How to Groupby values count on the Pandas DataFrame

To Groupby value counts, use the groupby(), size() and unstack() methods of the Pandas DataFrame. At first, create a DataFrame with 3 columns −

dataFrame = pd.DataFrame({
   'Product Category': ['Computer', 'Mobile Phone', 'Electronics', 'Electronics', 'Computer', 'Mobile Phone'],'Product Name': ['Keyboard', 'Charger', 'SmartTV', 'Camera', 'Graphic Card', 'Earphone'],'Quantity': [10, 50, 10, 20, 25, 50]})

Now, groupby values count with groupby() method. For count, use the size() and unstack(). The unstack() gives a new level of column labels −

dataFrame = dataFrame.groupby(['Product Category', 'Product Name', 'Quantity']).size().unstack(fill_value=0)

Example

Following is the complete code −

import pandas as pd

# create a dataframe with 3 columns
dataFrame = pd.DataFrame({
   'Product Category': ['Computer', 'Mobile Phone', 'Electronics', 'Electronics', 'Computer', 'Mobile Phone'],'Product Name': ['Keyboard', 'Charger', 'SmartTV', 'Camera', 'Graphic Card', 'Earphone'],'Quantity': [10, 50, 10, 20, 25, 50]})

# dataframe
print"Dataframe...\n",dataFrame

# count and unstack
dataFrame = dataFrame.groupby(['Product Category', 'Product Name', 'Quantity']).size().unstack(fill_value=0)

print"\nResultant DataFrame...\n",dataFrame

Output

This will produce the following output −

Dataframe...
   Product Category   Product Name   Quantity
0         Computer       Keyboard         10
1     Mobile Phone        Charger         50
2      Electronics        SmartTV         10
3      Electronics         Camera         20
4         Computer   Graphic Card         25
5     Mobile Phone       Earphone         50

Resultant DataFrame...
Quantity                          10   20   25   50
Product Category   Product Name
Computer           Graphic Card   0    0    1    0
                   Keyboard       1    0    0    0
Electronics        Camera         0    1    0    0
                   SmartTV        1    0    0    0
Mobile Phone       Charger        0    0    0    1
                   Earphone       0    0    0    1