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.
这篇关于float64 与 pandas to_csv的文章就介绍到这了,希望我们推荐的答案对大家有所帮助,也希望大家多多支持!