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.droplevel() function return Index with requested level removed. If MultiIndex has only 2 levels, the result will be of Index type not MultiIndex..
Syntax: MultiIndex.droplevel(level=0)
Parameters :
level : int/level name or list thereofReturns : index : Index or MultiIndex
Example #1: Use MultiIndex.droplevel() function to drop the 0th level of the MultiIndex.
# importing pandas as pd import pandas as pd # Create the MultiIndex midx = pd.MultiIndex.from_arrays([['Networking', 'Cryptography', 'Anthropology', 'Science'], [88, 84, 98, 95]]) # Print the MultiIndex print(midx) |
Output :
Now let’s drop the 0th level of the MultiIndex.
# drop the 0th level. midx.droplevel(level = 0) |
Output :
As we can see in the output, the function has dropped the 0th level and returned an Index object.
Example #2: Use MultiIndex.droplevel() function to drop the 1st level of the MultiIndex.
# importing pandas as pd import pandas as pd # Create the MultiIndex midx = pd.MultiIndex.from_arrays([['Networking', 'Cryptography', 'Anthropology', 'Science'], [88, 84, 98, 95]]) # Print the MultiIndex print(midx) |
Output :
Now let’s drop the 1st level of the MultiIndex.
# drop the 1st level. midx.droplevel(level = 1) |
Output :
As we can see in the output, the function has dropped the 1st level and returned an Index object.
