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
Python3
Output :
Now let's construct the dataframe from the MultiIndex.
Python3
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
Python3
Output :
Now let's create a dataframe using the midx MultiIndex.
Python3
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.
# 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)
Now let's construct the dataframe from the MultiIndex.
# Construct the DataFrame
midx.to_frame(index = True)
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.
# 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)
Now let's create a dataframe using the midx MultiIndex.
# 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.
As we can see in the output, the function has returned a DataFrame having different index value.