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Importing_datasets.ipynb
{
"cells": [
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# import pandas library\n",
"import pandas as pd\n",
"import numpy as np"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [],
"source": [
"# Import pandas library\n",
"import pandas as pd\n",
"\n",
"# Read the online file by the URL provides above, and assign it to variable \"df\"\n",
"other_path = \"https://cf-courses-data.s3.us.cloud-object-storage.appdomain.cloud/IBMDeveloperSkillsNetwork-DA0101EN-SkillsNetwork/labs/Data%20files/auto.csv\"\n",
"df = pd.read_csv(other_path, header=None)"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"The first 5 rows of the dataframe\n"
]
},
{
"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>0</th>\n",
" <th>1</th>\n",
" <th>2</th>\n",
" <th>3</th>\n",
" <th>4</th>\n",
" <th>5</th>\n",
" <th>6</th>\n",
" <th>7</th>\n",
" <th>8</th>\n",
" <th>9</th>\n",
" <th>...</th>\n",
" <th>16</th>\n",
" <th>17</th>\n",
" <th>18</th>\n",
" <th>19</th>\n",
" <th>20</th>\n",
" <th>21</th>\n",
" <th>22</th>\n",
" <th>23</th>\n",
" <th>24</th>\n",
" <th>25</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>3</td>\n",
" <td>?</td>\n",
" <td>alfa-romero</td>\n",
" <td>gas</td>\n",
" <td>std</td>\n",
" <td>two</td>\n",
" <td>convertible</td>\n",
" <td>rwd</td>\n",
" <td>front</td>\n",
" <td>88.6</td>\n",
" <td>...</td>\n",
" <td>130</td>\n",
" <td>mpfi</td>\n",
" <td>3.47</td>\n",
" <td>2.68</td>\n",
" <td>9.0</td>\n",
" <td>111</td>\n",
" <td>5000</td>\n",
" <td>21</td>\n",
" <td>27</td>\n",
" <td>13495</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>3</td>\n",
" <td>?</td>\n",
" <td>alfa-romero</td>\n",
" <td>gas</td>\n",
" <td>std</td>\n",
" <td>two</td>\n",
" <td>convertible</td>\n",
" <td>rwd</td>\n",
" <td>front</td>\n",
" <td>88.6</td>\n",
" <td>...</td>\n",
" <td>130</td>\n",
" <td>mpfi</td>\n",
" <td>3.47</td>\n",
" <td>2.68</td>\n",
" <td>9.0</td>\n",
" <td>111</td>\n",
" <td>5000</td>\n",
" <td>21</td>\n",
" <td>27</td>\n",
" <td>16500</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>1</td>\n",
" <td>?</td>\n",
" <td>alfa-romero</td>\n",
" <td>gas</td>\n",
" <td>std</td>\n",
" <td>two</td>\n",
" <td>hatchback</td>\n",
" <td>rwd</td>\n",
" <td>front</td>\n",
" <td>94.5</td>\n",
" <td>...</td>\n",
" <td>152</td>\n",
" <td>mpfi</td>\n",
" <td>2.68</td>\n",
" <td>3.47</td>\n",
" <td>9.0</td>\n",
" <td>154</td>\n",
" <td>5000</td>\n",
" <td>19</td>\n",
" <td>26</td>\n",
" <td>16500</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>2</td>\n",
" <td>164</td>\n",
" <td>audi</td>\n",
" <td>gas</td>\n",
" <td>std</td>\n",
" <td>four</td>\n",
" <td>sedan</td>\n",
" <td>fwd</td>\n",
" <td>front</td>\n",
" <td>99.8</td>\n",
" <td>...</td>\n",
" <td>109</td>\n",
" <td>mpfi</td>\n",
" <td>3.19</td>\n",
" <td>3.40</td>\n",
" <td>10.0</td>\n",
" <td>102</td>\n",
" <td>5500</td>\n",
" <td>24</td>\n",
" <td>30</td>\n",
" <td>13950</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>2</td>\n",
" <td>164</td>\n",
" <td>audi</td>\n",
" <td>gas</td>\n",
" <td>std</td>\n",
" <td>four</td>\n",
" <td>sedan</td>\n",
" <td>4wd</td>\n",
" <td>front</td>\n",
" <td>99.4</td>\n",
" <td>...</td>\n",
" <td>136</td>\n",
" <td>mpfi</td>\n",
" <td>3.19</td>\n",
" <td>3.40</td>\n",
" <td>8.0</td>\n",
" <td>115</td>\n",
" <td>5500</td>\n",
" <td>18</td>\n",
" <td>22</td>\n",
" <td>17450</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>5 rows × 26 columns</p>\n",
"</div>"
],
"text/plain": [
" 0 1 2 3 4 5 6 7 8 9 ... \\\n",
"0 3 ? alfa-romero gas std two convertible rwd front 88.6 ... \n",
"1 3 ? alfa-romero gas std two convertible rwd front 88.6 ... \n",
"2 1 ? alfa-romero gas std two hatchback rwd front 94.5 ... \n",
"3 2 164 audi gas std four sedan fwd front 99.8 ... \n",
"4 2 164 audi gas std four sedan 4wd front 99.4 ... \n",
"\n",
" 16 17 18 19 20 21 22 23 24 25 \n",
"0 130 mpfi 3.47 2.68 9.0 111 5000 21 27 13495 \n",
"1 130 mpfi 3.47 2.68 9.0 111 5000 21 27 16500 \n",
"2 152 mpfi 2.68 3.47 9.0 154 5000 19 26 16500 \n",
"3 109 mpfi 3.19 3.40 10.0 102 5500 24 30 13950 \n",
"4 136 mpfi 3.19 3.40 8.0 115 5500 18 22 17450 \n",
"\n",
"[5 rows x 26 columns]"
]
},
"execution_count": 11,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# show the first 5 rows using dataframe.head() method\n",
"print(\"The first 5 rows of the dataframe\") \n",
"df.head(5)"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"The Last 10 rows of the dataframe\n"
]
},
{
