n",
" <td>21</td>\n",
" <td>OKC</td>\n",
" <td>49</td>\n",
" <td>36</td>\n",
" <td>1087</td>\n",
" <td>6.0</td>\n",
" <td>14.5</td>\n",
" <td>...</td>\n",
" <td>2.2</td>\n",
" <td>1.3</td>\n",
" <td>0.7</td>\n",
" <td>1.7</td>\n",
" <td>3.4</td>\n",
" <td>16.4</td>\n",
" <td>NaN</td>\n",
" <td>108.0</td>\n",
" <td>113</td>\n",
" <td>16</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
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" Age G GS MP FG FGA \\\n",
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"25% 109.500000 16.0 \n",
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" <td>6.96000</td>\n",
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" <td>2.130000</td>\n",
" <td>6.575000</td>\n",
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" <td>2.260000</td>\n",
" <td>4.025000</td>\n",
" <td>18.535000</td>\n",
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" <td>108.90000</td>\n",
" <td>110.900000</td>\n",
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" <td>474.96842</td>\n",
" <td>1.13388</td>\n",
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" <td>0.34504</td>\n",
" <td>0.603738</td>\n",
" <td>0.599473</td>\n",
" <td>0.898464</td>\n",
" <td>2.464543</td>\n",
" <td>NaN</td>\n",
" <td>7.05542</td>\n",
" <td>3.596782</td>\n",
" <td>0.0</td>\n",
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" <td>4.90000</td>\n",
" <td>12.3000</td>\n",
" <td>0.393000</td>\n",
" <td>0.900000</td>\n",
" <td>2.800000</td>\n",
" <td>0.254000</td>\n",
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" <td>0.700000</td>\n",
" <td>1.600000</td>\n",
" <td>1.700000</td>\n",
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" <td>1087.75000</td>\n",
" <td>6.50000</td>\n",
" <td>14.3250</td>\n",
" <td>0.413250</td>\n",
" <td>1.825000</td>\n",
" <td>6.100000</td>\n",
" <td>0.300000</td>\n",
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" <td>2.300000</td>\n",
" <td>1.20000</td>\n",
" <td>0.900000</td>\n",
" <td>1.775000</td>\n",
" <td>3.500000</td>\n",
" <td>17.025000</td>\n",
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" <td>104.75000</td>\n",
" <td>109.500000</td>\n",
" <td>16.0</td>\n",
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" <th>50%</th>\n",
" <td>23.500000</td>\n",
" <td>64.000000</td>\n",
" <td>23.500000</td>\n",
" <td>1364.50000</td>\n",
" <td>6.80000</td>\n",
" <td>15.8000</td>\n",
" <td>0.435500</td>\n",
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" <td>110.00000</td>\n",
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" <td>1849.00000</td>\n",
" <td>7.52500</td>\n",
" <td>17.5250</td>\n",
" <td>0.467250</td>\n",
" <td>2.600000</td>\n",
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" <td>113.50000</td>\n",
" <td>113.000000</td>\n",
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" <td>9.90000</td>\n",
" <td>20.6000</td>\n",
" <td>0.517000</td>\n",
" <td>3.300000</td>\n",
" <td>9.700000</td>\n",
" <td>0.393000</td>\n",
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" <td>6.800000</td>\n",
" <td>2.50000</td>\n",
" <td>3.100000</td>\n",
" <td>3.700000</td>\n",
" <td>5.500000</td>\n",
" <td>24.900000</td>\n",
" <td>NaN</td>\n",
" <td>124.00000</td>\n",
" <td>117.000000</td>\n",
" <td>16.0</td>\n",
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" Rk Player Pos Age Tm G GS MP FG FGA ... AST \\\n",
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" if (!dataTable) return;\n",
"\n",
