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.
MultiIndex.sortlevel() function sort MultiIndex at the requested level. The result will respect the original ordering of the associated factor at that level.
Syntax: MultiIndex.sortlevel(level=0, ascending=True, sort_remaining=True)
level : [list-like, int or str, default 0] If a string is given, must be a name of the level If list-like must be names or ints of levels
ascending : False to sort in descending order Can also be a list to specify a directed ordering
sort_remaining : sort by the remaining levels after level.
sorted_index : Resulting index
indexer : Indices of output values in original index
Example #1: Use
MultiIndex.sortlevel() function to sort the 0th level of the MultiIndex in descending order.
Now let’s sort the 0th level of the MultiIndex in descending order.
As we can see in the output, the function has returned a new object having the 0th level sorted in descending order.
Example #2: Use
MultiIndex.sortlevel() function to sort the 1st level of the MultiIndex in the increasing order.
Now let’s sort the 1st level of the MultiIndex in increasing order.
As we can see in the output, the function has returned a new object having the first level sorted in increasing order.
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