import modules
<pre><code>import pandas as pd
import numpy as np</code></pre>
create dummy dataframe
<pre><code>raw_data = {'name': ['Willard Morris', 'Al Jennings', 'Omar Mullins', 'Spencer McDaniel'],
'age': [20, 20, 22, 21],
'favorite_color': ['blue', 'red', 'yellow', "green"],
'grade': [88, 92, 95, 70]}
df = pd.DataFrame(raw_data, index = ['Willard Morris', 'Al Jennings', 'Omar Mullins', 'Spencer McDaniel'])
df</code></pre>
<table>
<thead>
<tr>
<th></th>
<th>age</th>
<th>favorite_color</th>
<th>grade</th>
<th>name</th>
</tr>
</thead>
<tbody>
<tr>
<td>Willard Morris</td>
<td>20</td>
<td>blue</td>
<td>88</td>
<td>Willard Morris</td>
</tr>
<tr>
<td>Al Jennings</td>
<td>20</td>
<td>red</td>
<td>92</td>
<td>Al Jennings</td>
</tr>
<tr>
<td>Omar Mullins</td>
<td>22</td>
<td>yellow</td>
<td>95</td>
<td>Omar Mullins</td>
</tr>
<tr>
<td>Spencer McDaniel</td>
<td>21</td>
<td>green</td>
<td>70</td>
<td>Spencer McDaniel</td>
</tr>
</tbody>
</table>
return the frequency of each unique value in 'age' column in Pandas dataframe
<pre><code>df.groupby('age').size()</code></pre>
<pre><code> age 20 2 21 1 22 1 dtype: int64</code></pre>

A step-by-step Python code example that shows how to count the frequency a value occurs in Pandas DataFrame. Provided by Data Interview Questions, a mailing list for coding and data interview problems.

	age	favorite_color	grade	name
Willard Morris	20	blue	88	Willard Morris
Al Jennings	20	red	92	Al Jennings
Omar Mullins	22	yellow	95	Omar Mullins
Spencer McDaniel	21	green	70	Spencer McDaniel

Count the frequency a value occurs in Pandas dataframe