你能格式化 Pandas 整数来显示，比如用于浮点数的 `pd.options.display.float_format` 吗？
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Can you format pandas integers for display, like `pd.options.display.float_format` for floats?
提问by Michael K
I've seen thisand thison formatting floating-pointnumbers for display in pandas, but I'm interested in doing the same thing for integers.
我已经看到这个和这个关于格式化浮点数以在Pandas中显示，但我有兴趣对integers做同样的事情。
Right now, I have:
现在，我有：
pd.options.display.float_format = '{:,.2f}'.format
That works on the floats in my data, but will either leave annoying trailing zeroes on integers that are cast to floats, or I'll have plain integers that don't get formatted with commas.
这适用于我的数据中的浮点数，但要么会在转换为浮点数的整数上留下烦人的尾随零，要么我将使用未用逗号格式化的纯整数。
The pandas docs mention a SeriesFormatterclass about which I haven't been able to find any information.
pandas 文档提到了一个SeriesFormatter我无法找到任何信息的课程。
Alternatively, if there's a way to write a single string formatter that will format floats as '{:,.2f}'and floats with zero trailing decimal as '{:,d}', that'd work too.
或者，如果有一种方法可以编写一个单一的字符串格式化程序，将浮点数格式化为，'{:,.2f}'并将浮点数以零尾随十进制数设置为'{:,d}'，那也行。
采纳答案by unutbu
You could monkey-patch pandas.io.formats.format.IntArrayFormatter:
你可以猴子补丁pandas.io.formats.format.IntArrayFormatter：
import contextlib
import numpy as np
import pandas as pd
import pandas.io.formats.format as pf
np.random.seed(2015)
@contextlib.contextmanager
def custom_formatting():
orig_float_format = pd.options.display.float_format
orig_int_format = pf.IntArrayFormatter
pd.options.display.float_format = '{:0,.2f}'.format
class IntArrayFormatter(pf.GenericArrayFormatter):
def _format_strings(self):
formatter = self.formatter or '{:,d}'.format
fmt_values = [formatter(x) for x in self.values]
return fmt_values
pf.IntArrayFormatter = IntArrayFormatter
yield
pd.options.display.float_format = orig_float_format
pf.IntArrayFormatter = orig_int_format
df = pd.DataFrame(np.random.randint(10000, size=(5,3)), columns=list('ABC'))
df['D'] = np.random.random(df.shape[0])*10000
with custom_formatting():
print(df)
yields
产量
A B C D
0 2,658 2,828 4,540 8,961.77
1 9,506 2,734 9,805 2,221.86
2 3,765 4,152 4,583 2,011.82
3 5,244 5,395 7,485 8,656.08
4 9,107 6,033 5,998 2,942.53
while outside of the with-statement:
在 之外时with-statement：
print(df)
yields
产量
A B C D
0 2658 2828 4540 8961.765260
1 9506 2734 9805 2221.864779
2 3765 4152 4583 2011.823701
3 5244 5395 7485 8656.075610
4 9107 6033 5998 2942.530551
