Module « pandas »

Fonction lreshape - module pandas

Signature de la fonction lreshape

def lreshape(data: 'DataFrame', groups, dropna: bool = True, label=None) -> 'DataFrame' 

Description

lreshape.__doc__

    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.
    label : None
        Not used.

        .. deprecated:: 1.0.0

    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