"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>0</th>\n",
" <th>1</th>\n",
" <th>2</th>\n",
" <th>3</th>\n",
" <th>4</th>\n",
" <th>5</th>\n",
" <th>6</th>\n",
" <th>7</th>\n",
" <th>8</th>\n",
" <th>9</th>\n",
" <th>...</th>\n",
" <th>16</th>\n",
" <th>17</th>\n",
" <th>18</th>\n",
" <th>19</th>\n",
" <th>20</th>\n",
" <th>21</th>\n",
" <th>22</th>\n",
" <th>23</th>\n",
" <th>24</th>\n",
" <th>25</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>195</th>\n",
" <td>-1</td>\n",
" <td>74</td>\n",
" <td>volvo</td>\n",
" <td>gas</td>\n",
" <td>std</td>\n",
" <td>four</td>\n",
" <td>wagon</td>\n",
" <td>rwd</td>\n",
" <td>front</td>\n",
" <td>104.3</td>\n",
" <td>...</td>\n",
" <td>141</td>\n",
" <td>mpfi</td>\n",
" <td>3.78</td>\n",
" <td>3.15</td>\n",
" <td>9.5</td>\n",
" <td>114</td>\n",
" <td>5400</td>\n",
" <td>23</td>\n",
" <td>28</td>\n",
" <td>13415</td>\n",
" </tr>\n",
" <tr>\n",
" <th>196</th>\n",
" <td>-2</td>\n",
" <td>103</td>\n",
" <td>volvo</td>\n",
" <td>gas</td>\n",
" <td>std</td>\n",
" <td>four</td>\n",
" <td>sedan</td>\n",
" <td>rwd</td>\n",
" <td>front</td>\n",
" <td>104.3</td>\n",
" <td>...</td>\n",
" <td>141</td>\n",
" <td>mpfi</td>\n",
" <td>3.78</td>\n",
" <td>3.15</td>\n",
" <td>9.5</td>\n",
" <td>114</td>\n",
" <td>5400</td>\n",
" <td>24</td>\n",
" <td>28</td>\n",
" <td>15985</td>\n",
" </tr>\n",
" <tr>\n",
" <th>197</th>\n",
" <td>-1</td>\n",
" <td>74</td>\n",
" <td>volvo</td>\n",
" <td>gas</td>\n",
" <td>std</td>\n",
" <td>four</td>\n",
" <td>wagon</td>\n",
" <td>rwd</td>\n",
" <td>front</td>\n",
" <td>104.3</td>\n",
" <td>...</td>\n",
" <td>141</td>\n",
" <td>mpfi</td>\n",
" <td>3.78</td>\n",
" <td>3.15</td>\n",
" <td>9.5</td>\n",
" <td>114</td>\n",
" <td>5400</td>\n",
" <td>24</td>\n",
" <td>28</td>\n",
" <td>16515</td>\n",
" </tr>\n",
" <tr>\n",
" <th>198</th>\n",
" <td>-2</td>\n",
" <td>103</td>\n",
" <td>volvo</td>\n",
" <td>gas</td>\n",
" <td>turbo</td>\n",
" <td>four</td>\n",
" <td>sedan</td>\n",
" <td>rwd</td>\n",
" <td>front</td>\n",
" <td>104.3</td>\n",
" <td>...</td>\n",
" <td>130</td>\n",
" <td>mpfi</td>\n",
" <td>3.62</td>\n",
" <td>3.15</td>\n",
" <td>7.5</td>\n",
" <td>162</td>\n",
" <td>5100</td>\n",
" <td>17</td>\n",
" <td>22</td>\n",
" <td>18420</td>\n",
" </tr>\n",
" <tr>\n",
" <th>199</th>\n",
" <td>-1</td>\n",
" <td>74</td>\n",
" <td>volvo</td>\n",
" <td>gas</td>\n",
" <td>turbo</td>\n",
" <td>four</td>\n",
" <td>wagon</td>\n",
" <td>rwd</td>\n",
" <td>front</td>\n",
" <td>104.3</td>\n",
" <td>...</td>\n",
" <td>130</td>\n",
" <td>mpfi</td>\n",
" <td>3.62</td>\n",
" <td>3.15</td>\n",
" <td>7.5</td>\n",
" <td>162</td>\n",
" <td>5100</td>\n",
" <td>17</td>\n",
" <td>22</td>\n",
" <td>18950</td>\n",
" </tr>\n",
" <tr>\n",
" <th>200</th>\n",
" <td>-1</td>\n",
" <td>95</td>\n",
" <td>volvo</td>\n",
" <td>gas</td>\n",
" <td>std</td>\n",
" <td>four</td>\n",
" <td>sedan</td>\n",
" <td>rwd</td>\n",
" <td>front</td>\n",
" <td>109.1</td>\n",
" <td>...</td>\n",
" <td>141</td>\n",
" <td>mpfi</td>\n",
" <td>3.78</td>\n",
" <td>3.15</td>\n",
" <td>9.5</td>\n",
" <td>114</td>\n",
" <td>5400</td>\n",
" <td>23</td>\n",
" <td>28</td>\n",
" <td>16845</td>\n",
" </tr>\n",
" <tr>\n",
" <th>201</th>\n",
" <td>-1</td>\n",
" <td>95</td>\n",
" <td>volvo</td>\n",
" <td>gas</td>\n",
" <td>turbo</td>\n",
" <td>four</td>\n",
" <td>sedan</td>\n",
" <td>rwd</td>\n",
" <td>front</td>\n",
" <td>109.1</td>\n",
" <td>...</td>\n",
" <td>141</td>\n",
" <td>mpfi</td>\n",
" <td>3.78</td>\n",
" <td>3.15</td>\n",
" <td>8.7</td>\n",
" <td>160</td>\n",
" <td>5300</td>\n",
" <td>19</td>\n",
" <td>25</td>\n",
" <td>19045</td>\n",
" </tr>\n",
" <tr>\n",
" <th>202</th>\n",
" <td>-1</td>\n",
" <td>95</td>\n",
" <td>volvo</td>\n",
" <td>gas</td>\n",
" <td>std</td>\n",
" <td>four</td>\n",
" <td>sedan</td>\n",
" <td>rwd</td>\n",
" <td>front</td>\n",
" <td>109.1</td>\n",
" <td>...</td>\n",
" <td>173</td>\n",
" <td>mpfi</td>\n",
" <td>3.58</td>\n",
" <td>2.87</td>\n",
" <td>8.8</td>\n",
" <td>134</td>\n",
" <td>5500</td>\n",
" <td>18</td>\n",
" <td>23</td>\n",
" <td>21485</td>\n",
" </tr>\n",
" <tr>\n",
" <th>203</th>\n",
" <td>-1</td>\n",
" <td>95</td>\n",
" <td>volvo</td>\n",
" <td>diesel</td>\n",
" <td>turbo</td>\n",
" <td>four</td>\n",
" <td>sedan</td>\n",
" <td>rwd</td>\n",
" <td>front</td>\n",
" <td>109.1</td>\n",
" <td>...</td>\n",
" <td>145</td>\n",
" <td>idi</td>\n",
" <td>3.01</td>\n",
" <td>3.40</td>\n",
" <td>23.0</td>\n",
" <td>106</td>\n",
" <td>4800</td>\n",
" <td>26</td>\n",
" <td>27</td>\n",
" <td>22470</td>\n",
" </tr>\n",
" <tr>\n",
" <th>204</th>\n",
