pandas.io.excel.ExcelFile.parse

ExcelFile.parse(sheetname=0, 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, convert_float=True, has_index_names=False, converters=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)

converters : dict, default None

Dict of functions for converting values in certain columns. Keys can either be integers or column labels

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”)

parse_dates : boolean, default False

Parse date Excel values,

date_parser : function default None

Date parsing function

na_values : list-like, default None

List of additional strings to recognize as NA/NaN

thousands : str, default None

Thousands separator

chunksize : int, default None

Size of file chunk to read for lazy evaluation.

convert_float : boolean, default True

convert integral floats to int (i.e., 1.0 –> 1). If False, all numeric data will be read in as floats: Excel stores all numbers as floats internally.

has_index_names : boolean, default False

True if the cols defined in index_col have an index name and are not in the header

Returns :

parsed : DataFrame

DataFrame parsed from the Excel file