For example, if creating the dataframe required querying a snowflake database. I have often seen people fall into this case if creating the dataframe is an expensive task. Extra labels listed don’t throw an error. You can rename those columns with a dictionary where you can use dictionary keys and values to rename columns in a pandas DataFrame. Labels not contained in a dict / Series will be left as-is. Function / dict values must be unique (1-to-1). Not all the columns have to be renamed: df = df.rename(columns=, inplace=True)Īlternatively, there are cases where you want to preserve the original dataframe. DataFrame.rename (mapperNone, indexNone, columnsNone, axisNone, copyTrue, inplaceFalse, levelNone) source Alter axes labels. and Also explained how to rename series with lambda function, series.to_frame(), create multi-index labels with examples.Use the df.rename() function and refer the columns to be renamed. In this article, I have explained how to rename a pandas series using Series.rename() function. Ser2 = ser.rename("Courses", inplace=True) But again, it can also rename the row labels (i.e., the labels in the dataframe index). This technique is most often used to rename the columns of a dataframe (i.e., the variable names). # Use rename pandas series & inplace = true The Pandas rename method is fairly straight-forward: it enables you to rename the columns or rename the row labels of a Python dataframe. # Create the MultiIndex using series.rename() functionĨ. Use this function to rename the 1st level of the series. First, let’s apply the resetindex() function and save the resulting dataframe. In this method, we first apply the resetindex() function and then change the column name using the pandas dataframe rename() function. We can also use Series.rename() function to rename the multi-index axis of the given Series object. Rename the column after applying the resetindex() function. Using series.rename() Function to Create MultiIndex # Use series.rename() function to changes labelsħ. Pandas series.rename() function also used to rename multiple labels index values or all indexes of the pandas Series. ![]() The following example returns square index values from a series where values are changed in the labels index. We can also use Pandas series.rename() along with the lambda function. # Use series.to_frame() function to rename series We can also use series.to_frame() function to rename the pandas series. ![]() In line 4, we print the new DataFrame with a new column name. In the next section, youll see 2 examples of renaming: Single Column in Pandas DataFrame Multiple Columns in Pandas DataFrame. Use series.to_frame() Function to Rename Series In line 1, we use the rename() function and pass in the old column name and the new column name. Series.rename(index=None, *, axis=None, copy=True, inplace=False, level=None, errors='ignore')įollowing are the parameters of rename().ĥ. Ser2 = ser.rename(level = 1, index = 'Fee')įollowing is the syntax to create Series.rename() function. ![]() # Example 7: Create the MultiIndex using series.rename() function # Example 6: Use series.rename() function to changes labels # Example 5: Use series.rename() and lambda # Example 4: Use series.to_frame() function to rename series # Example 3: Use rename pandas series & inplace = true # Example 1: Use series.rename() function
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