How to encode time in the range of 1 to 48
-1
I have following time format with time interval of half hour in 24 HOUR, i.e 48 intervals in a day.
And I want to encode it in following format.
python-3.x pandas datetime time-series
asked Nov 24 '18 at 6:37
Nikhil MangireNikhil Mangire
659
add a comment |
-1
I have following time format with time interval of half hour in 24 HOUR, i.e 48 intervals in a day.
And I want to encode it in following format.
python-3.x pandas datetime time-series
asked Nov 24 '18 at 6:37
Nikhil MangireNikhil Mangire
659
add a comment |
-1
-1
-1
I have following time format with time interval of half hour in 24 HOUR, i.e 48 intervals in a day.
And I want to encode it in following format.
python-3.x pandas datetime time-series
asked Nov 24 '18 at 6:37
Nikhil MangireNikhil Mangire
659
I have following time format with time interval of half hour in 24 HOUR, i.e 48 intervals in a day.
And I want to encode it in following format.
python-3.x pandas datetime time-series
python-3.x pandas datetime time-series
asked Nov 24 '18 at 6:37
Nikhil MangireNikhil Mangire
659
asked Nov 24 '18 at 6:37
Nikhil MangireNikhil Mangire
659
asked Nov 24 '18 at 6:37
Nikhil MangireNikhil Mangire
659
asked Nov 24 '18 at 6:37
Nikhil MangireNikhil Mangire
659
asked Nov 24 '18 at 6:37
Nikhil MangireNikhil Mangire
659
659
add a comment |
add a comment |
1 Answer
1
active
oldest
votes
1
I believe you need map by dictionary created by timedelta_range and zip, for same types of data is necessary convert column to_timedelta:
df = pd.DataFrame({'Time':['00:00:00','00:30:00','01:00:00','08:00:00']})
print (type(df['Time'].iat[0]))
<class 'str'>
d = dict(zip(pd.timedelta_range('00:00:00', '23:30:00', freq='30T'), range(1, 49)))
df['EncodedTime'] = pd.to_timedelta(df['Time']).map(d)
print (df)
Time EncodedTime
0 00:00:00 1
1 00:30:00 2
2 01:00:00 3
3 08:00:00 17
Similar solution created by date_range with DatetimeIndex.strftime:
d = dict(zip(pd.date_range('00:00:00', '23:30:00', freq='30T').strftime('%H:%M:%S'),
range(1, 49)))
df['EncodedTime'] = df['Time'].map(d)
Solution working with times:
df = pd.DataFrame({'Time':pd.to_datetime(['00:00:00','00:30:00','01:00:00','08:00:00']).time})
print (type(df['Time'].iat[0]))
<class 'datetime.time'>
d = dict(zip(pd.date_range('00:00:00', '23:30:00', freq='30T').time, range(1, 49)))
df['EncodedTime'] = df['Time'].map(d)
answered Nov 24 '18 at 6:40
jezraeljezrael
340k25294365
your code only numbers from 1 to ~ , it doesn't encode from 1 to 48.
– Nikhil Mangire
Nov 24 '18 at 6:45
@NikhilMangire - OK, so check another solution.
– jezrael
Nov 24 '18 at 6:47
@NikhilMangire - Added next 2 solutions, it still some problem, what returnprint (type(df['Time'].iat[0]))?
