I have the dataframes below (date/time is multi index) and I want to replace column values in (00:00:00~07:00:00) as a numpy array:
[[ 21.63920663 21.62012822 20.9900515 21.23217008 21.19482458
21.10839656 20.89631935 20.79977166 20.99176729 20.91567565
20.87258765 20.76210464 20.50357827 20.55897631 20.38005033
20.38227309 20.54460993 20.37707293 20.08279925 20.09955877
20.02559575 20.12390737 20.2917257 20.20056711 20.1589065
20.41302289 20.48000767 20.55604102 20.70255192]]
date time
2018-01-26 00:00:00 21.65
00:15:00 NaN
00:30:00 NaN
00:45:00 NaN
01:00:00 NaN
01:15:00 NaN
01:30:00 NaN
01:45:00 NaN
02:00:00 NaN
02:15:00 NaN
02:30:00 NaN
02:45:00 NaN
03:00:00 NaN
03:15:00 NaN
03:30:00 NaN
03:45:00 NaN
04:00:00 NaN
04:15:00 NaN
04:30:00 NaN
04:45:00 NaN
05:00:00 NaN
05:15:00 NaN
05:30:00 NaN
05:45:00 NaN
06:00:00 NaN
06:15:00 NaN
06:30:00 NaN
06:45:00 NaN
07:00:00 NaN
07:15:00 NaN
07:30:00 NaN
07:45:00 NaN
08:00:00 NaN
08:15:00 NaN
08:30:00 NaN
08:45:00 NaN
09:00:00 NaN
09:15:00 NaN
09:30:00 NaN
09:45:00 NaN
10:00:00 NaN
10:15:00 NaN
10:30:00 NaN
10:45:00 NaN
11:00:00 NaN
Name: temp, dtype: float64
<class 'datetime.time'>
How can I do this?
You can use slicers:
idx = pd.IndexSlice
df1.loc[idx[:, '00:00:00':'02:00:00'],:] = 1
Or if second levels are times:
import datetime
idx = pd.IndexSlice
df1.loc[idx[:, datetime.time(0, 0, 0):datetime.time(2, 0, 0)],:] = 1
Sample:
print (df1)
aaa
date time
2018-01-26 00:00:00 21.65
00:15:00 NaN
00:30:00 NaN
00:45:00 NaN
01:00:00 NaN
01:15:00 NaN
01:30:00 NaN
01:45:00 NaN
02:00:00 NaN
02:15:00 NaN
02:30:00 NaN
02:45:00 NaN
03:00:00 NaN
2018-01-27 00:00:00 2.00
00:15:00 NaN
00:30:00 NaN
00:45:00 NaN
01:00:00 NaN
01:15:00 NaN
01:30:00 NaN
01:45:00 NaN
02:00:00 NaN
02:15:00 NaN
02:30:00 NaN
02:45:00 NaN
03:00:00 NaN
idx = pd.IndexSlice
df1.loc[idx[:, '00:00:00':'02:00:00'],:] = 1
print (df1)
aaa
date time
2018-01-26 00:00:00 1.0
00:15:00 1.0
00:30:00 1.0
00:45:00 1.0
01:00:00 1.0
01:15:00 1.0
01:30:00 1.0
01:45:00 1.0
02:00:00 1.0
02:15:00 NaN
02:30:00 NaN
02:45:00 NaN
03:00:00 NaN
2018-01-27 00:00:00 1.0
00:15:00 1.0
00:30:00 1.0
00:45:00 1.0
01:00:00 1.0
01:15:00 1.0
01:30:00 1.0
01:45:00 1.0
02:00:00 1.0
02:15:00 NaN
02:30:00 NaN
02:45:00 NaN
03:00:00 NaN
EDIT:
For assign array is necessary use numpy.tile for repeat by length of first level unique values:
df1.loc[idx[:, '00:00:00':'02:00:00'],:] = np.tile(np.arange(1, 10),len(df1.index.levels[0]))
print (df1)
aaa
date time
2018-01-26 00:00:00 1.0
00:15:00 2.0
00:30:00 3.0
00:45:00 4.0
01:00:00 5.0
01:15:00 6.0
01:30:00 7.0
01:45:00 8.0
02:00:00 9.0
02:15:00 NaN
02:30:00 NaN
02:45:00 NaN
03:00:00 NaN
2018-01-27 00:00:00 1.0
00:15:00 2.0
00:30:00 3.0
00:45:00 4.0
01:00:00 5.0
01:15:00 6.0
01:30:00 7.0
01:45:00 8.0
02:00:00 9.0
02:15:00 NaN
02:30:00 NaN
02:45:00 NaN
03:00:00 NaN
More general solution with generated array by length of slice:
idx = pd.IndexSlice
len0 = df1.loc[idx[df1.index.levels[0][0], '00:00:00':'02:00:00'],:].shape[0]
len1 = len(df1.index.levels[0])
df1.loc[idx[:, '00:00:00':'02:00:00'],:] = np.tile(np.arange(1, len0 + 1), len1)
Tested with times:
import datetime
idx = pd.IndexSlice
arr =np.tile(np.arange(1, 10),len(df1.index.levels[0]))
df1.loc[idx[:, datetime.time(0, 0, 0):datetime.time(2, 0, 0)],:] = arr
print (df1)
aaa
date time
2018-01-26 00:00:00 1.0
00:15:00 2.0
00:30:00 3.0
00:45:00 4.0
01:00:00 5.0
01:15:00 6.0
01:30:00 7.0
01:45:00 8.0
02:00:00 9.0
02:15:00 NaN
02:30:00 NaN
02:45:00 NaN
03:00:00 NaN
2018-01-27 00:00:00 1.0
00:15:00 2.0
00:30:00 3.0
00:45:00 4.0
01:00:00 5.0
01:15:00 6.0
01:30:00 7.0
01:45:00 8.0
02:00:00 9.0
02:15:00 NaN
02:30:00 NaN
02:45:00 NaN
03:00:00 NaN
EDIT:
Last was problem found - my solution wokrs with one column DataFrame, but if working with Series need remove one ::
arr = np.array([[ 21.63920663, 21.62012822, 20.9900515, 21.23217008, 21.19482458, 21.10839656,
20.89631935, 20.79977166, 20.99176729, 20.91567565, 20.87258765, 20.76210464,
20.50357827, 20.55897631, 20.38005033, 20.38227309, 20.54460993, 20.37707293,
20.08279925, 20.09955877, 20.02559575, 20.12390737, 20.2917257, 20.20056711,
20.1589065, 20.41302289, 20.48000767, 20.55604102, 20.70255192]])
import datetime
idx = pd.IndexSlice
df1.loc[idx[:, datetime.time(0, 0, 0): datetime.time(7, 0, 0)]] = arr[0]
---^^^
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