" <td>-1</td>\n",
" <td>95</td>\n",
" <td>volvo</td>\n",
" <td>gas</td>\n",
" <td>turbo</td>\n",
" <td>four</td>\n",
" <td>sedan</td>\n",
" <td>rwd</td>\n",
" <td>front</td>\n",
" <td>109.1</td>\n",
" <td>...</td>\n",
" <td>141</td>\n",
" <td>mpfi</td>\n",
" <td>3.78</td>\n",
" <td>3.15</td>\n",
" <td>9.5</td>\n",
" <td>114</td>\n",
" <td>5400</td>\n",
" <td>19</td>\n",
" <td>25</td>\n",
" <td>22625</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>10 rows × 26 columns</p>\n",
"</div>"
],
"text/plain": [
" 0 1 2 3 4 5 6 7 8 9 ... 16 \\\n",
"195 -1 74 volvo gas std four wagon rwd front 104.3 ... 141 \n",
"196 -2 103 volvo gas std four sedan rwd front 104.3 ... 141 \n",
"197 -1 74 volvo gas std four wagon rwd front 104.3 ... 141 \n",
"198 -2 103 volvo gas turbo four sedan rwd front 104.3 ... 130 \n",
"199 -1 74 volvo gas turbo four wagon rwd front 104.3 ... 130 \n",
"200 -1 95 volvo gas std four sedan rwd front 109.1 ... 141 \n",
"201 -1 95 volvo gas turbo four sedan rwd front 109.1 ... 141 \n",
"202 -1 95 volvo gas std four sedan rwd front 109.1 ... 173 \n",
"203 -1 95 volvo diesel turbo four sedan rwd front 109.1 ... 145 \n",
"204 -1 95 volvo gas turbo four sedan rwd front 109.1 ... 141 \n",
"\n",
" 17 18 19 20 21 22 23 24 25 \n",
"195 mpfi 3.78 3.15 9.5 114 5400 23 28 13415 \n",
"196 mpfi 3.78 3.15 9.5 114 5400 24 28 15985 \n",
"197 mpfi 3.78 3.15 9.5 114 5400 24 28 16515 \n",
"198 mpfi 3.62 3.15 7.5 162 5100 17 22 18420 \n",
"199 mpfi 3.62 3.15 7.5 162 5100 17 22 18950 \n",
"200 mpfi 3.78 3.15 9.5 114 5400 23 28 16845 \n",
"201 mpfi 3.78 3.15 8.7 160 5300 19 25 19045 \n",
"202 mpfi 3.58 2.87 8.8 134 5500 18 23 21485 \n",
"203 idi 3.01 3.40 23.0 106 4800 26 27 22470 \n",
"204 mpfi 3.78 3.15 9.5 114 5400 19 25 22625 \n",
"\n",
"[10 rows x 26 columns]"
]
},
"execution_count": 12,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# show the Last 10 rows using dataframe.tail() method\n",
"print(\"The Last 10 rows of the dataframe\") \n",
"df.tail(10)"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"headers\n",
" ['symboling', 'normalized-losses', 'make', 'fuel-type', 'aspiration', 'num-of-doors', 'body-style', 'drive-wheels', 'engine-location', 'wheel-base', 'length', 'width', 'height', 'curb-weight', 'engine-type', 'num-of-cylinders', 'engine-size', 'fuel-system', 'bore', 'stroke', 'compression-ratio', 'horsepower', 'peak-rpm', 'city-mpg', 'highway-mpg', 'price']\n"
]
}
],
"source": [
"# create headers list\n",
"headers = [\"symboling\",\"normalized-losses\",\"make\",\"fuel-type\",\"aspiration\", \"num-of-doors\",\"body-style\",\n",
" \"drive-wheels\",\"engine-location\",\"wheel-base\", \"length\",\"width\",\"height\",\"curb-weight\",\"engine-type\",\n",
" \"num-of-cylinders\", \"engine-size\",\"fuel-system\",\"bore\",\"stroke\",\"compression-ratio\",\"horsepower\",\n",
" \"peak-rpm\",\"city-mpg\",\"highway-mpg\",\"price\"]\n",
"print(\"headers\\n\", headers)"
]
},
{
"cell_type": "code",
"execution_count": 16,
"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>symboling</th>\n",
" <th>normalized-losses</th>\n",
" <th>make</th>\n",
" <th>fuel-type</th>\n",
" <th>aspiration</th>\n",
" <th>num-of-doors</th>\n",
" <th>body-style</th>\n",
" <th>drive-wheels</th>\n",
" <th>engine-location</th>\n",
" <th>wheel-base</th>\n",
" <th>...</th>\n",
" <th>engine-size</th>\n",
" <th>fuel-system</th>\n",
" <th>bore</th>\n",
" <th>stroke</th>\n",
" <th>compression-ratio</th>\n",
" <th>horsepower</th>\n",
" <th>peak-rpm</th>\n",
" <th>city-mpg</th>\n",
" <th>highway-mpg</th>\n",
" <th>price</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>3</td>\n",
" <td>?</td>\n",
" <td>alfa-romero</td>\n",
" <td>gas</td>\n",
" <td>std</td>\n",
" <td>two</td>\n",
" <td>convertible</td>\n",
" <td>rwd</td>\n",
" <td>front</td>\n",
" <td>88.6</td>\n",
" <td>...</td>\n",
" <td>130</td>\n",
" <td>mpfi</td>\n",
" <td>3.47</td>\n",
" <td>2.68</td>\n",
" <td>9.0</td>\n",
" <td>111</td>\n",
" <td>5000</td>\n",
" <td>21</td>\n",
" <td>27</td>\n",
" <td>13495</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>3</td>\n",
" <td>?</td>\n",
" <td>alfa-romero</td>\n",
" <td>gas</td>\n",
" <td>std</td>\n",
" <td>two</td>\n",
" <td>convertible</td>\n",
" <td>rwd</td>\n",
" <td>front</td>\n",
" <td>88.6</td>\n",
" <td>...</td>\n",
" <td>130</td>\n",
" <td>mpfi</td>\n",
" <td>3.47</td>\n",
" <td>2.68</td>\n",
" <td>9.0</td>\n",
" <td>111</td>\n",
" <td>5000</td>\n",
" <td>21</td>\n",
" <td>27</td>\n",
" <td>16500</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>1</td>\n",
