float64 与 pandas to_csv [英] float64 with pandas to_csv

问题描述

我正在读取带有浮点数的 CSV 文件，如下所示:

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

Bob,0.085
Alice,0.005

并导入到一个数据帧中，并将这个数据帧写入一个新的地方

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

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

现在这个 pandasfile 有:

Bob,0.085000000000000006
Alice,0.0050000000000000001

发生了什么?也许我必须转换为不同的类型，如 float32 或其他类型?

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

我使用 pandas 0.9.0 和 numpy 1.6.2.

推荐答案

如评论中所述，是一般的浮点问题.

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

但是你可以使用to_csv的float_format关键字来隐藏它:

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，如果您不想将 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')

会给你:

Bob,0.085
Alice,0.005

在您的输出文件中.

有关 %g 的说明，请参阅 格式规范迷你语言.

For an explanation of %g, see Format Specification Mini-Language.

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