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conanak99/harry.ipynb

Created January 22, 2019 11:09
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harry.ipynb
{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Harry Pandas Testing"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Import Library "
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [],
"source": [
"import pandas as pd\n",
"import numpy as np"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Random Series"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"0 -1.062298\n",
"1 2.479025\n",
"2 0.219077\n",
"3 0.163897\n",
"4 -1.329021\n",
"5 1.417700\n",
"6 0.429277\n",
"7 -1.132451\n",
"8 -2.302549\n",
"9 -0.503536\n",
"10 0.732323\n",
"11 0.127685\n",
"12 0.887372\n",
"13 -0.736562\n",
"14 -0.155842\n",
"15 0.120562\n",
"16 1.216447\n",
"17 -0.180917\n",
"18 0.666015\n",
"19 0.886909\n",
"20 1.098315\n",
"21 0.543258\n",
"22 0.266776\n",
"23 1.372116\n",
"24 -0.532650\n",
"25 1.034518\n",
"26 1.927744\n",
"27 -0.488514\n",
"28 0.395017\n",
"29 -0.074944\n",
"30 -2.591367\n",
"31 0.155569\n",
"32 -0.778885\n",
"33 -0.159217\n",
"34 -0.595685\n",
"35 0.204930\n",
"36 0.149245\n",
"37 -0.185524\n",
"38 -0.509900\n",
"39 -0.363044\n",
"40 -0.162456\n",
"41 -0.926784\n",
"42 0.883768\n",
"43 -0.583372\n",
"44 0.240259\n",
"45 0.229812\n",
"46 0.843649\n",
"47 0.174074\n",
"48 -0.238292\n",
"49 1.609257\n",
"dtype: float64"
]
},
"execution_count": 9,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"s = pd.Series(np.random.randn(50))\n",
"s"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Random Frame"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<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>A</th>\n",
" <th>B</th>\n",
" <th>C</th>\n",
" <th>D</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>0.473966</td>\n",
" <td>0.381508</td>\n",
" <td>0.573259</td>\n",
" <td>0.257870</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>-0.865101</td>\n",
" <td>-0.294504</td>\n",
" <td>0.740886</td>\n",
" <td>-0.157397</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>-0.227568</td>\n",
" <td>0.040860</td>\n",
" <td>-0.751676</td>\n",
" <td>-0.202259</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>-1.410605</td>\n",
" <td>1.079928</td>\n",
" <td>0.004035</td>\n",
" <td>0.772191</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>0.936140</td>\n",
" <td>-0.714205</td>\n",
" <td>0.608352</td>\n",
" <td>-1.660922</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5</th>\n",
" <td>1.123943</td>\n",
" <td>0.676052</td>\n",
" <td>0.871001</td>\n",
" <td>0.755819</td>\n",
" </tr>\n",
" <tr>\n",
" <th>6</th>\n",
" <td>1.163294</td>\n",
" <td>-0.399610</td>\n",
" <td>2.018614</td>\n",
" <td>-0.863637</td>\n",
" </tr>\n",
" <tr>\n",
" <th>7</th>\n",
" <td>2.426598</td>\n",
" <td>0.366610</td>\n",
