Python - Compute first of group values in a Pandas DataFrame

To compute first of group values, use the groupby.first() method. At first, import the required library with an alias −

import pandas as pd;

Create a DataFrame with 3 columns −

dataFrame = pd.DataFrame(    {       "Car": ['BMW', 'Lexus', 'BMW', 'Tesla', 'Lexus', 'Tesla'],"Place": ['Delhi','Bangalore','Pune','Punjab','Chandigarh','Mumbai'],"Units": [100, 150, 50, 80, 110, 90] } )

Now, group DataFrame by a column −

groupDF = dataFrame.groupby("Car") 

Compute first of group values and resetting index −

res = groupDF.first() res = res.reset_index()

Example

Following is the complete code −

 import pandas as pd; dataFrame = pd.DataFrame(    {       "Car": ['BMW', 'Lexus', 'BMW', 'Tesla', 'Lexus', 'Tesla'],"Place": ['Delhi','Bangalore','Pune','Punjab','Chandigarh','Mumbai'],"Units": [100, 150, 50, 80, 110, 90] } ) print("DataFrame ...\n",dataFrame) # grouping DataFrame by column Car groupDF = dataFrame.groupby("Car") res = groupDF.first() res = res.reset_index() print("\nFirst of group values = \n",res)

Output

This will produce the following output. The first occurrence of repeated values are displayed i.e. first of group values −

DataFrame ...      Car       Place   Units 0    BMW       Delhi     100 1  Lexus   Bangalore     150 2    BMW        Pune      50 3  Tesla      Punjab      80 4  Lexus  Chandigarh     110 5  Tesla      Mumbai      90 First of group values =      Car      Place Units 0    BMW      Delhi 100 1  Lexus  Bangalore 150 2  Tesla     Punjab 80