问题描述

我正在尝试让 float_format 参数与 pandas 的 to_excel() 函数一起使用，但它似乎没有做任何事情.

代码:

df = pd.DataFrame({'日期':['1/15/2016','2/1/2016','2/15/2016','3/15/2016'],'numA':[1000,2000,3000,4000.3],'numB':[10000,20000.2,30000,40000]})writer = pd.ExcelWriter('c:/.../pandas_excel_test.xlsx', engine = 'xlsxwriter')打印 df.dtypesdf.to_excel(作家，指数=假，float_format = '%.2f',)

但是 Excel 文件看起来像这样:

我确认 dtypes 为:

日期对象numA float64numB float64数据类型:对象

有谁知道如何正确格式化 to_excel() 中的浮点数?

我相信 Excel 格式会改变浮点数的显示方式.我尝试了 to_csv 方法并且 float_format 工作.对于 excel，告诉 excel 如何显示列有帮助:

df = pd.DataFrame({'日期':['1/15/2016','2/1/2016','2/15/2016','3/15/2016'],'numA':[1000,2000,3000,4000.3],'numB':[10000,20000.2,30000,40000]})writer = pd.ExcelWriter('c:/.../pandas_excel_test.xlsx', engine = 'xlsxwriter')df.to_excel(writer, index=False, sheet_name='Sheet1')工作簿 = writer.book工作表 = writer.sheets['Sheet1']format1 = workbook.add_format({'num_format': '0.00'})worksheet.set_column('C:C', None, format1) # 将格式添加到 C 列writer.save()

结果:

更多信息:http://xlsxwriter.readthedocs.io/example_pandas_column_formats.htmlp>

I'm trying to get the float_format parameter working with pandas' to_excel() function, but it doesn't seem to do anything.

Code:

df = pd.DataFrame({
        'date':['1/15/2016','2/1/2016','2/15/2016','3/15/2016'],
        'numA':[1000,2000,3000,4000.3],
        'numB':[10000,20000.2,30000,40000]
    })

writer = pd.ExcelWriter('c:/.../pandas_excel_test.xlsx', engine = 'xlsxwriter')

print df.dtypes

df.to_excel(writer, 
        index = False,
        float_format = '%.2f',
    )

But the Excel file looks like this:

I confirmed dtypes as:

date     object
numA    float64
numB    float64
dtype: object

Does anyone know how to properly format floats in to_excel()?

I believe Excel formatting changes how floats are displayed. I tried to_csv method and float_format worked. For excel, telling excel how to display the column helps:

df = pd.DataFrame({
        'date':['1/15/2016','2/1/2016','2/15/2016','3/15/2016'],
        'numA':[1000,2000,3000,4000.3],
        'numB':[10000,20000.2,30000,40000]
    })

writer = pd.ExcelWriter('c:/.../pandas_excel_test.xlsx', engine = 'xlsxwriter')
df.to_excel(writer, index=False, sheet_name='Sheet1')
workbook  = writer.book
worksheet = writer.sheets['Sheet1']
format1 = workbook.add_format({'num_format': '0.00'})
worksheet.set_column('C:C', None, format1)  # Adds formatting to column C
writer.save()

Result:

More info: http://xlsxwriter.readthedocs.io/example_pandas_column_formats.html

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