Pandas: Data Manipulation - merge_ordered() function
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’, ‘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:
Download the Pandas DataFrame Notebooks from here.
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