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Module « pandas »

Fonction lreshape - module pandas

Signature de la fonction lreshape

def lreshape(data: 'DataFrame', groups: 'dict', dropna: 'bool' = True) -> 'DataFrame' 

Description

help(pandas.lreshape)

Reshape wide-format data to long. Generalized inverse of DataFrame.pivot.

Accepts a dictionary, ``groups``, in which each key is a new column name
and each value is a list of old column names that will be "melted" under
the new column name as part of the reshape.

Parameters
----------
data : DataFrame
    The wide-format DataFrame.
groups : dict
    {new_name : list_of_columns}.
dropna : bool, default True
    Do not include columns whose entries are all NaN.

Returns
-------
DataFrame
    Reshaped DataFrame.

See Also
--------
melt : Unpivot a DataFrame from wide to long format, optionally leaving
    identifiers set.
pivot : Create a spreadsheet-style pivot table as a DataFrame.
DataFrame.pivot : Pivot without aggregation that can handle
    non-numeric data.
DataFrame.pivot_table : Generalization of pivot that can handle
    duplicate values for one index/column pair.
DataFrame.unstack : Pivot based on the index values instead of a
    column.
wide_to_long : Wide panel to long format. Less flexible but more
    user-friendly than melt.

Examples
--------
>>> data = pd.DataFrame({'hr1': [514, 573], 'hr2': [545, 526],
...                      'team': ['Red Sox', 'Yankees'],
...                      'year1': [2007, 2007], 'year2': [2008, 2008]})
>>> data
   hr1  hr2     team  year1  year2
0  514  545  Red Sox   2007   2008
1  573  526  Yankees   2007   2008

>>> pd.lreshape(data, {'year': ['year1', 'year2'], 'hr': ['hr1', 'hr2']})
      team  year   hr
0  Red Sox  2007  514
1  Yankees  2007  573
2  Red Sox  2008  545
3  Yankees  2008  526

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