pandas.DataFrame.merge

Merge DataFrame or named Series objects with a database-style join.

The join is done on columns or indexes. If joining columns on columns, the DataFrame indexes will be ignored. Otherwise if joining indexes on indexes or indexes on a column or columns, the index will be passed on.

param right

DataFrame or named Series

Object to merge with.

param how

{‘left’, ‘right’, ‘outer’, ‘inner’}, default ‘inner’

Type of merge to be performed.

• left: use only keys from left frame, similar to a SQL left outer join;

  preserve key order.

• right: use only keys from right frame, similar to a SQL right outer join;

  preserve key order.

• outer: use union of keys from both frames, similar to a SQL full outer

  join; sort keys lexicographically.

• inner: use intersection of keys from both frames, similar to a SQL inner

  join; preserve the order of the left keys.

param on

label or list

Column or index level names to join on. These must be found in both DataFrames. If on is None and not merging on indexes then this defaults to the intersection of the columns in both DataFrames.

param left_on

label or list, or array-like

Column or index level names to join on in the left DataFrame. Can also be an array or list of arrays of the length of the left DataFrame. These arrays are treated as if they are columns.

param right_on

label or list, or array-like

Column or index level names to join on in the right DataFrame. Can also be an array or list of arrays of the length of the right DataFrame. These arrays are treated as if they are columns.

param left_index

bool, default False

Use the index from the left DataFrame as the join key(s). If it is a MultiIndex, the number of keys in the other DataFrame (either the index or a number of columns) must match the number of levels.

param right_index

bool, default False

Use the index from the right DataFrame as the join key. Same caveats as left_index.

param sort

bool, default False

Sort the join keys lexicographically in the result DataFrame. If False, the order of the join keys depends on the join type (how keyword).

param suffixes

tuple of (str, str), default (‘_x’, ‘_y’)

Suffix to apply to overlapping column names in the left and right side, respectively. To raise an exception on overlapping columns use (False, False).

param copy

bool, default True

If False, avoid copy if possible.

param indicator

bool or str, default False

If True, adds a column to output DataFrame called “_merge” with information on the source of each row. If string, column with information on source of each row will be added to output DataFrame, and column will be named value of string. Information column is Categorical-type and takes on a value of “left_only” for observations whose merge key only appears in ‘left’ DataFrame, “right_only” for observations whose merge key only appears in ‘right’ DataFrame, and “both” if the observation’s merge key is found in both.

param validate

str, optional

If specified, checks if merge is of specified type.

• “one_to_one” or “1:1”: check if merge keys are unique in both

  left and right datasets.

• “one_to_many” or “1:m”: check if merge keys are unique in left

  dataset.

• “many_to_one” or “m:1”: check if merge keys are unique in right

  dataset.

• “many_to_many” or “m:m”: allowed, but does not result in checks.

New in version 0.21.0.

return

DataFrame A DataFrame of the two merged objects.

Warning

This feature is currently unsupported by Intel Scalable Dataframe Compiler