# 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