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" Age G GS MP FG FGA FG% \\\n",
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" <td>4.725000</td>\n",
" <td>2.800000</td>\n",
" <td>2.350000</td>\n",
" <td>4.025000</td>\n",
" <td>6.625000</td>\n",
" <td>17.350000</td>\n",
" <td>NaN</td>\n",
" <td>111.000000</td>\n",
" <td>100.500000</td>\n",
" <td>17.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>50%</th>\n",
" <td>28.0</td>\n",
" <td>61.000000</td>\n",
" <td>24.000000</td>\n",
" <td>1169.500000</td>\n",
" <td>7.800000</td>\n",
" <td>14.050000</td>\n",
" <td>0.554000</td>\n",
" <td>0.0</td>\n",
" <td>0.1</td>\n",
" <td>0.0</td>\n",
" <td>...</td>\n",
" <td>4.950000</td>\n",
" <td>2.900000</td>\n",
" <td>2.400000</td>\n",
" <td>4.150000</td>\n",
" <td>6.650000</td>\n",
" <td>18.200000</td>\n",
" <td>NaN</td>\n",
" <td>112.000000</td>\n",
" <td>101.000000</td>\n",
" <td>17.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>75%</th>\n",
" <td>28.0</td>\n",
" <td>67.000000</td>\n",
" <td>30.000000</td>\n",
" <td>1303.250000</td>\n",
" <td>8.150000</td>\n",
" <td>14.475000</td>\n",
" <td>0.562000</td>\n",
" <td>0.0</td>\n",
" <td>0.1</td>\n",
" <td>0.0</td>\n",
" <td>...</td>\n",
" <td>5.175000</td>\n",
" <td>3.000000</td>\n",
" <td>2.450000</td>\n",
" <td>4.275000</td>\n",
" <td>6.675000</td>\n",
" <td>19.050000</td>\n",
" <td>NaN</td>\n",
" <td>113.000000</td>\n",
" <td>101.500000</td>\n",
" <td>17.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>max</th>\n",
" <td>28.0</td>\n",
" <td>73.000000</td>\n",
" <td>36.000000</td>\n",
" <td>1437.000000</td>\n",
" <td>8.500000</td>\n",
" <td>14.900000</td>\n",
" <td>0.570000</td>\n",
" <td>0.0</td>\n",
" <td>0.1</td>\n",
" <td>0.0</td>\n",
" <td>...</td>\n",
" <td>5.400000</td>\n",
" <td>3.100000</td>\n",
" <td>2.500000</td>\n",
" <td>4.400000</td>\n",
" <td>6.700000</td>\n",
" <td>19.900000</td>\n",
" <td>NaN</td>\n",
" <td>114.000000</td>\n",
" <td>102.000000</td>\n",
" <td>17.0</td>\n",
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"text/plain": [
" Rk Player Pos Age Tm G GS MP FG FGA ... \\\n",
"262 191 Josh Giddey SG 19 OKC 54 54 1700 8.1 19.2 ... \n",
"276 204 Draymond Green PF 31 GSW 46 44 1329 5.0 9.4 ... \n",
"286 214 Tyrese Haliburton SG-PG 21 TOT 77 77 2695 7.7 16.3 ... \n",
"287 214 Tyrese Haliburton SG 21 SAC 51 51 1757 7.3 16.0 ... \n",
"288 214 Tyrese Haliburton PG 21 IND 26 26 938 8.5 16.9 ... \n",
"336 245 Jrue Holiday PG 31 MIL 67 64 2207 10.4 20.8 ... \n",
"559 400 Dejounte Murray PG 25 SAS 68 68 2366 11.6 25.2 ... \n",
"603 438 Chris Paul PG 36 PHO 65 65 2139 8.2 16.6 ... \n",
"706 511 Ish Smith PG 33 TOT 65 1 1126 8.0 18.6 ... \n",
"\n",
" AST STL BLK TOV PF PTS Unnamed: 29 ORtg DRtg Clusters \n",
"262 9.9 1.5 0.6 4.9 2.5 19.3 NaN 97.0 112 18 \n",
"276 11.7 2.2 1.8 5.1 5.0 12.7 NaN 109.0 103 18 \n",
"286 11.3 2.4 0.9 3.6 2.2 21.2 NaN 119.0 115 18 \n",
"287 10.4 2.4 0.9 3.1 1.9 19.9 NaN 117.0 115 18 \n",
"288 13.0 2.5 0.8 4.4 2.6 23.7 NaN 123.0 115 18 \n",
"336 9.9 2.4 0.6 4.0 2.9 26.7 NaN 117.0 112 18 \n",
"559 12.7 2.8 0.5 3.7 2.8 29.2 NaN 113.0 108 18 \n",
"603 15.8 2.7 0.4 3.4 3.0 21.6 NaN 124.0 107 18 \n",
"706 10.6 2.0 1.0 3.4 3.4 17.8 NaN 101.0 114 18 \n",
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" <th></th>\n",
" <th>Rk</th>\n",
" <th>Player</th>\n",
" <th>Pos</th>\n",
" <th>Age</th>\n",
" <th>Tm</th>\n",
" <th>G</th>\n",
" <th>GS</th>\n",
" <th>MP</th>\n",
" <th>FG</th>\n",
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" <th>...</th>\n",
