Python | Pandas dataframe.add_suffix()

Python is a great language for doing data analysis, primarily because of the fantastic ecosystem of data-centric python packages. Pandas is one of those packages and makes importing and analyzing data much easier.
Dataframe.add_suffix() function can be used with both series as well as dataframes. add_suffix() function Concatenate suffix string with panel items names.

  • For Series, the row labels are suffixed.
  • For DataFrame, the column labels are suffixed.
Syntax: DataFrame.add_suffix(suffix)

Parameters:
suffix : string

Returns:  with_suffix: type of caller

For link to CSV file Used in Code, click here

Example #1: Suffix _col in each columns in the dataframe.

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# importing pandas as pd
import pandas as pd
  
# Making data frame from the csv file
df = pd.read_csv("nba.csv")
  
# Printing the first 10 rows of
# the data frame for visualization
df[:10]

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# Using add_suffix() function to 
# add '_col' in each column label
df = df.add_suffix('_col')
  
# Print the dataframe
df 

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Output:



 

Example #2: Using add_suffix() with Series in pandas

add_suffix() alters the row index labels in the case of series.

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# importing pandas as pd
import pandas as pd
  
# Creating a Series 
df = pd.Series([1, 2, 3, 4, 5, 10, 11, 21, 4])
  
# This will suffix '_Row' in
# each row of the series
df = df.add_suffix('_Row')
  
# Print the Series
df

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Output:




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