29 04 13 18 15 00 7.667
29 04 13 18 30 00 7.000
29 04 13 18 45 00 7.000
29 04 13 19 00 00 7.333
29 04 13 19 15 00 7.000
import pandas as pd
from cStringIO import StringIO
def parse_all_fields(day_col, month_col, year_col, hour_col, minute_col,second_col):
day_col = _maybe_cast(day_col)
month_col = _maybe_cast(month_col)
year_col = _maybe_cast(year_col)
hour_col = _maybe_cast(hour_col)
minute_col = _maybe_cast(minute_col)
second_col = _maybe_cast(second_col)
return lib.try_parse_datetime_components(day_col, month_col, year_col, hour_col, minute_col, second_col)
##Read the .txt file
data1 = pd.read_table('0132_3.TXT', sep='s+', names=['Day','Month','Year','Hour','Min','Sec','Value'])
data1[:10]
Out[21]:
Day,Month,Year,Hour, Min, Sec, Value
29 04 13 18 15 00 7.667
29 04 13 18 30 00 7.000
29 04 13 18 45 00 7.000
29 04 13 19 00 00 7.333
29 04 13 19 15 00 7.000
data2 = pd.read_table(StringIO(data1), parse_dates={'datetime':['Day','Month','Year','Hour''Min','Sec']}, date_parser=parse_all_fields, dayfirst=True)
TypeError Traceback (most recent call last)
<ipython-input-22-8ee408dc19c3> in <module>()
----> 1 data2 = pd.read_table(StringIO(data1), parse_dates={'datetime': ['Day','Month','Year','Hour''Min','Sec']}, date_parser=parse_all_fields, dayfirst=True)
TypeError: expected read buffer, DataFrame found
In [1]: df = pd.read_csv('0132_3.TXT', header=None, sep='s+s', parse_dates=[[0]])
In [2]: df
Out[2]:
0 1
0 2013-04-29 00:00:00 7.667
1 2013-04-29 00:00:00 7.000
2 2013-04-29 00:00:00 7.000
3 2013-04-29 00:00:00 7.333
4 2013-04-29 00:00:00 7.000
In [11]: def date_parser(ss):
day, month, year, hour, min, sec = ss.split()
return pd.Timestamp('20%s-%s-%s %s:%s:%s' % (year, month, day, hour, min, sec))
In [12]: df = pd.read_csv('0132_3.TXT', header=None, sep='s+s', parse_dates=[[0]], date_parser=date_parser)
In [13]: df
Out[13]:
0 1
0 2013-04-29 18:15:00 7.667
1 2013-04-29 18:30:00 7.000
2 2013-04-29 18:45:00 7.000
3 2013-04-29 19:00:00 7.333
4 2013-04-29 19:15:00 7.000