" <td>?</td>\n",
" <td>alfa-romero</td>\n",
" <td>gas</td>\n",
" <td>std</td>\n",
" <td>two</td>\n",
" <td>hatchback</td>\n",
" <td>rwd</td>\n",
" <td>front</td>\n",
" <td>94.5</td>\n",
" <td>...</td>\n",
" <td>152</td>\n",
" <td>mpfi</td>\n",
" <td>2.68</td>\n",
" <td>3.47</td>\n",
" <td>9.0</td>\n",
" <td>154</td>\n",
" <td>5000</td>\n",
" <td>19</td>\n",
" <td>26</td>\n",
" <td>16500</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>2</td>\n",
" <td>164</td>\n",
" <td>audi</td>\n",
" <td>gas</td>\n",
" <td>std</td>\n",
" <td>four</td>\n",
" <td>sedan</td>\n",
" <td>fwd</td>\n",
" <td>front</td>\n",
" <td>99.8</td>\n",
" <td>...</td>\n",
" <td>109</td>\n",
" <td>mpfi</td>\n",
" <td>3.19</td>\n",
" <td>3.40</td>\n",
" <td>10.0</td>\n",
" <td>102</td>\n",
" <td>5500</td>\n",
" <td>24</td>\n",
" <td>30</td>\n",
" <td>13950</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>2</td>\n",
" <td>164</td>\n",
" <td>audi</td>\n",
" <td>gas</td>\n",
" <td>std</td>\n",
" <td>four</td>\n",
" <td>sedan</td>\n",
" <td>4wd</td>\n",
" <td>front</td>\n",
" <td>99.4</td>\n",
" <td>...</td>\n",
" <td>136</td>\n",
" <td>mpfi</td>\n",
" <td>3.19</td>\n",
" <td>3.40</td>\n",
" <td>8.0</td>\n",
" <td>115</td>\n",
" <td>5500</td>\n",
" <td>18</td>\n",
" <td>22</td>\n",
" <td>17450</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5</th>\n",
" <td>2</td>\n",
" <td>?</td>\n",
" <td>audi</td>\n",
" <td>gas</td>\n",
" <td>std</td>\n",
" <td>two</td>\n",
" <td>sedan</td>\n",
" <td>fwd</td>\n",
" <td>front</td>\n",
" <td>99.8</td>\n",
" <td>...</td>\n",
" <td>136</td>\n",
" <td>mpfi</td>\n",
" <td>3.19</td>\n",
" <td>3.40</td>\n",
" <td>8.5</td>\n",
" <td>110</td>\n",
" <td>5500</td>\n",
" <td>19</td>\n",
" <td>25</td>\n",
" <td>15250</td>\n",
" </tr>\n",
" <tr>\n",
" <th>6</th>\n",
" <td>1</td>\n",
" <td>158</td>\n",
" <td>audi</td>\n",
" <td>gas</td>\n",
" <td>std</td>\n",
" <td>four</td>\n",
" <td>sedan</td>\n",
" <td>fwd</td>\n",
" <td>front</td>\n",
" <td>105.8</td>\n",
" <td>...</td>\n",
" <td>136</td>\n",
" <td>mpfi</td>\n",
" <td>3.19</td>\n",
" <td>3.40</td>\n",
" <td>8.5</td>\n",
" <td>110</td>\n",
" <td>5500</td>\n",
" <td>19</td>\n",
" <td>25</td>\n",
" <td>17710</td>\n",
" </tr>\n",
" <tr>\n",
" <th>7</th>\n",
" <td>1</td>\n",
" <td>?</td>\n",
" <td>audi</td>\n",
" <td>gas</td>\n",
" <td>std</td>\n",
" <td>four</td>\n",
" <td>wagon</td>\n",
" <td>fwd</td>\n",
" <td>front</td>\n",
" <td>105.8</td>\n",
" <td>...</td>\n",
" <td>136</td>\n",
" <td>mpfi</td>\n",
" <td>3.19</td>\n",
" <td>3.40</td>\n",
" <td>8.5</td>\n",
" <td>110</td>\n",
" <td>5500</td>\n",
" <td>19</td>\n",
" <td>25</td>\n",
" <td>18920</td>\n",
" </tr>\n",
" <tr>\n",
" <th>8</th>\n",
" <td>1</td>\n",
" <td>158</td>\n",
" <td>audi</td>\n",
" <td>gas</td>\n",
" <td>turbo</td>\n",
" <td>four</td>\n",
" <td>sedan</td>\n",
" <td>fwd</td>\n",
" <td>front</td>\n",
" <td>105.8</td>\n",
" <td>...</td>\n",
" <td>131</td>\n",
" <td>mpfi</td>\n",
" <td>3.13</td>\n",
" <td>3.40</td>\n",
" <td>8.3</td>\n",
" <td>140</td>\n",
" <td>5500</td>\n",
" <td>17</td>\n",
" <td>20</td>\n",
" <td>23875</td>\n",
" </tr>\n",
" <tr>\n",
" <th>9</th>\n",
" <td>0</td>\n",
" <td>?</td>\n",
" <td>audi</td>\n",
" <td>gas</td>\n",
" <td>turbo</td>\n",
" <td>two</td>\n",
" <td>hatchback</td>\n",
" <td>4wd</td>\n",
" <td>front</td>\n",
" <td>99.5</td>\n",
" <td>...</td>\n",
" <td>131</td>\n",
" <td>mpfi</td>\n",
" <td>3.13</td>\n",
" <td>3.40</td>\n",
" <td>7.0</td>\n",
" <td>160</td>\n",
" <td>5500</td>\n",
" <td>16</td>\n",
" <td>22</td>\n",
" <td>?</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>10 rows × 26 columns</p>\n",
"</div>"
],
"text/plain": [
" symboling normalized-losses make fuel-type aspiration num-of-doors \\\n",
"0 3 ? alfa-romero gas std two \n",
"1 3 ? alfa-romero gas std two \n",
"2 1 ? alfa-romero gas std two \n",
"3 2 164 audi gas std four \n",
"4 2 164 audi gas std four \n",
"5 2 ? audi gas std two \n",
"6 1 158 audi gas std four \n",
"7 1 ? audi gas std four \n",
"8 1 158 audi gas turbo four \n",
"9 0 ? audi gas turbo two \n",
"\n",
" body-style drive-wheels engine-location wheel-base ... engine-size \\\n",
"0 convertible rwd front 88.6 ... 130 \n",
"1 convertible rwd front 88.6 ... 130 \n",
"2 hatchback rwd front 94.5 ... 152 \n",
"3 sedan fwd front 99.8 ... 109 \n",
"4 sedan 4wd front 99.4 ... 136 \n",
"5 sedan fwd front 99.8 ... 136 \n",
"6 sedan fwd front 105.8 ... 136 \n",
"7 wagon fwd front 105.8 ... 136 \n",
"8 sedan fwd front 105.8 ... 131 \n",
"9 hatchback 4wd front 99.5 ... 131 \n",