" <td>-1.634347</td>\n",
" <td>1.828948</td>\n",
" </tr>\n",
" <tr>\n",
" <th>8</th>\n",
" <td>0.664075</td>\n",
" <td>1.194904</td>\n",
" <td>0.859844</td>\n",
" <td>-1.573903</td>\n",
" </tr>\n",
" <tr>\n",
" <th>9</th>\n",
" <td>2.086721</td>\n",
" <td>0.117757</td>\n",
" <td>1.113913</td>\n",
" <td>-0.553091</td>\n",
" </tr>\n",
" <tr>\n",
" <th>10</th>\n",
" <td>0.689572</td>\n",
" <td>1.817442</td>\n",
" <td>-0.953554</td>\n",
" <td>-0.827302</td>\n",
" </tr>\n",
" <tr>\n",
" <th>11</th>\n",
" <td>0.778648</td>\n",
" <td>-0.190663</td>\n",
" <td>-0.897111</td>\n",
" <td>-0.675870</td>\n",
" </tr>\n",
" <tr>\n",
" <th>12</th>\n",
" <td>0.703365</td>\n",
" <td>1.124447</td>\n",
" <td>-0.849986</td>\n",
" <td>1.382501</td>\n",
" </tr>\n",
" <tr>\n",
" <th>13</th>\n",
" <td>-0.026022</td>\n",
" <td>-0.946897</td>\n",
" <td>0.058932</td>\n",
" <td>-0.207543</td>\n",
" </tr>\n",
" <tr>\n",
" <th>14</th>\n",
" <td>1.556308</td>\n",
" <td>1.054974</td>\n",
" <td>0.145805</td>\n",
" <td>-0.871226</td>\n",
" </tr>\n",
" <tr>\n",
" <th>15</th>\n",
" <td>-0.684150</td>\n",
" <td>1.231485</td>\n",
" <td>-0.981294</td>\n",
" <td>-1.742971</td>\n",
" </tr>\n",
" <tr>\n",
" <th>16</th>\n",
" <td>0.801028</td>\n",
" <td>0.366246</td>\n",
" <td>-0.473794</td>\n",
" <td>0.073391</td>\n",
" </tr>\n",
" <tr>\n",
" <th>17</th>\n",
" <td>-0.135861</td>\n",
" <td>1.923322</td>\n",
" <td>0.560173</td>\n",
" <td>0.042548</td>\n",
" </tr>\n",
" <tr>\n",
" <th>18</th>\n",
" <td>-0.354168</td>\n",
" <td>-0.535552</td>\n",
" <td>-0.331556</td>\n",
" <td>1.054646</td>\n",
" </tr>\n",
" <tr>\n",
" <th>19</th>\n",
" <td>-0.632291</td>\n",
" <td>-0.188284</td>\n",
" <td>0.932492</td>\n",
" <td>-0.542673</td>\n",
" </tr>\n",
" <tr>\n",
" <th>20</th>\n",
" <td>1.708389</td>\n",
" <td>-1.101101</td>\n",
" <td>1.035156</td>\n",
" <td>-2.395025</td>\n",
" </tr>\n",
" <tr>\n",
" <th>21</th>\n",
" <td>0.554584</td>\n",
" <td>1.016959</td>\n",
" <td>-1.614568</td>\n",
" <td>0.508982</td>\n",
" </tr>\n",
" <tr>\n",
" <th>22</th>\n",
" <td>-1.173039</td>\n",
" <td>1.553102</td>\n",
" <td>-0.662802</td>\n",
" <td>0.225355</td>\n",
" </tr>\n",
" <tr>\n",
" <th>23</th>\n",
" <td>-0.403863</td>\n",
" <td>-1.063498</td>\n",
" <td>-1.298217</td>\n",
" <td>-0.025722</td>\n",
" </tr>\n",
" <tr>\n",
" <th>24</th>\n",
" <td>-1.840328</td>\n",
" <td>-1.071873</td>\n",
" <td>1.368573</td>\n",
" <td>-1.089553</td>\n",
" </tr>\n",
" <tr>\n",
" <th>25</th>\n",
" <td>0.926127</td>\n",
" <td>-1.487209</td>\n",
" <td>-0.291226</td>\n",
" <td>-2.380213</td>\n",
" </tr>\n",
" <tr>\n",
" <th>26</th>\n",
" <td>0.040705</td>\n",
" <td>0.120548</td>\n",
" <td>-0.273665</td>\n",
" <td>-0.461162</td>\n",
" </tr>\n",
" <tr>\n",
" <th>27</th>\n",
" <td>1.781844</td>\n",
" <td>-3.041243</td>\n",
" <td>0.680399</td>\n",
" <td>-0.216563</td>\n",
" </tr>\n",
