带有 Pandas 数据框千位分隔符的 XlsxWriter答案

【问题标题】：XlsxWriter with Pandas dataframe thousand separator带有 Pandas 数据框千位分隔符的 XlsxWriter
【发布时间】：2020-01-21 10:08:22
【问题描述】：

据我所知，Xlsxwriter 可能是用千位分隔符格式化我的数字的最佳软件包。我已经多次阅读 xlsxwriter 文档，仍然很困惑，我认为其他人可能有同样的问题，因此我在这里发布我的问题。我有一个熊猫数据框 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

数据框 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。所以，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()

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

谁能提供解决方案，不胜感激。

【问题讨论】：

在您的代码中，您要么在定义之前调用workbook，要么在调用workbook=writer.book 时重新定义。无论哪种方式，您都失去了添加的数字格式。
你能给我一个代码示例，我该如何编写它；我还是很困惑

标签： python excel pandas xlsxwriter

【解决方案1】：

它应该工作。在获得对工作簿对象的引用后，您需要稍后在代码中移动 add_format()。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()

输出：

【讨论】：