(mat)
return pd.DataFrame(
        dict(('x%d' % i, mat[:, i]) for i in range(mat.shape[1])))
Sometimes (though not very often) it is useful to convert a numpy matrix
    which has no column names to a Pandas dataframe for use of the Pandas
    functions.  This method converts a 2D numpy matrix to Pandas dataframe
    with default column headers.

    Parameters
    ----------
    mat : The numpy matrix

    Returns
    -------
    A pandas dataframe with the same data as the input matrix but with columns
    named x0,  x1, ... x[n-1] for the number of columns.
Sometimes (though not very often) it is useful to convert a numpy matrix
    which has no column names to a Pandas dataframe for use of the Pandas
    functions.  This method converts a 2D numpy matrix to Pandas dataframe
    with default column headers.
Sometimes ( though not very often ) it is useful to convert a numpy matrix which has no column names to a Pandas dataframe for use of the Pandas functions . This method converts a 2D numpy matrix to Pandas dataframe with default column headers .
def numpymat2df(mat):
    """
    Sometimes (though not very often) it is useful to convert a numpy matrix
    which has no column names to a Pandas dataframe for use of the Pandas
    functions.  This method converts a 2D numpy matrix to Pandas dataframe
    with default column headers.

    Parameters
    ----------
    mat : The numpy matrix

    Returns
    -------
    A pandas dataframe with the same data as the input matrix but with columns
    named x0,  x1, ... x[n-1] for the number of columns.
    """
    return pd.DataFrame(
        dict(('x%d' % i, mat[:, i]) for i in range(mat.shape[1])))
def numpymat2df ( mat ) : return pd . DataFrame ( dict ( ( 'x%d' % i , mat [ : , i ] ) for i in range ( mat . shape [ 1 ] ) ) )