Python | Pandas dataframe.add_prefix()
Last Updated : 16 Nov, 2018
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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. Python3 1== 
Python3 1== 
Example #2: Using Python3 1== 
Dataframe.add_prefix()function can be used with both series as well as dataframes.- For Series, the row labels are prefixed.
- For DataFrame, the column labels are prefixed.
Syntax: DataFrame.add_prefix(prefix) Parameters: prefix : string Returns: with_prefix: type of callerFor link to CSV file Used in Code, click here Example #1: Prefix
col_in each columns in the dataframe# 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
# dataframe for visualization
df[:10]
# Using add_prefix() function
# to add 'col_' in each column label
df = df.add_prefix('col_')
# Print the dataframe
df
add_prefix() with Series in pandas add_prefix() alters the row index labels in the case of series.# 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 prefix 'Row_' in
# each row of the series
df = df.add_prefix('Row_')
# Print the Series
df
