概述
这篇文章主要介绍了Python 中pandas.read_excel详细介绍的相关资料,需要的朋友可以参考下
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.
最后给大家推荐一个资源很全的python学习聚集地,[点击进入],这里有我收集以前学习心得,学习笔记,还有一线企业的工作经验,且给大定on零基础到项目实战的资料,大家也可以在下方,留言,把不懂的提出来,大家一起学习进步
最后
以上就是甜美海燕为你收集整理的python基础教程:Python 中pandas.read_excel详细介绍的全部内容,希望文章能够帮你解决python基础教程:Python 中pandas.read_excel详细介绍所遇到的程序开发问题。
如果觉得靠谱客网站的内容还不错,欢迎将靠谱客网站推荐给程序员好友。
本图文内容来源于网友提供,作为学习参考使用,或来自网络收集整理,版权属于原作者所有。
发表评论 取消回复