"\n",
" fuel-system bore stroke compression-ratio horsepower peak-rpm city-mpg \\\n",
"0 mpfi 3.47 2.68 9.0 111 5000 21 \n",
"1 mpfi 3.47 2.68 9.0 111 5000 21 \n",
"2 mpfi 2.68 3.47 9.0 154 5000 19 \n",
"3 mpfi 3.19 3.40 10.0 102 5500 24 \n",
"4 mpfi 3.19 3.40 8.0 115 5500 18 \n",
"5 mpfi 3.19 3.40 8.5 110 5500 19 \n",
"6 mpfi 3.19 3.40 8.5 110 5500 19 \n",
"7 mpfi 3.19 3.40 8.5 110 5500 19 \n",
"8 mpfi 3.13 3.40 8.3 140 5500 17 \n",
"9 mpfi 3.13 3.40 7.0 160 5500 16 \n",
"\n",
" highway-mpg price \n",
"0 27 13495 \n",
"1 27 16500 \n",
"2 26 16500 \n",
"3 30 13950 \n",
"4 22 17450 \n",
"5 25 15250 \n",
"6 25 17710 \n",
"7 25 18920 \n",
"8 20 23875 \n",
"9 22 ? \n",
"\n",
"[10 rows x 26 columns]"
]
},
"execution_count": 16,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df.columns = headers\n",
"df.head(10)"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {},
"outputs": [],
"source": [
"# Replace Missing values with Nan\n",
"df1=df.replace('?',np.NaN)"
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Index(['symboling', 'normalized-losses', 'make', 'fuel-type', 'aspiration',\n",
" 'num-of-doors', 'body-style', 'drive-wheels', 'engine-location',\n",
" 'wheel-base', 'length', 'width', 'height', 'curb-weight', 'engine-type',\n",
" 'num-of-cylinders', 'engine-size', 'fuel-system', 'bore', 'stroke',\n",
" 'compression-ratio', 'horsepower', 'peak-rpm', 'city-mpg',\n",
" 'highway-mpg', 'price'],\n",
" dtype='object')\n"
]
}
],
"source": [
"print(df.columns)"
]
},
{
"cell_type": "code",
"execution_count": 18,
"metadata": {},
"outputs": [],
"source": [
"df.to_csv(\"automobile.csv\", index=False)"
]
},
{
"cell_type": "code",
"execution_count": 19,
"metadata": {},
"outputs": [],
"source": [
"# use similar functions to pd.read_csv() and df.to_csv() for other data formats\n",
"# Data Formate\tRead\tSave\n",
"# csv\tpd.read_csv()\tdf.to_csv()\n",
"# json\tpd.read_json()\tdf.to_json()\n",
"# excel\tpd.read_excel()\tdf.to_excel()\n",
"# hdf\tpd.read_hdf()\tdf.to_hdf()\n",
"# sql\tpd.read_sql()\tdf.to_sql()\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": 21,
"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>symboling</th>\n",
" <th>wheel-base</th>\n",
" <th>length</th>\n",
" <th>width</th>\n",
" <th>height</th>\n",
" <th>curb-weight</th>\n",
" <th>engine-size</th>\n",
" <th>compression-ratio</th>\n",
" <th>city-mpg</th>\n",
" <th>highway-mpg</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>count</th>\n",
" <td>205.000000</td>\n",
" <td>205.000000</td>\n",
" <td>205.000000</td>\n",
" <td>205.000000</td>\n",
" <td>205.000000</td>\n",
" <td>205.000000</td>\n",
" <td>205.000000</td>\n",
" <td>205.000000</td>\n",
" <td>205.000000</td>\n",
" <td>205.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>mean</th>\n",
" <td>0.834146</td>\n",
" <td>98.756585</td>\n",
" <td>174.049268</td>\n",
" <td>65.907805</td>\n",
" <td>53.724878</td>\n",
" <td>2555.565854</td>\n",
" <td>126.907317</td>\n",
" <td>10.142537</td>\n",
" <td>25.219512</td>\n",
" <td>30.751220</td>\n",
" </tr>\n",
" <tr>\n",
" <th>std</th>\n",
" <td>1.245307</td>\n",
" <td>6.021776</td>\n",
" <td>12.337289</td>\n",
" <td>2.145204</td>\n",
" <td>2.443522</td>\n",
" <td>520.680204</td>\n",
" <td>41.642693</td>\n",
" <td>3.972040</td>\n",
" <td>6.542142</td>\n",
" <td>6.886443</td>\n",
" </tr>\n",
" <tr>\n",
" <th>min</th>\n",
" <td>-2.000000</td>\n",
" <td>86.600000</td>\n",
" <td>141.100000</td>\n",
" <td>60.300000</td>\n",
" <td>47.800000</td>\n",
" <td>1488.000000</td>\n",
" <td>61.000000</td>\n",
" <td>7.000000</td>\n",
" <td>13.000000</td>\n",
" <td>16.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>25%</th>\n",
" <td>0.000000</td>\n",
" <td>94.500000</td>\n",
" <td>166.300000</td>\n",
" <td>64.100000</td>\n",
" <td>52.000000</td>\n",
" <td>2145.000000</td>\n",
" <td>97.000000</td>\n",
" <td>8.600000</td>\n",
" <td>19.000000</td>\n",
" <td>25.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>50%</th>\n",
" <td>1.000000</td>\n",
" <td>97.000000</td>\n",
" <td>173.200000</td>\n",
" <td>65.500000</td>\n",
" <td>54.100000</td>\n",
" <td>2414.000000</td>\n",
" <td>120.000000</td>\n",
" <td>9.000000</td>\n",
" <td>24.000000</td>\n",
" <td>30.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>75%</th>\n",
" <td>2.000000</td>\n",
" <td>102.400000</td>\n",
" <td>183.100000</td>\n",
" <td>66.900000</td>\n",
" <td>55.500000</td>\n",
" <td>2935.000000</td>\n",
" <td>141.000000</td>\n",
" <td>9.400000</td>\n",
" <td>30.000000</td>\n",