" <tr>\n",
" <th>28</th>\n",
" <td>-0.007001</td>\n",
" <td>1.060720</td>\n",
" <td>1.427962</td>\n",
" <td>0.867160</td>\n",
" </tr>\n",
" <tr>\n",
" <th>29</th>\n",
" <td>0.624166</td>\n",
" <td>-0.006437</td>\n",
" <td>0.601387</td>\n",
" <td>-0.376425</td>\n",
" </tr>\n",
" <tr>\n",
" <th>30</th>\n",
" <td>0.792650</td>\n",
" <td>0.904800</td>\n",
" <td>1.392125</td>\n",
" <td>-0.297326</td>\n",
" </tr>\n",
" <tr>\n",
" <th>31</th>\n",
" <td>-2.032892</td>\n",
" <td>-0.359078</td>\n",
" <td>0.549779</td>\n",
" <td>0.302271</td>\n",
" </tr>\n",
" <tr>\n",
" <th>32</th>\n",
" <td>-0.970749</td>\n",
" <td>-2.524223</td>\n",
" <td>1.368305</td>\n",
" <td>0.878750</td>\n",
" </tr>\n",
" <tr>\n",
" <th>33</th>\n",
" <td>-0.908990</td>\n",
" <td>1.226420</td>\n",
" <td>-0.420891</td>\n",
" <td>-0.814441</td>\n",
" </tr>\n",
" <tr>\n",
" <th>34</th>\n",
" <td>0.267988</td>\n",
" <td>-2.409989</td>\n",
" <td>1.887542</td>\n",
" <td>-0.250847</td>\n",
" </tr>\n",
" <tr>\n",
" <th>35</th>\n",
" <td>1.180837</td>\n",
" <td>0.529325</td>\n",
" <td>1.209006</td>\n",
" <td>-0.016048</td>\n",
" </tr>\n",
" <tr>\n",
" <th>36</th>\n",
" <td>-0.255369</td>\n",
" <td>-0.357612</td>\n",
" <td>0.488842</td>\n",
" <td>1.064465</td>\n",
" </tr>\n",
" <tr>\n",
" <th>37</th>\n",
" <td>-0.566115</td>\n",
" <td>1.082725</td>\n",
" <td>0.799946</td>\n",
" <td>-0.323027</td>\n",
" </tr>\n",
" <tr>\n",
" <th>38</th>\n",
" <td>1.020873</td>\n",
" <td>-1.113354</td>\n",
" <td>0.262756</td>\n",
" <td>-1.166912</td>\n",
" </tr>\n",
" <tr>\n",
" <th>39</th>\n",
" <td>0.873324</td>\n",
" <td>0.720812</td>\n",
" <td>0.221815</td>\n",
" <td>-1.140340</td>\n",
" </tr>\n",
" <tr>\n",
" <th>40</th>\n",
" <td>-0.728797</td>\n",
" <td>0.906350</td>\n",
" <td>2.060547</td>\n",
" <td>0.899554</td>\n",
" </tr>\n",
" <tr>\n",
" <th>41</th>\n",
" <td>0.189867</td>\n",
" <td>-1.747070</td>\n",
" <td>1.615279</td>\n",
" <td>1.136936</td>\n",
" </tr>\n",
" <tr>\n",
" <th>42</th>\n",
" <td>-0.025881</td>\n",
" <td>0.264950</td>\n",
" <td>-0.548986</td>\n",
" <td>-0.078668</td>\n",
" </tr>\n",
" <tr>\n",
" <th>43</th>\n",
" <td>-0.857711</td>\n",
" <td>2.033325</td>\n",
" <td>0.302750</td>\n",
" <td>-0.279391</td>\n",
" </tr>\n",
" <tr>\n",
" <th>44</th>\n",
" <td>0.937300</td>\n",
" <td>-0.139334</td>\n",
" <td>0.160748</td>\n",
" <td>1.379907</td>\n",
" </tr>\n",
" <tr>\n",
" <th>45</th>\n",
" <td>0.579146</td>\n",
" <td>1.037569</td>\n",
" <td>-1.642841</td>\n",
" <td>-0.013524</td>\n",
" </tr>\n",
" <tr>\n",
" <th>46</th>\n",
" <td>-0.009736</td>\n",
" <td>-0.321982</td>\n",
" <td>-0.689138</td>\n",
" <td>-0.715967</td>\n",
" </tr>\n",
" <tr>\n",
" <th>47</th>\n",
" <td>0.288380</td>\n",
" <td>0.284520</td>\n",
" <td>-0.723584</td>\n",
" <td>1.042251</td>\n",
" </tr>\n",
" <tr>\n",
" <th>48</th>\n",
" <td>0.507354</td>\n",
" <td>-0.238541</td>\n",
