与 pandas 一起使用float64 to_csv [英] float64 with pandas to_csv

问题描述

我正在读取具有以下浮点数的CSV:

I'm reading a CSV with float numbers like this:

Bob,0.085
Alice,0.005

并导入数据框，然后将此数据框写入新位置

And import into a dataframe, and write this dataframe to a new place

df = pd.read_csv(orig)
df.to_csv(pandasfile)

现在，该pandasfile具有:

Bob,0.085000000000000006
Alice,0.0050000000000000001

会发生什么?也许我必须强制转换为float32之类的其他类型?

What happen? maybe I have to cast to a different type like float32 or something?

我正在使用 pandas 0.9.0 和 numpy 1.6.2 .

推荐答案

如注释中所述，这是一个通用的浮点问题.

As mentioned in the comments, it is a general floating point problem.

但是您可以使用to_csv的float_format关键字将其隐藏:

However you can use the float_format key word of to_csv to hide it:

df.to_csv('pandasfile.csv', float_format='%.3f')

或者，如果您不希望将0.0001舍入为零:

or, if you don't want 0.0001 to be rounded to zero:

df.to_csv('pandasfile.csv', float_format='%g')

会给您:

Bob,0.085
Alice,0.005

在您的输出文件中.

有关%g的说明，请参见最小格式规范-语言.

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