" <td>34.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>max</th>\n",
" <td>3.000000</td>\n",
" <td>120.900000</td>\n",
" <td>208.100000</td>\n",
" <td>72.300000</td>\n",
" <td>59.800000</td>\n",
" <td>4066.000000</td>\n",
" <td>326.000000</td>\n",
" <td>23.000000</td>\n",
" <td>49.000000</td>\n",
" <td>54.000000</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" symboling wheel-base length width height \\\n",
"count 205.000000 205.000000 205.000000 205.000000 205.000000 \n",
"mean 0.834146 98.756585 174.049268 65.907805 53.724878 \n",
"std 1.245307 6.021776 12.337289 2.145204 2.443522 \n",
"min -2.000000 86.600000 141.100000 60.300000 47.800000 \n",
"25% 0.000000 94.500000 166.300000 64.100000 52.000000 \n",
"50% 1.000000 97.000000 173.200000 65.500000 54.100000 \n",
"75% 2.000000 102.400000 183.100000 66.900000 55.500000 \n",
"max 3.000000 120.900000 208.100000 72.300000 59.800000 \n",
"\n",
" curb-weight engine-size compression-ratio city-mpg highway-mpg \n",
"count 205.000000 205.000000 205.000000 205.000000 205.000000 \n",
"mean 2555.565854 126.907317 10.142537 25.219512 30.751220 \n",
"std 520.680204 41.642693 3.972040 6.542142 6.886443 \n",
"min 1488.000000 61.000000 7.000000 13.000000 16.000000 \n",
"25% 2145.000000 97.000000 8.600000 19.000000 25.000000 \n",
"50% 2414.000000 120.000000 9.000000 24.000000 30.000000 \n",
"75% 2935.000000 141.000000 9.400000 30.000000 34.000000 \n",
"max 4066.000000 326.000000 23.000000 49.000000 54.000000 "
]
},
"execution_count": 21,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# dataframe.describe()\n",
"df.describe()"
]
},
{
"cell_type": "code",
"execution_count": 22,
"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>symboling</th>\n",
" <th>normalized-losses</th>\n",
" <th>make</th>\n",
" <th>fuel-type</th>\n",
" <th>aspiration</th>\n",
" <th>num-of-doors</th>\n",
" <th>body-style</th>\n",
" <th>drive-wheels</th>\n",
" <th>engine-location</th>\n",
" <th>wheel-base</th>\n",
" <th>...</th>\n",
" <th>engine-size</th>\n",
" <th>fuel-system</th>\n",
" <th>bore</th>\n",
" <th>stroke</th>\n",
" <th>compression-ratio</th>\n",
" <th>horsepower</th>\n",
" <th>peak-rpm</th>\n",
" <th>city-mpg</th>\n",
" <th>highway-mpg</th>\n",
" <th>price</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>count</th>\n",
" <td>205.000000</td>\n",
" <td>205</td>\n",
" <td>205</td>\n",
" <td>205</td>\n",
" <td>205</td>\n",
" <td>205</td>\n",
" <td>205</td>\n",
" <td>205</td>\n",
" <td>205</td>\n",
" <td>205.000000</td>\n",
" <td>...</td>\n",
" <td>205.000000</td>\n",
" <td>205</td>\n",
" <td>205</td>\n",
" <td>205</td>\n",
" <td>205.000000</td>\n",
" <td>205</td>\n",
" <td>205</td>\n",
" <td>205.000000</td>\n",
" <td>205.000000</td>\n",
" <td>205</td>\n",
" </tr>\n",
" <tr>\n",
" <th>unique</th>\n",
" <td>NaN</td>\n",
" <td>52</td>\n",
" <td>22</td>\n",
" <td>2</td>\n",
" <td>2</td>\n",
" <td>3</td>\n",
" <td>5</td>\n",
" <td>3</td>\n",
" <td>2</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>8</td>\n",
" <td>39</td>\n",
" <td>37</td>\n",
" <td>NaN</td>\n",
" <td>60</td>\n",
" <td>24</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>187</td>\n",
" </tr>\n",
" <tr>\n",
" <th>top</th>\n",
" <td>NaN</td>\n",
" <td>?</td>\n",
" <td>toyota</td>\n",
" <td>gas</td>\n",
" <td>std</td>\n",
" <td>four</td>\n",
" <td>sedan</td>\n",
" <td>fwd</td>\n",
" <td>front</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>mpfi</td>\n",
" <td>3.62</td>\n",
" <td>3.40</td>\n",
" <td>NaN</td>\n",
" <td>68</td>\n",
" <td>5500</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>?</td>\n",
" </tr>\n",
" <tr>\n",
" <th>freq</th>\n",
" <td>NaN</td>\n",
" <td>41</td>\n",
" <td>32</td>\n",
" <td>185</td>\n",
" <td>168</td>\n",
" <td>114</td>\n",
" <td>96</td>\n",
" <td>120</td>\n",
" <td>202</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>94</td>\n",
" <td>23</td>\n",
" <td>20</td>\n",
" <td>NaN</td>\n",
" <td>19</td>\n",
" <td>37</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>4</td>\n",
" </tr>\n",
" <tr>\n",
" <th>mean</th>\n",
" <td>0.834146</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>98.756585</td>\n",
" <td>...</td>\n",
" <td>126.907317</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>10.142537</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>25.219512</td>\n",
" <td>30.751220</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>std</th>\n",
" <td>1.245307</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>6.021776</td>\n",
" <td>...</td>\n",
