格式化大 pandas 数据框中的整数的千位分隔符 [英] Formatting thousand separator for integers in a pandas dataframe

问题描述

我正尝试使用'{:,}'.format(number)像下面的示例一样在熊猫数据框中格式化数字:

I'm trying to use '{:,}'.format(number) like the example below to format a number in a pandas dataframe:

# This works for floats and integers
print '{:,}'.format(20000)
# 20,000
print '{:,}'.format(20000.0)
# 20,000.0

问题在于，具有整数的数据帧不起作用，而具有浮点数的数据帧可以正常工作.请参见示例:

The problem is that with a dataframe that has integers does not work, and in a dataframe with float works ok. See the examples:

# Does not work. The format stays the same, does not show thousands separator
df_int = DataFrame({"A": [20000, 10000]})
print df_int.to_html(float_format=lambda x: '{:,}'.format(x))

# Example of result
# <tr>
#   <th>0</th>
#   <td> 20000</td>
# </tr

# Works OK
df_float = DataFrame({"A": [20000.0, 10000.0]})
print df_float.to_html(float_format=lambda x: '{:,}'.format(x))

# Example of result
# <tr>
#   <th>0</th>
#   <td>20,000.0</td>
# </tr>

我做错了什么?

推荐答案

to_html中的formatters参数将采用映射到格式函数的列名字典.以下是构建dict的函数示例，该dict将相同的函数映射到float和int.

The formatters parameter in to_html will take a dictionary of column names mapped to a formatting function. Below has an example of a function to build a dict that maps the same function to both floats and ints.

In [250]: num_format = lambda x: '{:,}'.format(x)

In [246]: def build_formatters(df, format):
     ...:     return {column:format 
     ...:               for (column, dtype) in df.dtypes.iteritems()
     ...:               if dtype in [np.dtype('int64'), np.dtype('float64')]}
     ...: 

In [247]: formatters = build_formatters(df_int, num_format)


In [249]: print df_int.to_html(formatters=formatters)
<table border="1" class="dataframe">
  <thead>
    <tr style="text-align: right;">
      <th></th>
      <th>A</th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <th>0</th>
      <td>20,000</td>
    </tr>
    <tr>
      <th>1</th>
      <td>10,000</td>
    </tr>
  </tbody>
</table>

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