格式化/抑制 Python Pandas 聚合结果的科学记数法
问题描述
如何修改 pandas 中的 groupby 操作的输出格式，该操作为非常大的数字生成科学记数法?
How can one modify the format for the output from a groupby operation in pandas that produces scientific notation for very large numbers?
我知道如何在 python 中进行字符串格式化，但是在这里应用它时我不知所措.
I know how to do string formatting in python but I'm at a loss when it comes to applying it here.
df1.groupby('dept')['data1'].sum()
dept
value1 1.192433e+08
value2 1.293066e+08
value3 1.077142e+08
如果我转换为字符串，这会抑制科学记数法，但现在我只是想知道如何格式化字符串和添加小数.
This suppresses the scientific notation if I convert to string but now I'm just wondering how to string format and add decimals.
sum_sales_dept.astype(str)
解决方案
当然，我在评论中链接的答案不是很有帮助.您可以像这样指定自己的字符串转换器.
Granted, the answer I linked in the comments is not very helpful. You can specify your own string converter like so.
In [25]: pd.set_option('display.float_format', lambda x: '%.3f' % x)
In [28]: Series(np.random.randn(3))*1000000000
Out[28]:
0 -757322420.605
1 -1436160588.997
2 -1235116117.064
dtype: float64
我不确定这是否是首选方法，但它确实有效.
I'm not sure if that's the preferred way to do this, but it works.
纯粹出于审美目的将数字转换为字符串似乎是个坏主意，但如果你有充分的理由，这是一种方法:
Converting numbers to strings purely for aesthetic purposes seems like a bad idea, but if you have a good reason, this is one way:
In [6]: Series(np.random.randn(3)).apply(lambda x: '%.3f' % x)
Out[6]:
0 0.026
1 -0.482
2 -0.694
dtype: object
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