" <td>41.642693</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>3.972040</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>6.542142</td>\n",
" <td>6.886443</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>min</th>\n",
" <td>-2.000000</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>86.600000</td>\n",
" <td>...</td>\n",
" <td>61.000000</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>7.000000</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>13.000000</td>\n",
" <td>16.000000</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>25%</th>\n",
" <td>0.000000</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>94.500000</td>\n",
" <td>...</td>\n",
" <td>97.000000</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>8.600000</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>19.000000</td>\n",
" <td>25.000000</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>50%</th>\n",
" <td>1.000000</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>97.000000</td>\n",
" <td>...</td>\n",
" <td>120.000000</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>9.000000</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>24.000000</td>\n",
" <td>30.000000</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>75%</th>\n",
" <td>2.000000</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>102.400000</td>\n",
" <td>...</td>\n",
" <td>141.000000</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>9.400000</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>30.000000</td>\n",
" <td>34.000000</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>max</th>\n",
" <td>3.000000</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>120.900000</td>\n",
" <td>...</td>\n",
" <td>326.000000</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>23.000000</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>49.000000</td>\n",
" <td>54.000000</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>11 rows × 26 columns</p>\n",
"</div>"
],
"text/plain": [
" symboling normalized-losses make fuel-type aspiration \\\n",
"count 205.000000 205 205 205 205 \n",
"unique NaN 52 22 2 2 \n",
"top NaN ? toyota gas std \n",
"freq NaN 41 32 185 168 \n",
"mean 0.834146 NaN NaN NaN NaN \n",
"std 1.245307 NaN NaN NaN NaN \n",
"min -2.000000 NaN NaN NaN NaN \n",
"25% 0.000000 NaN NaN NaN NaN \n",
"50% 1.000000 NaN NaN NaN NaN \n",
"75% 2.000000 NaN NaN NaN NaN \n",
"max 3.000000 NaN NaN NaN NaN \n",
"\n",
" num-of-doors body-style drive-wheels engine-location wheel-base ... \\\n",
"count 205 205 205 205 205.000000 ... \n",
"unique 3 5 3 2 NaN ... \n",
"top four sedan fwd front NaN ... \n",
"freq 114 96 120 202 NaN ... \n",
"mean NaN NaN NaN NaN 98.756585 ... \n",
"std NaN NaN NaN NaN 6.021776 ... \n",
"min NaN NaN NaN NaN 86.600000 ... \n",
"25% NaN NaN NaN NaN 94.500000 ... \n",
"50% NaN NaN NaN NaN 97.000000 ... \n",
"75% NaN NaN NaN NaN 102.400000 ... \n",
"max NaN NaN NaN NaN 120.900000 ... \n",
"\n",
" engine-size fuel-system bore stroke compression-ratio horsepower \\\n",
"count 205.000000 205 205 205 205.000000 205 \n",
"unique NaN 8 39 37 NaN 60 \n",
"top NaN mpfi 3.62 3.40 NaN 68 \n",
"freq NaN 94 23 20 NaN 19 \n",
"mean 126.907317 NaN NaN NaN 10.142537 NaN \n",
"std 41.642693 NaN NaN NaN 3.972040 NaN \n",
"min 61.000000 NaN NaN NaN 7.000000 NaN \n",
"25% 97.000000 NaN NaN NaN 8.600000 NaN \n",
"50% 120.000000 NaN NaN NaN 9.000000 NaN \n",
"75% 141.000000 NaN NaN NaN 9.400000 NaN \n",
"max 326.000000 NaN NaN NaN 23.000000 NaN \n",
"\n",
" peak-rpm city-mpg highway-mpg price \n",
"count 205 205.000000 205.000000 205 \n",
"unique 24 NaN NaN 187 \n",
"top 5500 NaN NaN ? \n",
"freq 37 NaN NaN 4 \n",
"mean NaN 25.219512 30.751220 NaN \n",
"std NaN 6.542142 6.886443 NaN \n",
"min NaN 13.000000 16.000000 NaN \n",
"25% NaN 19.000000 25.000000 NaN \n",
"50% NaN 24.000000 30.000000 NaN \n",
"75% NaN 30.000000 34.000000 NaN \n",
"max NaN 49.000000 54.000000 NaN \n",
"\n",
"[11 rows x 26 columns]"
]
},
"execution_count": 22,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# describe all the columns in \"df\" \n",
"df.describe(include = \"all\")"
]
},
{
"cell_type": "code",
"execution_count": 29,
"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>length</th>\n",
" <th>compression-ratio</th>\n",
" <th>price</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>168.8</td>\n",
" <td>9.0</td>\n",
" <td>13495</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>168.8</td>\n",
" <td>9.0</td>\n",
" <td>16500</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>171.2</td>\n",
