countvalues
================
<!-- WARNING: THIS FILE WAS AUTOGENERATED! DO NOT EDIT! -->
## Install
``` sh
pip install countvalues
```
## How to use
``` python
import pandas as pd
from countvalues.core import count_values
```
``` python
df = pd.read_csv('../data/titanic.csv')
df.head()
```
<div>
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<table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>PassengerId</th>
<th>Survived</th>
<th>Pclass</th>
<th>Name</th>
<th>Sex</th>
<th>Age</th>
<th>SibSp</th>
<th>Parch</th>
<th>Ticket</th>
<th>Fare</th>
<th>Cabin</th>
<th>Embarked</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
<td>0</td>
<td>3</td>
<td>Braund, Mr. Owen Harris</td>
<td>male</td>
<td>22.0</td>
<td>1</td>
<td>0</td>
<td>A/5 21171</td>
<td>7.2500</td>
<td>NaN</td>
<td>S</td>
</tr>
<tr>
<th>1</th>
<td>2</td>
<td>1</td>
<td>1</td>
<td>Cumings, Mrs. John Bradley (Florence Briggs Th...</td>
<td>female</td>
<td>38.0</td>
<td>1</td>
<td>0</td>
<td>PC 17599</td>
<td>71.2833</td>
<td>C85</td>
<td>C</td>
</tr>
<tr>
<th>2</th>
<td>3</td>
<td>1</td>
<td>3</td>
<td>Heikkinen, Miss. Laina</td>
<td>female</td>
<td>26.0</td>
<td>0</td>
<td>0</td>
<td>STON/O2. 3101282</td>
<td>7.9250</td>
<td>NaN</td>
<td>S</td>
</tr>
<tr>
<th>3</th>
<td>4</td>
<td>1</td>
<td>1</td>
<td>Futrelle, Mrs. Jacques Heath (Lily May Peel)</td>
<td>female</td>
<td>35.0</td>
<td>1</td>
<td>0</td>
<td>113803</td>
<td>53.1000</td>
<td>C123</td>
<td>S</td>
</tr>
<tr>
<th>4</th>
<td>5</td>
<td>0</td>
<td>3</td>
<td>Allen, Mr. William Henry</td>
<td>male</td>
<td>35.0</td>
<td>0</td>
<td>0</td>
<td>373450</td>
<td>8.0500</td>
<td>NaN</td>
<td>S</td>
</tr>
</tbody>
</table>
</div>
``` python
count_values(df, 'Sex')
```
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<table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>Sex</th>
<th>count</th>
<th>percentual</th>
<th>cumulative_percentual</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>female</td>
<td>314</td>
<td>0.352413</td>
<td>0.352413</td>
</tr>
<tr>
<th>1</th>
<td>male</td>
<td>577</td>
<td>0.647587</td>
<td>1.000000</td>
</tr>
</tbody>
</table>
</div>
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"description": "countvalues\n================\n\n<!-- WARNING: THIS FILE WAS AUTOGENERATED! DO NOT EDIT! -->\n\n## Install\n\n``` sh\npip install countvalues\n```\n\n## How to use\n\n``` python\nimport pandas as pd\nfrom countvalues.core import count_values\n```\n\n``` python\ndf = pd.read_csv('../data/titanic.csv')\ndf.head()\n```\n\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>PassengerId</th>\n <th>Survived</th>\n <th>Pclass</th>\n <th>Name</th>\n <th>Sex</th>\n <th>Age</th>\n <th>SibSp</th>\n <th>Parch</th>\n <th>Ticket</th>\n <th>Fare</th>\n <th>Cabin</th>\n <th>Embarked</th>\n </tr>\n </thead>\n <tbody>\n <tr>\n <th>0</th>\n <td>1</td>\n <td>0</td>\n <td>3</td>\n <td>Braund, Mr. Owen Harris</td>\n <td>male</td>\n <td>22.0</td>\n <td>1</td>\n <td>0</td>\n <td>A/5 21171</td>\n <td>7.2500</td>\n <td>NaN</td>\n <td>S</td>\n </tr>\n <tr>\n <th>1</th>\n <td>2</td>\n <td>1</td>\n <td>1</td>\n <td>Cumings, Mrs. John Bradley (Florence Briggs Th...</td>\n <td>female</td>\n <td>38.0</td>\n <td>1</td>\n <td>0</td>\n <td>PC 17599</td>\n <td>71.2833</td>\n <td>C85</td>\n <td>C</td>\n </tr>\n <tr>\n <th>2</th>\n <td>3</td>\n <td>1</td>\n <td>3</td>\n <td>Heikkinen, Miss. Laina</td>\n <td>female</td>\n <td>26.0</td>\n <td>0</td>\n <td>0</td>\n <td>STON/O2. 3101282</td>\n <td>7.9250</td>\n <td>NaN</td>\n <td>S</td>\n </tr>\n <tr>\n <th>3</th>\n <td>4</td>\n <td>1</td>\n <td>1</td>\n <td>Futrelle, Mrs. Jacques Heath (Lily May Peel)</td>\n <td>female</td>\n <td>35.0</td>\n <td>1</td>\n <td>0</td>\n <td>113803</td>\n <td>53.1000</td>\n <td>C123</td>\n <td>S</td>\n </tr>\n <tr>\n <th>4</th>\n <td>5</td>\n <td>0</td>\n <td>3</td>\n <td>Allen, Mr. William Henry</td>\n <td>male</td>\n <td>35.0</td>\n <td>0</td>\n <td>0</td>\n <td>373450</td>\n <td>8.0500</td>\n <td>NaN</td>\n <td>S</td>\n </tr>\n </tbody>\n</table>\n</div>\n\n``` python\ncount_values(df, 'Sex')\n```\n\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>Sex</th>\n <th>count</th>\n <th>percentual</th>\n <th>cumulative_percentual</th>\n </tr>\n </thead>\n <tbody>\n <tr>\n <th>0</th>\n <td>female</td>\n <td>314</td>\n <td>0.352413</td>\n <td>0.352413</td>\n </tr>\n <tr>\n <th>1</th>\n <td>male</td>\n <td>577</td>\n <td>0.647587</td>\n <td>1.000000</td>\n </tr>\n </tbody>\n</table>\n</div>\n",
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