Formatting thousand separator for integers in a pandas dataframe

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自闭症患者 2021-02-15 16:16

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
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  • 2021-02-15 16:53

    You can always cast your table to float64 and then use float_format as you like, especially if you are constructing a small table for viewing purposes. Instead of dealing with ints and floats separately this gives a quick solution.

    df.astype('float64',errors='ignore').to_html(float_format=lambda x: format(x,',.2f'))

    errors='ignore' is there to prevent raising an exception when a column can not be converted to floats, like strings.

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  • 2021-02-15 16:57

    pandas (as of 0.20.1) does not allow overriding the default integer format in an easy way. It is hard coded in pandas.io.formats.format.IntArrayFormatter (the labmda function):

    class IntArrayFormatter(GenericArrayFormatter):
    
        def _format_strings(self):
            formatter = self.formatter or (lambda x: '% d' % x)
            fmt_values = [formatter(x) for x in self.values]
            return fmt_values
    

    I'm assuming is what you're actually asking for is how you can override the format for all integers: replace ("monkey patch") the IntArrayFormatter to print integer values with thousands separated by comma as follows:

    import pandas
    
    class _IntArrayFormatter(pandas.io.formats.format.GenericArrayFormatter):
    
        def _format_strings(self):
            formatter = self.formatter or (lambda x: ' {:,}'.format(x))
            fmt_values = [formatter(x) for x in self.values]
            return fmt_values
    
    pandas.io.formats.format.IntArrayFormatter = _IntArrayFormatter
    

    Note:

    • before 0.20.0, the formatters were in pandas.formats.format.
    • before 0.18.1, the formatters were in pandas.core.format.

    Aside

    For floats you do not need to jump through those hoops since there is a configuration option for it:

    display.float_format: The callable should accept a floating point number and return a string with the desired format of the number. This is used in some places like SeriesFormatter. See core.format.EngFormatter for an example.

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  • 2021-02-15 17:03

    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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