pandas.ExcelFile.parse

ExcelFile.parse(sheetname, header=0, skiprows=None, skip_footer=0, index_col=None, parse_cols=None, parse_dates=False, date_parser=None, na_values=None, thousands=None, chunksize=None, **kwds)

Read an Excel table into DataFrame

Parameters:

sheetname : string or integer

Name of Excel sheet or the page number of the sheet

header : int, default 0

Row to use for the column labels of the parsed DataFrame

skiprows : list-like

Rows to skip at the beginning (0-indexed)

skip_footer : int, default 0

Rows at the end to skip (0-indexed)

index_col : int, default None

Column to use as the row labels of the DataFrame. Pass None if there is no such column

parse_cols : int or list, default None

• If None then parse all columns
• If int then indicates last column to be parsed
• If list of ints then indicates list of column numbers to be parsed
• If string then indicates comma separated list of column names and column ranges (e.g. “A:E” or “A,C,E:F”)

na_values : list-like, default None

List of additional strings to recognize as NA/NaN

keep_default_na : bool, default True

If na_values are specified and keep_default_na is False the default NaN values are overridden, otherwise they’re appended to

verbose : boolean, default False

Indicate number of NA values placed in non-numeric columns

Returns:

parsed : DataFrame

DataFrame parsed from the Excel file