Python - Compute last of group values in a Pandas DataFrame

To compute last of group values, use the groupby.last() 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 last of group values and resetting index −

res = groupDF.last()
res = res.reset_index()

Example

Following is the complete code. The last occurrence of repeated values are displayed i.e. last of group values −

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.last()
res = res.reset_index()

print"\nLast of group values = \n",res

Output

This will produce the following output −

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

Last of group values =
      Car        Place   Units
0    BMW         Pune      50
1  Lexus   Chandigarh     110
2  Tesla       Mumbai      90