I have a dataset that containes a column with "Time" values, but it's showing as object, and I want to converte them to time so I can do a for loop to see if the time is between two times.
for i in df['Time']:
if i >= dt.time(21,0,0) and i <= dt.time(7, 30,0) or i >= dt.time(3,0,0) and i <= dt.time(10,0,0) or i >= dt.time(10,30,0) and i <= dt.time(14,0,0):
df['In/Out'] = 'In'
else:
df['In/Out'] = 'Out'
I want the code to set the value in a new column to "In" if the time is between two times. The first times are (21:00) & (07:30) the second are (03:00) & (10:00) and the third are (10:30) & (14:00)
If the time is not in those ranges, it should set the value in the new column to "Out".
You can simplify:
(21:00) & (07:30) the second are (03:00) & (10:00)
to:
(21:00) & (10:00)
so solution is use Series.between
with numpy.where
:
df=pd.DataFrame({'Time':['0:01:00','8:01:00','2021-08-13 10:19:10','12:01:00',
'14:01:00','18:01:01','23:01:00']})
df['Time'] = pd.to_datetime(df['Time']).dt.time
m = (df['Time'].between(dt.time(21,0,0), dt.time(23,23,23)) |
df['Time'].between(dt.time(0,0,0), dt.time(10,0,0)) |
df['Time'].between(dt.time(10,30,0), dt.time(14, 0,0)))
df['In/Out'] = np.where(m, 'In','Out')
print (df)
Time In/Out
0 00:01:00 In
1 08:01:00 In
2 10:19:10 Out
3 12:01:00 In
4 14:01:00 Out
5 18:01:01 Out
6 23:01:00 In
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