" <td>0.459474</td>\n",
" <td>0.225959</td>\n",
" </tr>\n",
" <tr>\n",
" <th>49</th>\n",
" <td>-1.309012</td>\n",
" <td>2.076121</td>\n",
" <td>-0.045753</td>\n",
" <td>-0.892809</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" A B C D\n",
"0 0.473966 0.381508 0.573259 0.257870\n",
"1 -0.865101 -0.294504 0.740886 -0.157397\n",
"2 -0.227568 0.040860 -0.751676 -0.202259\n",
"3 -1.410605 1.079928 0.004035 0.772191\n",
"4 0.936140 -0.714205 0.608352 -1.660922\n",
"5 1.123943 0.676052 0.871001 0.755819\n",
"6 1.163294 -0.399610 2.018614 -0.863637\n",
"7 2.426598 0.366610 -1.634347 1.828948\n",
"8 0.664075 1.194904 0.859844 -1.573903\n",
"9 2.086721 0.117757 1.113913 -0.553091\n",
"10 0.689572 1.817442 -0.953554 -0.827302\n",
"11 0.778648 -0.190663 -0.897111 -0.675870\n",
"12 0.703365 1.124447 -0.849986 1.382501\n",
"13 -0.026022 -0.946897 0.058932 -0.207543\n",
"14 1.556308 1.054974 0.145805 -0.871226\n",
"15 -0.684150 1.231485 -0.981294 -1.742971\n",
"16 0.801028 0.366246 -0.473794 0.073391\n",
"17 -0.135861 1.923322 0.560173 0.042548\n",
"18 -0.354168 -0.535552 -0.331556 1.054646\n",
"19 -0.632291 -0.188284 0.932492 -0.542673\n",
"20 1.708389 -1.101101 1.035156 -2.395025\n",
"21 0.554584 1.016959 -1.614568 0.508982\n",
"22 -1.173039 1.553102 -0.662802 0.225355\n",
"23 -0.403863 -1.063498 -1.298217 -0.025722\n",
"24 -1.840328 -1.071873 1.368573 -1.089553\n",
"25 0.926127 -1.487209 -0.291226 -2.380213\n",
"26 0.040705 0.120548 -0.273665 -0.461162\n",
"27 1.781844 -3.041243 0.680399 -0.216563\n",
"28 -0.007001 1.060720 1.427962 0.867160\n",
"29 0.624166 -0.006437 0.601387 -0.376425\n",
"30 0.792650 0.904800 1.392125 -0.297326\n",
"31 -2.032892 -0.359078 0.549779 0.302271\n",
"32 -0.970749 -2.524223 1.368305 0.878750\n",
"33 -0.908990 1.226420 -0.420891 -0.814441\n",
"34 0.267988 -2.409989 1.887542 -0.250847\n",
"35 1.180837 0.529325 1.209006 -0.016048\n",
"36 -0.255369 -0.357612 0.488842 1.064465\n",
"37 -0.566115 1.082725 0.799946 -0.323027\n",
"38 1.020873 -1.113354 0.262756 -1.166912\n",
"39 0.873324 0.720812 0.221815 -1.140340\n",
"40 -0.728797 0.906350 2.060547 0.899554\n",
"41 0.189867 -1.747070 1.615279 1.136936\n",
"42 -0.025881 0.264950 -0.548986 -0.078668\n",
"43 -0.857711 2.033325 0.302750 -0.279391\n",
"44 0.937300 -0.139334 0.160748 1.379907\n",
"45 0.579146 1.037569 -1.642841 -0.013524\n",
"46 -0.009736 -0.321982 -0.689138 -0.715967\n",
"47 0.288380 0.284520 -0.723584 1.042251\n",
"48 0.507354 -0.238541 0.459474 0.225959\n",
"49 -1.309012 2.076121 -0.045753 -0.892809"
]
},
"execution_count": 8,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df = pd.DataFrame(np.random.randn(50, 4), columns=list('ABCD'))\n",
"df"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.6.4"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
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