I have files of the below format in a text file which I am trying to read into a pandas dataframe.
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 10 integers after the floating point in the input file.
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
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.
I figured out that I have to do something about dtype
but I am not sure where I should use it.
It is only display problem, see docs:
#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):
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 documentation for more.