" <th>AST</th>\n",
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" <th>262</th>\n",
" <td>191</td>\n",
" <td>Josh Giddey</td>\n",
" <td>SG</td>\n",
" <td>19</td>\n",
" <td>OKC</td>\n",
" <td>54</td>\n",
" <td>54</td>\n",
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" <td>8.1</td>\n",
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" <td>109.0</td>\n",
" <td>103</td>\n",
" <td>18</td>\n",
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" <td>214</td>\n",
" <td>Tyrese Haliburton</td>\n",
" <td>SG-PG</td>\n",
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" <td>7.7</td>\n",
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" <td>214</td>\n",
" <td>Tyrese Haliburton</td>\n",
" <td>SG</td>\n",
" <td>21</td>\n",
" <td>SAC</td>\n",
" <td>51</td>\n",
" <td>51</td>\n",
" <td>1757</td>\n",
" <td>7.3</td>\n",
" <td>16.0</td>\n",
" <td>...</td>\n",
" <td>10.4</td>\n",
" <td>2.4</td>\n",
" <td>0.9</td>\n",
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" <td>1.9</td>\n",
" <td>19.9</td>\n",
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" <td>117.0</td>\n",
" <td>115</td>\n",
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" <th>288</th>\n",
" <td>214</td>\n",
" <td>Tyrese Haliburton</td>\n",
" <td>PG</td>\n",
" <td>21</td>\n",
" <td>IND</td>\n",
" <td>26</td>\n",
" <td>26</td>\n",
" <td>938</td>\n",
" <td>8.5</td>\n",
" <td>16.9</td>\n",
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" <td>13.0</td>\n",
" <td>2.5</td>\n",
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" <td>2.6</td>\n",
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" <td>NaN</td>\n",
" <td>123.0</td>\n",
" <td>115</td>\n",
" <td>18</td>\n",
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" <tr>\n",
" <th>336</th>\n",
" <td>245</td>\n",
" <td>Jrue Holiday</td>\n",
" <td>PG</td>\n",
" <td>31</td>\n",
" <td>MIL</td>\n",
" <td>67</td>\n",
" <td>64</td>\n",
" <td>2207</td>\n",
" <td>10.4</td>\n",
" <td>20.8</td>\n",
" <td>...</td>\n",
" <td>9.9</td>\n",
" <td>2.4</td>\n",
" <td>0.6</td>\n",
" <td>4.0</td>\n",
" <td>2.9</td>\n",
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" <td>NaN</td>\n",
" <td>117.0</td>\n",
" <td>112</td>\n",
" <td>18</td>\n",
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" <th>559</th>\n",
" <td>400</td>\n",
" <td>Dejounte Murray</td>\n",
" <td>PG</td>\n",
" <td>25</td>\n",
" <td>SAS</td>\n",
" <td>68</td>\n",
" <td>68</td>\n",
" <td>2366</td>\n",
" <td>11.6</td>\n",
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" <td>2.8</td>\n",
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" <td>113.0</td>\n",
" <td>108</td>\n",
" <td>18</td>\n",
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" <th>603</th>\n",
" <td>438</td>\n",
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" <td>PG</td>\n",
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" <td>PHO</td>\n",
" <td>65</td>\n",
" <td>65</td>\n",
" <td>2139</td>\n",
" <td>8.2</td>\n",
" <td>16.6</td>\n",
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" <td>15.8</td>\n",
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" <td>NaN</td>\n",
" <td>124.0</td>\n",
" <td>107</td>\n",
" <td>18</td>\n",
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" <tr>\n",
" <th>706</th>\n",
" <td>511</td>\n",
" <td>Ish Smith</td>\n",
" <td>PG</td>\n",
" <td>33</td>\n",
" <td>TOT</td>\n",
" <td>65</td>\n",
" <td>1</td>\n",
" <td>1126</
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