Python pandas. read_excel

pandas. read_excel in Python

#coding:utf-8
import pandas as pd
import numpy as np

filefullpath = r"/home/geeklee/temp/all_gov_file/pol_gov_mon/downloads/1.xls"
#filefullpath = r"/home/geeklee/temp/all_gov_file/pol_gov_mon/downloads/26368f3a-ea03-46b9-8033-73615ed07816.xls"
df = pd.read_excel(filefullpath,skiprows=[0])
#df = pd.read_excel(filefullpath, sheetname=[0,2],skiprows=[0])
#sheetname Specifies how many to read sheet . sheet The number from 0 start 
# if sheetname=[0,2] That's reading the number one 0 And the first page 2 page sheet
#skiprows=[0] Represents the number of rows skipped 0 Line, do not write means do not skip the title 
#df = pd.read_excel(filefullpath, sheetname=None ,skiprows=[0])

print df
print type(df)
# If it's multiple pages, type(df) for <type 'dict'>
# If it 1 Page, type(df) for <class 'pandas.core.frame.DataFrame'>
#{0:dataframe,1:dataframe,2:dataframe}

pandas.read_excel(io, sheetname=0, header=0, skiprows=None, skip_footer=0,
 index_col=None, names=None, parse_cols=None, parse_dates=False, date_parser=None,
 na_values=None, thousands=None, convert_float=True, has_index_names=None, converters=None,
 engine=None, squeeze=False, **kwds)

Read an Excel table into a pandas DataFrame

Parameter analysis:

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.

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 : list-like, default None

  List of additional strings to recognize as NA/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.

The result returned by return

parsed : DataFrame or Dict of DataFrames

  DataFrame from the passed in Excel file. See notes in sheetname argument for more information on when a Dict of Dataframes is returned.

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