Python使用Pandas和XlsxWriter |S–2 _Pandas

先决条件： Python与pandas和xlsxwriter一起使用设置1
Python Pandas是一个数据分析库。它可以读取, 过滤和重新排列大小数据集, 并以包括Excel在内的多种格式输出它们。
大熊猫使用XlsxWriter模块写入Excel文件。
XlsxWriter是用于以XLSX文件格式写入文件的Python模块。它可以用于将文本, 数字和公式写入多个工作表。此外, 它还支持格式设置, 图像, 图表, 页面设置, 自动过滤器, 条件格式设置等功能。
代码1：使用Pandas和XlsxWriter将具有日期时间的Pandas数据帧转换为具有默认日期时间和日期格式的Excel文件。

# import pandas library as pd import pandas as pd# from datetime module import # datetime and date method from datetime import datetime, date# Create a Pandas dataframe from some datetime data. # datetime(year, month, date, hour, minute, second) # date(year, month, date) dataframe = pd.DataFrame({ 'Date and time' : [ datetime( 2018 , 1 , 11 , 11 , 30 , 55 ), datetime( 2018 , 2 , 12 , 1 , 20 , 33 ), datetime( 2018 , 3 , 13 , 11 , 10), datetime( 2018 , 4 , 14 , 16 , 45 , 35 ), datetime( 2018 , 5 , 15 , 12 , 10 , 15 )], 'Dates only' :[ date( 2018 , 6 , 21 ), date( 2018 , 7 , 22 ), date( 2018 , 8 , 23 ), date( 2018 , 9 , 24 ), date( 2018 , 10 , 25 ) ], })# Create a Pandas Excel writer # object using XlsxWriter as the engine. # Also set the default datetime and date formats.# mmmm dd yyyy => month date year # month - full name, date - 2 digit, year - 4 digit# mmm d yyyy hh:mm:ss => month date year hour: minute: second # month - first 3 letters , date - 1 or 2 digit , year - 4 digit. writer_object = pd.ExcelWriter( "Example_datetime.xlsx" , engine = 'xlsxwriter' , datetime_format = 'mmm d yyyy hh:mm:ss' , date_format = 'mmmm dd yyyy' )# Write a dataframe to the worksheet. dataframe.to_excel(writer_object, sheet_name = 'Sheet1' )# Create xlsxwriter worksheet object worksheet_object= writer_object.sheets[ 'Sheet1' ]# set width of the B and C column worksheet_object.set_column( 'B:C' , 20 )# Close the Pandas Excel writer # object and output the Excel file. writer_object.save()

输出：

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代码2：
使用Pandas和XlsxWriter将Pandas数据框转换为具有列格式的Excel文件。

# import pandas lib as pd import pandas as pd# Create a Pandas dataframe from some data. dataframe = pd.DataFrame( { 'Marks (Out of 50)' : [ 30 , 40 , 45 , 15 , 8 , 5 , 35 ], 'Percentage' : [. 6 , . 8 , . 9 , . 3 , . 16 , . 1 , . 7 ], })# Create a Pandas Excel writer # object using XlsxWriter as the engine. writer_object = pd.ExcelWriter( "Example_column.xlsx" , engine = 'xlsxwriter' )# Write a dataframe to the worksheet. dataframe.to_excel(writer_object, sheet_name = 'Sheet1' )# Create xlsxwriter workbook object . workbook_object = writer_object.book# Create xlsxwriter worksheet object worksheet_object = writer_object.sheets[ 'Sheet1' ]# Create a new Format object to formats cells # in worksheets using add_format() method .# number taken upto 2 decimal places # format object is create. format_object1 = workbook_object.add_format({ 'num_format' : '# 0.00' })# Integral percentage format object is create. format_object2 = workbook_object.add_format({ 'num_format' : '0 %' })# Note: It isn't possible to format # any cells that already have a format # such as the index or headers or any # cells that contain dates or datetimes.# Set the column width and format. worksheet_object.set_column( 'B:B' , 20 , format_object1)# Set the column width and format. worksheet_object.set_column( 'C:C' , 15 , format_object2)# Close the Pandas Excel writer # object and output the Excel file. writer_object.save()

输出：

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代码3：
使用Pandas和XlsxWriter将Pandas数据框转换为具有用户定义的标头格式的Excel文件。

# import pandas lib as pd import pandas as pddata1 = [ "Math" , "Physics" , "Computer" , "Hindi" , "English" , "chemistry" ] data2 = [ 95 , 78 , 80 , 80 , 60 , 95 ] data3 = [ 90 , 67 , 78 , 70 , 63 , 90 ]# Create a Pandas dataframe from some data. dataframe = pd.DataFrame( { 'Subject' : data1, 'Mid Term Exam Scores Out of 100' : data2, 'End Term Exam Scores Out of 100' : data3})# Create a Pandas Excel writer # object using XlsxWriter as the engine. writer_object = pd.ExcelWriter( "Example_header.xlsx" , engine = 'xlsxwriter' )# Write a dataframe to the worksheet. # we turn off the default header # and skip one row because we want # to insert a user defined header there. dataframe.to_excel(writer_object, sheet_name = 'Sheet1' , startrow = 1 , header = False )# Create xlsxwriter workbook object . workbook_object = writer_object.book# Create xlsxwriter worksheet object worksheet_object = writer_object.sheets[ 'Sheet1' ]# Create a new Format object to formats cells # in worksheets using add_format() method .# here we create a format object for header. header_format_object = workbook_object.add_format({ 'bold' : True , 'italic' : True , 'text_wrap' : True , 'valign' : 'top' , 'font_color' : 'red' , 'border' : 2 })# Write the column headers with the defined format. for col_number, value in enumerate (dataframe.columns.values): worksheet_object.write( 0 , col_number + 1 , value, header_format_object)# Close the Pandas Excel writer # object and output the Excel file. writer_object.save()

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