pandas.DataFrame.join

DataFrame.join(other, on=None, how='left', lsuffix='', rsuffix='', sort=False)

Join columns with other DataFrame either on index or on a key column. Efficiently Join multiple DataFrame objects by index at once by passing a list.

Parameters:

other : DataFrame, Series with name field set, or list of DataFrame

Index should be similar to one of the columns in this one. If a Series is passed, its name attribute must be set, and that will be used as the column name in the resulting joined DataFrame

on : column name, tuple/list of column names, or array-like

Column(s) to use for joining, otherwise join on index. If multiples columns given, the passed DataFrame must have a MultiIndex. Can pass an array as the join key if not already contained in the calling DataFrame. Like an Excel VLOOKUP operation

how : {‘left’, ‘right’, ‘outer’, ‘inner’}

How to handle indexes of the two objects. Default: ‘left’ for joining on index, None otherwise

• left: use calling frame’s index
• right: use input frame’s index
• outer: form union of indexes
• inner: use intersection of indexes

lsuffix : string

Suffix to use from left frame’s overlapping columns

rsuffix : string

Suffix to use from right frame’s overlapping columns

sort : boolean, default False

Order result DataFrame lexicographically by the join key. If False, preserves the index order of the calling (left) DataFrame

Returns:

joined : DataFrame

Notes

on, lsuffix, and rsuffix options are not supported when passing a list of DataFrame objects