def sheet_asdict(fn, sheet=0, header=True, startcell=None, stopcell=None,
                 usecols=None, chnames_out=None):
    """Read data from a spread sheet. Return the data in a dict with
    column numbers as keys.

    fn: str
        The file to read from.

    sheet: int or str
        If int, it is the index for the sheet 0-based. Else the sheet
        name.

    header: bool or str
        True if the defined data range includes a header with field
        names. Else False - the whole range is data. If a string, it is
        a spread sheet style notation of the startcell for the header
        ("F9"). The "width" of this record is the same as for the data.


    startcell: str or None
        If given, a spread sheet style notation of the cell where reading
        start, ("F9").

    stopcell: str or None
        A spread sheet style notation of the cell where data end,
        ("F9").

    usecols: str or seqence of ints
        The columns to use, 0-based. 0 is the spread sheet column
        "A". Can be given as a string also - 'C:E, H' for columns C, D,
        E and H.

    usecols: str or sequence of ints or None
        The columns to use, 0-based. 0 is the spread sheet column
        "A". Can be given as a string also - 'C:E, H' for columns C, D,
        E and H.

    chnames_out: list or None
        If a list it will be populated with the channel names. The size
        of the list will equal to the number of channel names extracted.
        Whatever is in the list supplied will first be removed.

    Values in the returned dict are numpy arrays. Types are set based on
    the types in the spread sheet.
    """
    book = xlrd.open_workbook(fn)
    try:
        sh = book.sheet_by_index(sheet)
    except TypeError:
        sh = book.sheet_by_name(sheet)

    ss = prepread(sh, header=header, startcell=startcell, stopcell=stopcell)

    chnames = sheetheader(sh, ss, usecols=usecols)

    if chnames_out is not None and chnames is not None:
        vals = list(chnames_out)
        [chnames_out.remove(v) for v in vals]
        chnames_out.extend(chnames)

    return _sheet_asdict(sh, ss, usecols=usecols)
Read data from a spread sheet. Return the data in a dict with
    column numbers as keys.

    fn: str
        The file to read from.

    sheet: int or str
        If int, it is the index for the sheet 0-based. Else the sheet
        name.

    header: bool or str
        True if the defined data range includes a header with field
        names. Else False - the whole range is data. If a string, it is
        a spread sheet style notation of the startcell for the header
        ("F9"). The "width" of this record is the same as for the data.


    startcell: str or None
        If given, a spread sheet style notation of the cell where reading
        start, ("F9").

    stopcell: str or None
        A spread sheet style notation of the cell where data end,
        ("F9").

    usecols: str or seqence of ints
        The columns to use, 0-based. 0 is the spread sheet column
        "A". Can be given as a string also - 'C:E, H' for columns C, D,
        E and H.

    usecols: str or sequence of ints or None
        The columns to use, 0-based. 0 is the spread sheet column
        "A". Can be given as a string also - 'C:E, H' for columns C, D,
        E and H.

    chnames_out: list or None
        If a list it will be populated with the channel names. The size
        of the list will equal to the number of channel names extracted.
        Whatever is in the list supplied will first be removed.

    Values in the returned dict are numpy arrays. Types are set based on
    the types in the spread sheet.