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 drop the 0th level of the MultiIndex.
Python3
Output :
As we can see in the output, the function has dropped the 0th level and returned an Index object.
Example #2: Use
Python3
Output :
Now let's drop the 1st level of the MultiIndex.
Python3
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 thereof Returns : index : Index or MultiIndexExample #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)
Now let's drop the 0th level of the MultiIndex.
# drop the 0th level.
midx.droplevel(level = 0)
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)
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.
As we can see in the output, the function has dropped the 1st level and returned an Index object.