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.rename_axis() is used to rename the axes of the index or columns in dataframe.
Syntax: DataFrame.rename_axis(mapper, axis=0, copy=True, inplace=False)
Parameters:
mapper : [scalar, list-like, optional] Value to set the axis name attribute.
axis : int or string, default 0
copy : [iboolean, default True] Also copy underlying data
inplace :boolean, default FalseReturns: renamed : type of caller or None if inplace=True
For link to CSV file Used in Code, click here
Example #1: Replace team “Boston Celtics” with “Omega Warrior” in the nba.csv file
# 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] |
Output:
We are going to change the row indexes and increase the value by twice.
# this will Increase the row index value by twice df.rename_axis(lambda x:x * 2, axis ="index") |
Output:
Example #2: Changing the column name
# importing pandas as pd import pandas as pd # Making data frame from the csv file df = pd.read_csv("nba.csv") # this will add '_X' at the end of each column name df.rename_axis(lambda x:x+"_X", axis ="columns") |
Output:
