Pandas DataFrame: rank() function

Last update on August 19 2022 21:50:33 (UTC/GMT +8 hours)

DataFrame - rank() function

The rank() function is used to compute numerical data ranks (1 through n) along axis.

By default, equal values are assigned a rank that is the average of the ranks of those values.

Syntax:

DataFrame.rank(self, axis=0, method='average', numeric_only=None, na_option='keep', ascending=True, pct=False)

Parameters:

Name	Description	Type/Default Value	Required / Optional
axis	Index to direct ranking.	{0 or ‘index’, 1 or ‘columns’} Default Value: 0	Required
method	How to rank the group of records that have the same value (i.e. ties): average: average rank of the group min: lowest rank in the group max: highest rank in the group first: ranks assigned in order they appear in the array dense: like ‘min’, but rank always increases by 1 between groups	{‘average’, ‘min’, ‘max’, ‘first’, ‘dense’} Default Value: ‘average’	Required
numeric_only	For DataFrame objects, rank only numeric columns if set to True.	bool	Optional
na_option	How to rank NaN values: keep: assign NaN rank to NaN values top: assign smallest rank to NaN values if ascending bottom: assign highest rank to NaN values if ascending	{‘keep’, ‘top’, ‘bottom’} Default Value: ‘keep’	Required
ascending	Whether or not the elements should be ranked in ascending order.	bool Default Value: True	Required
pct	Whether or not to display the returned rankings in percentile form.	bool Default Value: False	Required

Returns: same type as caller
Return a Series or DataFrame with data ranks as values.

Example:

Download the Pandas DataFrame Notebooks from here.

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