" <td>9.0</td>\n",
" <td>16500</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>176.6</td>\n",
" <td>10.0</td>\n",
" <td>13950</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>176.6</td>\n",
" <td>8.0</td>\n",
" <td>17450</td>\n",
" </tr>\n",
" <tr>\n",
" <th>...</th>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>200</th>\n",
" <td>188.8</td>\n",
" <td>9.5</td>\n",
" <td>16845</td>\n",
" </tr>\n",
" <tr>\n",
" <th>201</th>\n",
" <td>188.8</td>\n",
" <td>8.7</td>\n",
" <td>19045</td>\n",
" </tr>\n",
" <tr>\n",
" <th>202</th>\n",
" <td>188.8</td>\n",
" <td>8.8</td>\n",
" <td>21485</td>\n",
" </tr>\n",
" <tr>\n",
" <th>203</th>\n",
" <td>188.8</td>\n",
" <td>23.0</td>\n",
" <td>22470</td>\n",
" </tr>\n",
" <tr>\n",
" <th>204</th>\n",
" <td>188.8</td>\n",
" <td>9.5</td>\n",
" <td>22625</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>205 rows × 3 columns</p>\n",
"</div>"
],
"text/plain": [
" length compression-ratio price\n",
"0 168.8 9.0 13495\n",
"1 168.8 9.0 16500\n",
"2 171.2 9.0 16500\n",
"3 176.6 10.0 13950\n",
"4 176.6 8.0 17450\n",
".. ... ... ...\n",
"200 188.8 9.5 16845\n",
"201 188.8 8.7 19045\n",
"202 188.8 8.8 21485\n",
"203 188.8 23.0 22470\n",
"204 188.8 9.5 22625\n",
"\n",
"[205 rows x 3 columns]"
]
},
"execution_count": 29,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df[['length' , 'compression-ratio', 'price']]"
]
},
{
"cell_type": "code",
"execution_count": 28,
"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>length</th>\n",
" <th>compression-ratio</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>count</th>\n",
" <td>205.000000</td>\n",
" <td>205.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>mean</th>\n",
" <td>174.049268</td>\n",
" <td>10.142537</td>\n",
" </tr>\n",
" <tr>\n",
" <th>std</th>\n",
" <td>12.337289</td>\n",
" <td>3.972040</td>\n",
" </tr>\n",
" <tr>\n",
" <th>min</th>\n",
" <td>141.100000</td>\n",
" <td>7.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>25%</th>\n",
" <td>166.300000</td>\n",
" <td>8.600000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>50%</th>\n",
" <td>173.200000</td>\n",
" <td>9.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>75%</th>\n",
" <td>183.100000</td>\n",
" <td>9.400000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>max</th>\n",
" <td>208.100000</td>\n",
" <td>23.000000</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" length compression-ratio\n",
"count 205.000000 205.000000\n",
"mean 174.049268 10.142537\n",
"std 12.337289 3.972040\n",
"min 141.100000 7.000000\n",
"25% 166.300000 8.600000\n",
"50% 173.200000 9.000000\n",
"75% 183.100000 9.400000\n",
"max 208.100000 23.000000"
]
},
"execution_count": 28,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df[['length', 'compression-ratio']].describe()"
]
},
{
"cell_type": "code",
"execution_count": 31,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"<class 'pandas.core.frame.DataFrame'>\n",
"RangeIndex: 205 entries, 0 to 204\n",
"Data columns (total 26 columns):\n",
" # Column Non-Null Count Dtype \n",
"--- ------ -------------- ----- \n",
" 0 symboling 205 non-null int64 \n",
" 1 normalized-losses 205 non-null object \n",
" 2 make 205 non-null object \n",
" 3 fuel-type 205 non-null object \n",
" 4 aspiration 205 non-null object \n",
" 5 num-of-doors 205 non-null object \n",
" 6 body-style 205 non-null object \n",
" 7 drive-wheels 205 non-null object \n",
" 8 engine-location 205 non-null object \n",
" 9 wheel-base 205 non-null float64\n",
" 10 length 205 non-null float64\n",
" 11 width 205 non-null float64\n",
" 12 height 205 non-null float64\n",
" 13 curb-weight 205 non-null int64 \n",
" 14 engine-type 205 non-null object \n",
" 15 num-of-cylinders 205 non-null object \n",
" 16 engine-size 205 non-null int64 \n",
" 17 fuel-system 205 non-null object \n",
" 18 bore 205 non-null object \n",
" 19 stroke 205 non-null object \n",
" 20 compression-ratio 205 non-null float64\n",
" 21 horsepower 205 non-null object \n",
" 22 peak-rpm 205 non-null object \n",
" 23 city-mpg 205 non-null int64 \n",
" 24 highway-mpg 205 non-null int64 \n",
" 25 price 205 non-null object \n",
"dtypes: float64(5), int64(5), object(16)\n",
"memory usage: 41.8+ KB\n"
]
}
],
"source": [
"# look at the info of \"df\"\n",
"df.info()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python",
"language": "python",
"name": "conda-env-python-py"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.6.12"
}
},
"nbformat": 4,
"nbformat_minor": 4
}
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