Pandas: Data Manipulation - wide_to_long() function

Last update on August 19 2022 21:50:52 (UTC/GMT +8 hours)

wide_to_long() function

Wide panel to long format. Less flexible but more user-friendly than melt.
With stubnames [‘A’, ‘B’], this function expects to find one or more group of columns with format A-suffix1, A-suffix2,…, B-suffix1, B-suffix2,… You specify what you want to call this suffix in the resulting long format with j (for example j=’year’)
Each row of these wide variables are assumed to be uniquely identified by i (can be a single column name or a list of column names)
All remaining variables in the data frame are left intact.

Syntax:

pandas.wide_to_long(df, stubnames, i, j, sep='', suffix='\d+')

Parameters:

Name	Description	Type	Default Value	Required / Optional
df	The wide-format DataFrame	DataFrame		Required
stubnames	The stub name(s). The wide format variables are assumed to start with the stub names.	str or list-like		Required
i	Column(s) to use as id variable(s)	str or list-like		Required
j	The name of the sub-observation variable. What you wish to name your suffix in the long format.	str		Required
sep	A character indicating the separation of the variable names in the wide format, to be stripped from the names in the long format. For example, if your column names are A-suffix1, A-suffix2, you can strip the hyphen by specifying sep=’-‘	str	Default: “”	Required
suffix	A regular expression capturing the wanted suffixes. ‘\d+’ captures numeric suffixes. Suffixes with no numbers could be specified with the negated character class ‘\D+’. You can also further disambiguate suffixes, for example, if your wide variables are of the form A-one, B-two,.., and you have an unrelated column A-rating, you can ignore the last one by specifying suffix=’(!?	str	Default: ‘\d+’	Required

Returns:DataFrame - A DataFrame that contains each stub name as a variable, with new index (i, j).

Notes: All extra variables are left untouched. This simply uses pandas.melt under the hood, but is hard-coded to “do the right thing” in a typical case.

Example:

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