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Use the df.rename() function and refer the columns to be renamed. Not all the columns have to be renamed: df = df.rename(columns={'oldName1': 'newName1', 'oldName2': 'newName2'}) # Or rename the existing DataFrame (rather than creating a copy)
26 Ιουν 2024 · You can rename multiple columns in a Pandas DataFrame using a dictionary with old column names as keys and new column names as values passed to the rename() method. import pandas as pd # Example DataFrame df = pd.DataFrame({ 'A': [1, 2, 3], 'B': [4, 5, 6], 'C': [7, 8, 9] }) # Rename multiple columns df.rename(columns={'A': 'New_A', 'B': 'New_B ...
30 Ιουλ 2020 · Given a Pandas DataFrame, let’s see how to rename columns in Pandas with examples. Here, we will discuss 5 different ways to rename column names in Pandas DataFrame. Pandas Rename Column df.rename(columns={'old_column_name1': 'new_column_name1', 'old_column_name2': 'new_column_name2'}, inplace=True)Pandas Rename ColumnRename Column Pandas ...
5 Μαρ 2024 · Method 1: Rename Specific Columns Using rename() One of the most flexible methods to rename columns in a Pandas DataFrame is by using its rename() method, which allows for renaming specific columns via a dictionary argument. The keys are the old column names and the values are the new names.
3 Μαρ 2021 · To rename columns in a Pandas DataFrame, you have two options: using the rename () method or the columns attribute. The .rename () method allows you to pass in existing labels and the ones you want to use. The .columns attribute allows you to specify a list of values to use as column labels.
9 Μαρ 2023 · We can rename the DataFrame columns using DataFrame.add_prefix() and DataFrame.add_suffix() functions. It appends the input string as a prefix or suffix to the column names respectively. Note: These functions are only applicable to column labels and not row index of the DataFrame.
7 Αυγ 2023 · You can rename (change) column and/or index names in a pandas.DataFrame by using the rename(), add_prefix(), add_suffix(), set_axis() methods or by directly updating the columns and/or index attributes. Similarly, you can rename index names of a pandas.Series.