– jezrael
Nov 24 '18 at 7:00
add a comment |
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1 Answer
1
active
oldest
votes
1 Answer
1
active
oldest
votes
active
oldest
votes
active
oldest
votes
1
I believe you need map by dictionary created by timedelta_range and zip, for same types of data is necessary convert column to_timedelta:
df = pd.DataFrame({'Time':['00:00:00','00:30:00','01:00:00','08:00:00']})
print (type(df['Time'].iat[0]))
<class 'str'>
d = dict(zip(pd.timedelta_range('00:00:00', '23:30:00', freq='30T'), range(1, 49)))
df['EncodedTime'] = pd.to_timedelta(df['Time']).map(d)
print (df)
Time EncodedTime
0 00:00:00 1
1 00:30:00 2
2 01:00:00 3
3 08:00:00 17
Similar solution created by date_range with DatetimeIndex.strftime:
d = dict(zip(pd.date_range('00:00:00', '23:30:00', freq='30T').strftime('%H:%M:%S'),
range(1, 49)))
df['EncodedTime'] = df['Time'].map(d)
Solution working with times:
df = pd.DataFrame({'Time':pd.to_datetime(['00:00:00','00:30:00','01:00:00','08:00:00']).time})
print (type(df['Time'].iat[0]))
<class 'datetime.time'>
d = dict(zip(pd.date_range('00:00:00', '23:30:00', freq='30T').time, range(1, 49)))
df['EncodedTime'] = df['Time'].map(d)
answered Nov 24 '18 at 6:40
jezraeljezrael
340k25294365
your code only numbers from 1 to ~ , it doesn't encode from 1 to 48.
– Nikhil Mangire
Nov 24 '18 at 6:45
@NikhilMangire - OK, so check another solution.
– jezrael
Nov 24 '18 at 6:47
@NikhilMangire - Added next 2 solutions, it still some problem, what returnprint (type(df['Time'].iat[0]))?
– jezrael
Nov 24 '18 at 7:00
add a comment |
1
I believe you need map by dictionary created by timedelta_range and zip, for same types of data is necessary convert column to_timedelta:
df = pd.DataFrame({'Time':['00:00:00','00:30:00','01:00:00','08:00:00']})
print (type(df['Time'].iat[0]))
<class 'str'>
d = dict(zip(pd.timedelta_range('00:00:00', '23:30:00', freq='30T'), range(1, 49)))
df['EncodedTime'] = pd.to_timedelta(df['Time']).map(d)
print (df)
Time EncodedTime
0 00:00:00 1
1 00:30:00 2
2 01:00:00 3
3 08:00:00 17
Similar solution created by date_range with DatetimeIndex.strftime:
d = dict(zip(pd.date_range('00:00:00', '23:30:00', freq='30T').strftime('%H:%M:%S'),
range(1, 49)))
df['EncodedTime'] = df['Time'].map(d)
Solution working with times:
df = pd.DataFrame({'Time':pd.to_datetime(['00:00:00','00:30:00','01:00:00','08:00:00']).time})
print (type(df['Time'].iat[0]))
<class 'datetime.time'>
d = dict(zip(pd.date_range('00:00:00', '23:30:00', freq='30T').time, range(1, 49)))
df['EncodedTime'] = df['Time'].map(d)
answered Nov 24 '18 at 6:40
jezraeljezrael
340k25294365
your code only numbers from 1 to ~ , it doesn't encode from 1 to 48.
– Nikhil Mangire
Nov 24 '18 at 6:45
@NikhilMangire - OK, so check another solution.
– jezrael
Nov 24 '18 at 6:47
@NikhilMangire - Added next 2 solutions, it still some problem, what returnprint (type(df['Time'].iat[0]))?
