在 Pandas 中使用 read_csv 时精度丢失
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Precision lost while using read_csv in pandas
提问by Krishna Sangeeth K S
I have files of the below format in a text file which I am trying to read into a pandas dataframe.
我在文本文件中有以下格式的文件，我试图将其读入Pandas数据帧。
895|2015-4-23|19|10000|LA|0.4677978806|0.4773469340|0.4089938425|0.8224291972|0.8652525793|0.6829942860|0.5139162227|
As you can see there are 10integers after the floating point in the input file.
如您所见，输入文件中浮点数后有10 个整数。
df = pd.read_csv('mockup.txt',header=None,delimiter='|')
When I try to read it into dataframe, I am not getting the last 4 integers
当我尝试将它读入数据帧时，我没有得到最后 4 个整数
df[5].head()
0 0.467798
1 0.258165
2 0.860384
3 0.803388
4 0.249820
Name: 5, dtype: float64
How can I get the complete precision as present in the input file? I have some matrix operations that needs to be performed so i cannot cast it as string.
如何获得输入文件中的完整精度？我有一些需要执行的矩阵运算，所以我不能将它转换为字符串。
I figured out that I have to do something about dtypebut I am not sure where I should use it.
我发现我必须做些什么，dtype但我不确定应该在哪里使用它。
回答by jezrael
It is only display problem, see docs:
这只是显示问题，请参阅文档：
#temporaly set display precision
with pd.option_context('display.precision', 10):
print df
0 1 2 3 4 5 6 7 \
0 895 2015-4-23 19 10000 LA 0.4677978806 0.477346934 0.4089938425
8 9 10 11 12
0 0.8224291972 0.8652525793 0.682994286 0.5139162227 NaN
EDIT: (Thank you Mark Dickinson):
编辑：（谢谢马克狄金森）：
Pandas uses a dedicated decimal-to-binary converter that sacrifices perfect accuracy for the sake of speed. Passing
float_precision='round_trip'to read_csv fixes this. See the documentationfor more.
Pandas 使用专用的十进制到二进制转换器，为了速度而牺牲了完美的准确性。传递
float_precision='round_trip'给 read_csv 解决了这个问题。有关更多信息，请参阅文档。
