pandas.core.groupby.DataFrameGroupBy.rank

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

Compute numerical data ranks (1 through n) along axis. Equal values are assigned a rank that is the average of the ranks of those values

Parameters:

axis : {0 or ‘index’, 1 or ‘columns’}, default 0

Ranks over columns (0) or rows (1)

numeric_only : boolean, default None

Include only float, int, boolean data

method : {‘average’, ‘min’, ‘max’, ‘first’, ‘dense’}

• average: average rank of group
• min: lowest rank in group
• max: highest rank in group
• first: ranks assigned in order they appear in the array
• dense: like ‘min’, but rank always increases by 1 between groups

na_option : {‘keep’, ‘top’, ‘bottom’}

• keep: leave NA values where they are
• top: smallest rank if ascending
• bottom: smallest rank if descending

ascending : boolean, default True

False for ranks by high (1) to low (N)

pct : boolean, default False

Computes percentage rank of data

Returns:

ranks : DataFrame