pandas.read_excel()

io : string, path object (pathlib.Path or py._path.local.LocalPath),

file-like object, pandas ExcelFile, or xlrd workbook. The string could be a URL. Valid URL schemes include http, ftp, s3, and file. For file URLs, a host is expected. For instance, a local file could be file://localhost/path/to/workbook.xlsx

sheetname : string, int, mixed list of strings/ints, or None, default 0

Strings are used for sheet names, Integers are used in zero-indexed sheet positions.

Lists of strings/integers are used to request multiple sheets.

Specify None to get all sheets.

str|int -> DataFrame is returned. list|None -> Dict of DataFrames is returned, with keys representing sheets.

Available Cases

• Defaults to 0 -> 1st sheet as a DataFrame
• 1 -> 2nd sheet as a DataFrame
• ?Sheet1? -> 1st sheet as a DataFrame
• [0,1,?Sheet5?] -> 1st, 2nd & 5th sheet as a dictionary of DataFrames
• None -> All sheets as a dictionary of DataFrames

header : int, list of ints, default 0

Row (0-indexed) to use for the column labels of the parsed DataFrame. If a list of integers is passed those row positions will be combined into a MultiIndex

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, list of ints, default None

Column (0-indexed) to use as the row labels of the DataFrame. Pass None if there is no such column. If a list is passed, those columns will be combined into a MultiIndex

names : array-like, default None

List of column names to use. If file contains no header row, then you should explicitly pass header=None

converters : dict, default None

Dict of functions for converting values in certain columns. Keys can either be integers or column labels, values are functions that take one input argument, the Excel cell content, and return the transformed content.

true_values : list, default None

Values to consider as True

false_values : list, default None

Values to consider as False

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?)

squeeze : boolean, default False

If the parsed data only contains one column then return a Series

na_values : scalar, str, list-like, or dict, default None

Additional strings to recognize as NA/NaN. If dict passed, specific per-column NA values. By default the following values are interpreted as NaN: ??, ?#N/A?, ?#N/A N/A?, ?#NA?, ?-1.#IND?, ?-1.#QNAN?, ?-NaN?, ?-nan?,

?1.#IND?, ?1.#QNAN?, ?N/A?, ?NA?, ?NULL?, ?NaN?, ?nan?.

thousands : str, default None

Thousands separator for parsing string columns to numeric. Note that this parameter is only necessary for columns stored as TEXT in Excel, any numeric columns will automatically be parsed, regardless of display format.

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

engine: string, default None

If io is not a buffer or path, this must be set to identify io. Acceptable values are None or xlrd

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 None

DEPRECATED: for version 0.17+ index names will be automatically inferred based on index_col. To read Excel output from 0.16.2 and prior that had saved index names, use True.