Pandas: Data Manipulation - merge_ordered() function

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

merge_ordered() function

Perform merge with optional filling/interpolation designed for ordered data like time series data. Optionally perform group-wise merge.

Syntax:

pandas.merge_ordered(left, right, on=None, left_on=None, right_on=None, left_by=None, right_by=None, fill_method=None, suffixes=('_x', '_y'), how='outer')

Parameters:

Name	Description	Type	Default Value	Required / Optional
left		DataFrame		Required
right		DataFrame		Required
on	Field names to join on. Must be found in both DataFrames.	label or list		Required
left_on	Field names to join on in left DataFrame. Can be a vector or list of vectors of the length of the DataFrame to use a particular vector as the join key instead of columns.	label or list, or array-like		Optional
right_on	Field names to join on in right DataFrame or vector/list of vectors per left_on docs	label or list, or array-like		Optional
left_by	Group left DataFrame by group columns and merge piece by piece with right DataFrame	column name or list of column names		Optional
right_by	Group right DataFrame by group columns and merge piece by piece with left DataFrame.	column name or list of column names		Optional
fill_method	Interpolation method for data.	{‘ffill’, None}	Default: None	Optional
suffixes	A length-2 sequence where each element is optionally a string indicating the suffix to add to overlapping column names in left and right respectively. Pass a value of None instead of a string to indicate that the column name from left or right should be left as-is, with no suffix. At least one of the values must not be None.	Sequence	Default: (“_x”, “_y”)	Optional
how	left: use only keys from left frame (SQL: left outer join) right: use only keys from right frame (SQL: right outer join) outer: use union of keys from both frames (SQL: full outer join) inner: use intersection of keys from both frames (SQL: inner join)	{‘left’, ‘right’, ‘outer’, ‘inner’},	Default: ‘outer’	Optional

Returns: merged: The output type will the be same as ‘left’, if it is a subclass of DataFrame.

Example:

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