Multi-index allows you to select more than one row and column in your index. It is a multi-level or hierarchical object for pandas object. Now there are various methods of multi-index that are used such as MultiIndex.from_arrays, MultiIndex.from_tuples, MultiIndex.from_product, MultiIndex.from_frame, etc which helps us to create multiple indexes from arrays, tuples, dataframes, etc.
Syntax : pandas.MultiIndex(levels=None, codes=None, sortorder=None, names=None, dtype=None, copy=False, name=None, verify_integrity=True)
levels : It is a sequence of arrays which shows the unique labels for each level.
codes : It is also a sequence of arrays where integers at each level helps us to designate the labels in that location.
sortorder : optional int. It helps us to sort the levels lexographically.
dtype : data-type(size of the data which can be of 32 bits or 64 bits)
copy : It is a boolean type parameter with default value as False. It helps us to copy the metadata.
verify_integrity : It is a boolean type parameter with default value as True. It checks the integrity of the levels and codes i.t if they are valid.
