Python 中pandas.read_excel详细介绍

yipeiwu_com5年前Python基础

Python 中pandas.read_excel详细介绍

#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指定为读取几个sheet,sheet数目从0开始
#如果sheetname=[0,2],那代表读取第0页和第2页的sheet
#skiprows=[0]代表读取跳过的行数第0行,不写代表不跳过标题
#df = pd.read_excel(filefullpath, sheetname=None ,skiprows=[0])

print df
print type(df)
#若果有多页,type(df)就为<type 'dict'>
#如果就一页,type(df)就为<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

参数解析:

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.

return返回的结果

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.

感谢阅读,希望能帮助到大家,谢谢大家对本站的支持!

相关文章

基于python脚本实现软件的注册功能(机器码+注册码机制)

一、前言: 目的:完成已有python图像处理工具的注册功能 功能:用户运行程序后,通过文件自动检测认证状态,如果未经认证,就需要注册。注册过程是用户将程序运行后显示的机器码(C盘的卷序...

Python机器学习算法库scikit-learn学习之决策树实现方法详解

Python机器学习算法库scikit-learn学习之决策树实现方法详解

本文实例讲述了Python机器学习算法库scikit-learn学习之决策树实现方法。分享给大家供大家参考,具体如下: 决策树 决策树(DTs)是一种用于分类和回归的非参数监督学习方法。...

Python中装饰器学习总结

本文研究的主要内容是Python中装饰器相关学习总结,具体如下。 装饰器(decorator)功能 引入日志 函数执行时间统计 执行函数前预备处理 执行函数后清理功能...

Python+tkinter使用40行代码实现计算器功能

Python+tkinter使用40行代码实现计算器功能

本文实例为大家分享了40行Python代码实现计算器功能,供大家参考,具体内容如下 偶尔用脚本写点东西也是不错的。 效果图 代码 from tkinter import *...

Django model序列化为json的方法示例

本文环境 Python 3.6.5 Django 2.0.4 fix(2018.5.19):最近得知Django 的model基类需要声明为abstract,故在原来的代码加...