– jezrael
Nov 24 '18 at 7:00
add a comment |
1
1
1
I believe you need map by dictionary created by timedelta_range and zip, for same types of data is necessary convert column to_timedelta:
df = pd.DataFrame({'Time':['00:00:00','00:30:00','01:00:00','08:00:00']})
print (type(df['Time'].iat[0]))
<class 'str'>
d = dict(zip(pd.timedelta_range('00:00:00', '23:30:00', freq='30T'), range(1, 49)))
df['EncodedTime'] = pd.to_timedelta(df['Time']).map(d)
print (df)
Time EncodedTime
0 00:00:00 1
1 00:30:00 2
2 01:00:00 3
3 08:00:00 17
Similar solution created by date_range with DatetimeIndex.strftime:
d = dict(zip(pd.date_range('00:00:00', '23:30:00', freq='30T').strftime('%H:%M:%S'),
range(1, 49)))
df['EncodedTime'] = df['Time'].map(d)
Solution working with times:
df = pd.DataFrame({'Time':pd.to_datetime(['00:00:00','00:30:00','01:00:00','08:00:00']).time})
print (type(df['Time'].iat[0]))
<class 'datetime.time'>
d = dict(zip(pd.date_range('00:00:00', '23:30:00', freq='30T').time, range(1, 49)))
df['EncodedTime'] = df['Time'].map(d)
answered Nov 24 '18 at 6:40
jezraeljezrael
340k25294365
I believe you need map by dictionary created by timedelta_range and zip, for same types of data is necessary convert column to_timedelta:
df = pd.DataFrame({'Time':['00:00:00','00:30:00','01:00:00','08:00:00']})
print (type(df['Time'].iat[0]))
<class 'str'>
d = dict(zip(pd.timedelta_range('00:00:00', '23:30:00', freq='30T'), range(1, 49)))
df['EncodedTime'] = pd.to_timedelta(df['Time']).map(d)
print (df)
Time EncodedTime
0 00:00:00 1
1 00:30:00 2
2 01:00:00 3
3 08:00:00 17
Similar solution created by date_range with DatetimeIndex.strftime:
d = dict(zip(pd.date_range('00:00:00', '23:30:00', freq='30T').strftime('%H:%M:%S'),
range(1, 49)))
df['EncodedTime'] = df['Time'].map(d)
Solution working with times:
df = pd.DataFrame({'Time':pd.to_datetime(['00:00:00','00:30:00','01:00:00','08:00:00']).time})
print (type(df['Time'].iat[0]))
<class 'datetime.time'>
d = dict(zip(pd.date_range('00:00:00', '23:30:00', freq='30T').time, range(1, 49)))
df['EncodedTime'] = df['Time'].map(d)
answered Nov 24 '18 at 6:40
jezraeljezrael
340k25294365
edited Nov 24 '18 at 6:56
answered Nov 24 '18 at 6:40
jezraeljezrael
340k25294365
answered Nov 24 '18 at 6:40
jezraeljezrael
340k25294365
answered Nov 24 '18 at 6:40
jezraeljezrael
340k25294365
340k25294365
your code only numbers from 1 to ~ , it doesn't encode from 1 to 48.
– Nikhil Mangire
Nov 24 '18 at 6:45
@NikhilMangire - OK, so check another solution.
– jezrael
Nov 24 '18 at 6:47
@NikhilMangire - Added next 2 solutions, it still some problem, what returnprint (type(df['Time'].iat[0]))?
– jezrael
Nov 24 '18 at 7:00
add a comment |
your code only numbers from 1 to ~ , it doesn't encode from 1 to 48.
– Nikhil Mangire
Nov 24 '18 at 6:45
@NikhilMangire - OK, so check another solution.
– jezrael
Nov 24 '18 at 6:47
@NikhilMangire - Added next 2 solutions, it still some problem, what returnprint (type(df['Time'].iat[0]))?
– jezrael
Nov 24 '18 at 7:00
your code only numbers from 1 to ~ , it doesn't encode from 1 to 48.
– Nikhil Mangire
Nov 24 '18 at 6:45
your code only numbers from 1 to ~ , it doesn't encode from 1 to 48.
– Nikhil Mangire
Nov 24 '18 at 6:45
@NikhilMangire - OK, so check another solution.
– jezrael
Nov 24 '18 at 6:47
@NikhilMangire - OK, so check another solution.
– jezrael
Nov 24 '18 at 6:47
@NikhilMangire - Added next 2 solutions, it still some problem, what return
print (type(df['Time'].iat[0])) ?– jezrael
Nov 24 '18 at 7:00
@NikhilMangire - Added next 2 solutions, it still some problem, what return
print (type(df['Time'].iat[0])) ?– jezrael
Nov 24 '18 at 7:00
add a comment |
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