![]() ![]() Extra labels in the mapping don’t throw an error.If the new name mapping is not provided for some column label then it isn’t renamed.Set errors='ignore' to not throw any errors.Method 2: assigning list of new column names. Set errors='raised' to throws KeyError for the unknown columns In this mini tutorial, we will review four methods that will help you rename single or multiple-column names.If yes, then use the errors parameter of DataFrame.rename(). Print(student_df.columns.values) Raise error while renaming a columnīy default, The DataFrame.rename() doesn’t throw any error if column names you tried to rename doesn’t exist in the dataset.ĭo you want to throw an error in such cases? Use the following syntax code to rename the column. Use the column parameter of DataFrame.rename() function and pass the columns to be renamed. Sometimes it is required to rename the single or specific column names only. Also, It raises KeyError If any of the labels are not found in the selected axis when errors='raise'.It returns a DataFrame with the renamed column and row labels or None if inplace=True.If ‘ignore’, existing keys will be renamed and extra keys will be ignored. If ‘raise’, raise a KeyError if the columns or index are not present. errors: It is either ‘ignore’ or ‘raise’.Looking at renaming columns, lets see how the hidden copying mechanism leads. level: In the case of a multi-index DataFrame, only rename labels in the specified level. Pandas performance gets slowed down by copying going on underneath the hood.inplace: It is used to specify whether to return a new copy of a DataFrame or update existing ones.copy: It allows the copy of underlying data. ![]() ![]() Column axis represented as 1 or ‘columns‘. It is used to specify the axis to apply with the mapper. It takes to dictionary or function as input. columns: It is used to specify new names for columns.It takes a Python dictionary or function as input. mapper: It is used to specify new names for columns. How to rename the columns in DataFrame using Pandas In line 1, we use the rename() function and pass in the old column name and the new column name.Syntax: DataFrame.rename(mapper=None, columns=None, axis=None, copy=True, inplace=False, level=None, errors='ignore') Let’s see the syntax of it before moving to examples. ![]() This is the most widely used pandas function for renaming columns and row indexes.
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