利用pands提取csv中的数据

前言

数据分析时候，需要将数据进行加载和存储，本文主要介绍和excel的交互。

从csv中提取n列数据写入到excl中

read_excel()

加载函数为read_excel(),其具体参数如下。

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,dtype=None, true_values=None, false_values=None, engine=None, squeeze=False, **kwds)

常用参数解析：

io : string, path object ; excel 路径。
sheetname : string, int, mixed list of strings/ints, or None, default 0 返回多表使用sheetname=[0,1],若sheetname=None是返回全表注意：int/string 返回的是dataframe，而none和list返回的是dict of dataframe
header : int, list of ints, default 0 指定列名行，默认0，即取第一行，数据为列名行以下的数据若数据不含列名，则设定 header = None
skiprows : list-like,Rows to skip at the beginning，省略指定行数的数据
skip_footer : int,default 0, 省略从尾部数的int行数据
index_col : int, list of ints, default None指定列为索引列，也可以使用u”strings”
names : array-like, default None, 指定列的名字。

to_excel()

存储函数为pd.DataFrame.to_excel()，注意，必须是DataFrame写入excel, 即Write DataFrame to an excel sheet。其具体参数如下：

to_excel(self, excel_writer, sheet_name='Sheet1', na_rep='', float_format=None,columns=None, header=True, index=True, index_label=None,startrow=0, startcol=0, engine=None, merge_cells=True, encoding=None,
inf_rep='inf', verbose=True, freeze_panes=None)

常用参数解析(这部分有部分英文解释，英语渣渣，先放着)
- excel_writer : string or ExcelWriter object File path or existing ExcelWriter目标路径
- sheet_name : string, default ‘Sheet1’ Name of sheet which will contain DataFrame,填充excel的第几页
- na_rep : string, default ”,Missing data representation 缺失值填充
- float_format : string, default None Format string for floating point numbers
- columns : sequence, optional，Columns to write 选择输出的的列。
- header : boolean or list of string, default True Write out column names. If a list of string is given it is assumed to be aliases for the column names
- index : boolean, default True，Write row names (index)
- index_label : string or sequence, default None， Column label for index column(s) if desired. If None is given, andheader and index are True, then the index names are used. A sequence should be given if the DataFrame uses MultiIndex.
- startrow :upper left cell row to dump data frame
- startcol :upper left cell column to dump data frame
- engine : string, default None ，write engine to use - you can also set this via the options，io.excel.xlsx.writer, io.excel.xls.writer, andio.excel.xlsm.writer.
- merge_cells : boolean, default True Write MultiIndex and Hierarchical Rows as merged cells.
- encoding: string, default None encoding of the resulting excel file. Only necessary for xlwt,other writers support unicode natively.
- inf_rep : string, default ‘inf’ Representation for infinity (there is no native representation for infinity in Excel)
- freeze_panes : tuple of integer (length 2), default None Specifies the one-based bottommost row and rightmost column that is to be frozen

实例

准备

1.vscode

2.csv文件内容

2代码

import pandas as pd
csv_name=r"D:\测试文件夹\test文件\test\csv数据提取\2020-4-22.csv"
#file=pd.read_csv(csv_name,encoding="ISO-8859-1") #读取csv文件
df1=pd.read_csv(csv_name,usecols=[1])
df2=pd.read_csv(csv_name,usecols=[5])
df3=pd.read_csv(csv_name,usecols=[6])
df4=pd.read_csv(csv_name,usecols=[7])
writer = pd.ExcelWriter(r"D:\测试文件夹\test文件\test\csv数据提取\提取结果\2020-4-22.xls")  # 定义一个向Excel写入数据的对象
df1.to_excel(writer,index=False)  # 向该Excel中写入df1到Data1这个sheet
df2.to_excel(writer,startcol=1,index=False)  # 向该Excel中写入df2到Data2这个sheet
df3.to_excel(writer,startcol=2,index=False)
df4.to_excel(writer,startcol=3,index=False)
writer.save()  # 保存Excel表格
writer.close()  # 关闭Excel表格