Python | Pandas MultiIndex.to_frame()

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. Pandas MultiIndex.to_frame() function create a DataFrame with the levels of the MultiIndex as columns.

Syntax: MultiIndex.to_frame(index=True) Parameters : index : Set the index of the returned DataFrame as the original MultiIndex. Returns : DataFrame : a DataFrame containing the original MultiIndex data.

Example #1: Use MultiIndex.to_frame() function to construct a dataframe using the MultiIndex levels as the column and index. Python3

# importing pandas as pd
import pandas as pd

# Create the MultiIndex
midx = pd.MultiIndex.from_tuples([(10, 'Ten'), (10, 'Twenty'), 
                                  (20, 'Ten'), (20, 'Twenty')], 
                                        names =['Num', 'Char'])

# Print the MultiIndex
print(midx)

Output : Now let's construct the dataframe from the MultiIndex. Python3

# Construct the DataFrame
midx.to_frame(index = True)

Output : As we can see in the output, the function has constructed the Dataframe using the MultiIndex. Notice the index of the dataframe is constructed using the levels of the MultiIndex.   Example #2: Use MultiIndex.to_frame() function to construct a DataFrame using the MultiIndex. Do not use the MultiIndex levels to construct the index of the Dataframe. Python3

# importing pandas as pd
import pandas as pd

# Create the MultiIndex
midx = pd.MultiIndex.from_tuples([(10, 'Ten'), (10, 'Twenty'),  
                                  (20, 'Ten'), (20, 'Twenty')], 
                                        names =['Num', 'Char'])

# Print the MultiIndex
print(midx)

Output : Now let's create a dataframe using the midx MultiIndex. Python3

# Create Dataframe with new index values.
midx.to_frame(index = False)

Output : As we can see in the output, the function has returned a DataFrame having different index value.