shibashib...@gmail.com wrote:
> Hello
>>
>> I'm very new in python. I have a file in the format:
>>
>> 2018-05-31 16:00:00 28.90 81.77 4.3
>> 2018-05-31 20:32:00 28.17 84.89 4.1
>> 2018-06-20 04:09:00 27.36 88.01 4.8
>> 2018-06-20 04:15:00 27.31 87.09 4.7
>> 2018-06-28 04.07:00 27.87 84.91 5.0
>> 2018-06-29 00.42:00 32.20 104.61 4.8
>
> I would like to read this file in python column-wise.
>
> I tried this way but not working ....
> event_list = open('seismicity_R023E.txt',"r")
> info_event = read(event_list,'%s %s %f %f %f %f\n');
There is actually a library that implements a C-like scanf. You can install
it with
$ pip install scanf
After that:
$ cat read_table.py
from scanf import scanf
with open("seismicity_R023E.txt") as f:
for line in f:
print(
scanf("%s %s %f %f %f\n", line)
)
$ cat seismicity_R023E.txt
2018-05-31 16:00:00 28.90 81.77 4.3
2018-05-31 20:32:00 28.17 84.89 4.1
2018-06-20 04:09:00 27.36 88.01 4.8
2018-06-20 04:15:00 27.31 87.09 4.7
2018-06-28 04.07:00 27.87 84.91 5.0
2018-06-29 00.42:00 32.20 104.61 4.8
$ python read_table.py
('2018-05-31', '16:00:00', 28.9, 81.77, 4.3)
('2018-05-31', '20:32:00', 28.17, 84.89, 4.1)
('2018-06-20', '04:09:00', 27.36, 88.01, 4.8)
('2018-06-20', '04:15:00', 27.31, 87.09, 4.7)
('2018-06-28', '04.07:00', 27.87, 84.91, 5.0)
('2018-06-29', '00.42:00', 32.2, 104.61, 4.8)
$
However, in the long term you may be better off with a tool like pandas:
>>> import pandas
>>> pandas.read_table(
... "seismicity_R023E.txt", sep=r"\s+",
... names=["date", "time", "foo", "bar", "baz"],
... parse_dates=[["date", "time"]]
... )
date_time foo bar baz
0 2018-05-31 16:00:00 28.90 81.77 4.3
1 2018-05-31 20:32:00 28.17 84.89 4.1
2 2018-06-20 04:09:00 27.36 88.01 4.8
3 2018-06-20 04:15:00 27.31 87.09 4.7
4 2018-06-28 04:00:00 27.87 84.91 5.0
5 2018-06-29 00:00:00 32.20 104.61 4.8
[6 rows x 4 columns]
>>>
It will be harder in the beginning, but if you work with tabular data
regularly it will pay off.
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