Mic*_*ael 4 python excel pandas xlsxwriter
据我所知,Xlsxwriter 可能是使用千位分隔符格式化数字的最佳软件包。我已经阅读了很多次 xlsxwriter 文档,仍然很困惑,我认为其他人可能也有同样的问题,因此我在这里发布我的问题。我有一个 pandas 数据框 DF_T_1_EQUITY_CHANGE_Summary_ADE,我想将它们导出到 Excel 并使用格式化千位分隔符。
Row Labels object
Sum of EQUITY_CHANGE float64
Sum of TRUE_PROFIT float64
Sum of total_cost float64
Sum of FOREX VOL float64
Sum of BULLION VOL float64
Oil float64
Sum of CFD VOL object
Sum of BITCOIN VOL object
Sum of DEPOSIT float64
Sum of WITHDRAW float64
Sum of IN/OUT float64
dtype: object
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数据帧 DF_T_1_EQUITY_CHANGE_Summary_ADE 是明确的,除了第一列行标签是对象,其他都是数字。因此,我使用 xlsxwriter 将数据框写入 Excel:
import xlsxwriter
num_fmt = workbook.add_format({'num_format': '#,###'}) #set the separator I want
writer = pd.ExcelWriter('ADE_CN.xlsx', engine='xlsxwriter')
DF_T_1_EQUITY_CHANGE_Summary_ADE.to_excel(writer, sheet_name='Sheet1')
workbook=writer.book
worksheet = writer.sheets['Sheet1']
worksheet.set_column('C:M', None, num_fmt)
writer.save()
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但是,我没有得到千位分隔符,Excel中的结果如下:
Row Labels Sum of EQUITY_CHANGE Sum of TRUE_PROFIT Sum of total_cost Sum of FOREX VOL Sum of BULLION VOL Oil Sum of CFD VOL Sum of BITCOIN VOL Sum of DEPOSIT Sum of WITHDRAW Sum of IN/OUT
0 ADE A BOOK USD 778.17 517.36 375.9 37.79 0.33 0 0 0 1555.95 0 1555.95
1 ADE B BOOK USD 6525.51 403.01 529.65 35.43 14.3 0 0 0 500 -2712.48 -2212.48
2 ADE A BOOK AUD 537.7 189.63 147 12.25 0 0 0 0 0 0 0
3 ADE B BOOK AUD -22235.71 7363.14 224.18 2.69 9.16 0.2 0 0 5000 -103 4897
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有人可以提供解决方案吗,非常感谢。
它应该有效。在获得对工作簿对象的引用后,您需要add_format()稍后在代码中移动它。这是一个例子:
import pandas as pd
# Create a Pandas dataframe from some data.
df = pd.DataFrame({'Data': [1234.56, 234.56, 5678.92]})
# Create a Pandas Excel writer using XlsxWriter as the engine.
writer = pd.ExcelWriter('pandas.xlsx', engine='xlsxwriter')
# Convert the dataframe to an XlsxWriter Excel object.
df.to_excel(writer, sheet_name='Sheet1')
# Get the xlsxwriter workbook and worksheet objects.
workbook = writer.book
worksheet = writer.sheets['Sheet1']
# Set a currency number format for a column.
num_format = workbook.add_format({'num_format': '#,###'})
worksheet.set_column('B:B', None, num_format)
# Close the Pandas Excel writer and output the Excel file.
writer.save()
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