格式化/抑制 Python Pandas 聚合结果中的科学记数法 [英] Format / Suppress Scientific Notation from Python Pandas Aggregation Results

问题描述

如何修改 Pandas 中 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设置字符串格式并添加小数.

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)

推荐答案

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

我不确定这是否是执行此操作的首选方法，但它有效.

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一个坏主意，但如果您有充分的理由，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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