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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def _create_column(data, col, value):
 """ Create column in dataframe Helper method meant to deal with problematic column values. e.g When the series index does not match that of the data. Parameters data : pandas.DataFrame dataframe in which to insert value col : column label Column name value : object Value to assign to column Returns ------- data : pandas.DataFrame Modified original dataframe Data index and value index do not match x y 0 1 11 1 2 12 2 3 13 Non-empty dataframe, scalar value x y z 0 1 11 3 1 2 12 3 2 3 13 3 Empty dataframe, scalar value w 0 3 w z 0 3 abc """

    with suppress(AttributeError):
        # If the index of a series and the dataframe
        # in which the series will be assigned to a
        # column do not match, missing values/NaNs
        # are created. We do not want that.
        if not value.index.equals(data.index):
            if len(value) == len(data):
                value.index = data.index
            else:
                value.reset_index(drop=True, inplace=True)

    # You cannot assign a scalar value to a dataframe
    # without an index. You need an interable value.
    if data.index.empty:
        try:
            len(value)
        except TypeError:
            scalar = True
        else:
            scalar = isinstance(value, str)

        if scalar:
            value = [value]

    data[col] = value
    return data