如何使用列的格式字符串显示浮点数的 Pandas DataFrame? [英] How to display pandas DataFrame of floats using a format string for columns?

问题描述

我想使用 print() 和 IPython display() 显示具有给定格式的 Pandas 数据帧.例如:

I would like to display a pandas dataframe with a given format using print() and the IPython display(). For example:

df = pd.DataFrame([123.4567, 234.5678, 345.6789, 456.7890],
                  index=['foo','bar','baz','quux'],
                  columns=['cost'])
print df

         cost
foo   123.4567
bar   234.5678
baz   345.6789
quux  456.7890

我想以某种方式将其强制打印

I would like to somehow coerce this into printing

         cost
foo   $123.46
bar   $234.57
baz   $345.68
quux  $456.79

无需修改数据本身或创建副本，只需更改其显示方式即可.

without having to modify the data itself or create a copy, just change the way it is displayed.

我该怎么做?

推荐答案

import pandas as pd
pd.options.display.float_format = '${:,.2f}'.format
df = pd.DataFrame([123.4567, 234.5678, 345.6789, 456.7890],
                  index=['foo','bar','baz','quux'],
                  columns=['cost'])
print(df)

收益

        cost
foo  $123.46
bar  $234.57
baz  $345.68
quux $456.79

但这仅适用于每个浮点数都使用美元符号进行格式化的情况.

but this only works if you want every float to be formatted with a dollar sign.

否则，如果您只想为某些浮点数设置美元格式，那么我认为您必须预先修改数据框(将这些浮点数转换为字符串):

Otherwise, if you want dollar formatting for some floats only, then I think you'll have to pre-modify the dataframe (converting those floats to strings):

import pandas as pd
df = pd.DataFrame([123.4567, 234.5678, 345.6789, 456.7890],
                  index=['foo','bar','baz','quux'],
                  columns=['cost'])
df['foo'] = df['cost']
df['cost'] = df['cost'].map('${:,.2f}'.format)
print(df)

收益

         cost       foo
foo   $123.46  123.4567
bar   $234.57  234.5678
baz   $345.68  345.6789
quux  $456.79  456.7890

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