Title: Apply Functions By Group In Pandas
Slug: pandas_apply_function_by_group
Summary: Apply Functions By Group In Pandas
Date: 2016-05-01 12:00
Category: Python
Tags: Data Wrangling
Authors: Chris Albon

Preliminaries



In [5]:

    
# import pandas as pd
import pandas as pd

Create a simulated dataset



In [6]:

    
# Create an example dataframe
data = {'Platoon': ['A','A','A','A','A','A','B','B','B','B','B','C','C','C','C','C'],
       'Casualties': [1,4,5,7,5,5,6,1,4,5,6,7,4,6,4,6]}
df = pd.DataFrame(data)
df

Apply A Function (Rolling Mean) To The DataFrame, By Group



In [7]:

    
# Group df by df.platoon, then apply a rolling mean lambda function to df.casualties
df.groupby('Platoon')['Casualties'].apply(lambda x:x.rolling(center=False,window=2).mean())









    Out[7]:





0     NaN
1     2.5
2     4.5
3     6.0
4     6.0
5     5.0
6     NaN
7     3.5
8     2.5
9     4.5
10    5.5
11    NaN
12    5.5
13    5.0
14    5.0
15    5.0
dtype: float64