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.
# 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] |
# Using add_suffix() function to # add '_col' in each column label df = df.add_suffix('_col')   # Print the dataframe df |
Output:
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Example #2: Using add_suffix() with Series in pandas
add_suffix() 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 suffix '_Row' in # each row of the series df = df.add_suffix('_Row')   # Print the Series df |
Output:
