vDataFrame.between_time¶

In [ ]:

vDataFrame.between_time(ts: str, 
                        start_time: (str, datetime.timedelta), 
                        end_time: (str, datetime.timedelta))

Filters the vDataFrame by only keeping the records between two input times.

Parameters¶

Name	Type	Optional	Description
ts	str	❌	TS (Time Series) vcolumn to use to filter the data. The vcolumn type must be date like (date, datetime, timestamp...)
start_time	str / time	❌	Input Start Time. For example, time = '12:00' will filter the data when time('ts') is lesser than 12:00.
end_time	str / time	❌	Input End Time. For example, time = '14:00' will filter the data when time('ts') is greater than 14:00.

Returns¶

vDataFrame : self

Example¶

In [126]:

from verticapy.datasets import load_smart_meters
sm = load_smart_meters()
display(sm)

	123 val Numeric(11,7)	📅 time Timestamp	123 id Int
1	0.0370000	2014-01-01 01:15:00	2
2	0.0800000	2014-01-01 02:30:00	5
3	0.0810000	2014-01-01 03:00:00	1
4	1.4890000	2014-01-01 05:00:00	3
5	0.0720000	2014-01-01 06:00:00	5
6	2.3060000	2014-01-01 07:15:00	9
7	0.1020000	2014-01-01 07:45:00	4
8	0.0970000	2014-01-01 10:45:00	8
9	0.0290000	2014-01-01 11:00:00	0
10	0.5060000	2014-01-01 11:00:00	6
11	0.1290000	2014-01-01 11:15:00	5
12	0.6220000	2014-01-01 13:00:00	4
13	0.2770000	2014-01-01 13:45:00	0
14	0.2350000	2014-01-01 15:30:00	9
15	0.6230000	2014-01-01 16:45:00	7
16	1.3500000	2014-01-01 17:00:00	5
17	0.5590000	2014-01-01 17:15:00	1
18	0.3750000	2014-01-01 19:15:00	1
19	0.5400000	2014-01-01 22:30:00	9
20	0.3580000	2014-01-02 00:30:00	2
21	0.1390000	2014-01-02 01:30:00	3
22	0.0550000	2014-01-02 02:45:00	3
23	0.0860000	2014-01-02 03:00:00	6
24	0.0440000	2014-01-02 03:30:00	1
25	0.0730000	2014-01-02 03:45:00	8
26	0.1000000	2014-01-02 04:45:00	7
27	0.0440000	2014-01-02 05:30:00	1
28	0.0480000	2014-01-02 06:45:00	1
29	0.0550000	2014-01-02 06:45:00	5
30	0.0820000	2014-01-02 10:15:00	1
31	0.3210000	2014-01-02 10:45:00	0
32	0.3050000	2014-01-02 11:15:00	0
33	0.3970000	2014-01-02 12:30:00	5
34	0.3580000	2014-01-02 13:45:00	0
35	0.2540000	2014-01-02 14:30:00	4
36	0.1150000	2014-01-02 15:30:00	0
37	0.1850000	2014-01-02 15:30:00	7
38	0.5240000	2014-01-02 16:00:00	8
39	0.8710000	2014-01-02 17:45:00	4
40	1.0380000	2014-01-02 19:30:00	9
41	1.4780000	2014-01-02 19:45:00	6
42	1.7760000	2014-01-02 20:15:00	8
43	0.0940000	2014-01-03 00:30:00	8
44	0.3130000	2014-01-03 00:45:00	6
45	0.1330000	2014-01-03 01:45:00	9
46	0.0600000	2014-01-03 02:45:00	6
47	0.0850000	2014-01-03 03:15:00	9
48	0.0660000	2014-01-03 04:30:00	3
49	0.0680000	2014-01-03 04:30:00	1
50	0.0670000	2014-01-03 05:45:00	8
51	0.0320000	2014-01-03 06:30:00	7
52	0.0840000	2014-01-03 07:45:00	9
53	0.2720000	2014-01-03 07:45:00	2
54	0.0710000	2014-01-03 08:30:00	0
55	1.5060000	2014-01-03 09:15:00	4
56	0.0740000	2014-01-03 10:30:00	9
57	2.1080000	2014-01-03 11:00:00	4
58	0.1030000	2014-01-03 12:15:00	8
59	0.4890000	2014-01-03 19:45:00	7
60	0.6720000	2014-01-03 21:30:00	7
61	0.5910000	2014-01-03 22:15:00	5
62	1.9380000	2014-01-03 22:15:00	1
63	0.2840000	2014-01-03 23:30:00	4
64	0.1310000	2014-01-04 01:15:00	6
65	1.5460000	2014-01-04 01:30:00	1
66	0.3610000	2014-01-04 01:45:00	6
67	0.3830000	2014-01-04 02:15:00	6
68	0.1850000	2014-01-04 02:45:00	5
69	0.0620000	2014-01-04 05:45:00	8
70	0.2670000	2014-01-04 06:00:00	5
71	0.0770000	2014-01-04 06:45:00	8
72	0.0680000	2014-01-04 07:30:00	2
73	0.3090000	2014-01-04 07:45:00	4
74	0.1530000	2014-01-04 10:00:00	8
75	0.5450000	2014-01-04 10:45:00	7
76	1.2680000	2014-01-04 11:45:00	8
77	0.0760000	2014-01-04 12:00:00	2
78	1.3600000	2014-01-04 13:30:00	8
79	0.2850000	2014-01-04 17:15:00	2
80	0.4470000	2014-01-04 17:15:00	9
81	0.6410000	2014-01-04 18:00:00	4
82	0.8270000	2014-01-04 22:30:00	4
83	0.3230000	2014-01-04 23:45:00	0
84	0.3050000	2014-01-05 02:15:00	6
85	0.1110000	2014-01-05 04:00:00	9
86	0.0750000	2014-01-05 06:30:00	9
87	0.0900000	2014-01-05 08:00:00	4
88	0.1600000	2014-01-05 08:45:00	9
89	0.2810000	2014-01-05 10:00:00	3
90	0.5800000	2014-01-05 10:15:00	6
91	1.1320000	2014-01-05 11:30:00	6
92	0.6250000	2014-01-05 17:30:00	4
93	0.5370000	2014-01-05 19:45:00	4
94	0.5460000	2014-01-05 19:45:00	1
95	0.5390000	2014-01-05 23:30:00	9
96	0.0850000	2014-01-06 01:15:00	0
97	0.0870000	2014-01-06 02:45:00	8
98	0.0690000	2014-01-06 05:00:00	3
99	0.0270000	2014-01-06 07:45:00	3
100	0.5300000	2014-01-06 07:45:00	2

Rows: 1-100 of 11844 | Columns: 3

In [127]:

sm.between_time(ts = "time", start_time = "12:00", end_time = "14:00")

10693 element(s) was/were filtered

	123 val Numeric(11,7)	📅 time Timestamp	123 id Int
1	0.6220000	2014-01-01 13:00:00	4
2	0.2770000	2014-01-01 13:45:00	0
3	0.3970000	2014-01-02 12:30:00	5
4	0.3580000	2014-01-02 13:45:00	0
5	0.1030000	2014-01-03 12:15:00	8
6	0.0760000	2014-01-04 12:00:00	2
7	1.3600000	2014-01-04 13:30:00	8
8	0.0870000	2014-01-07 13:15:00	3
9	0.4690000	2014-01-07 14:00:00	6
10	0.2720000	2014-01-08 13:15:00	7
11	0.1610000	2014-01-09 12:00:00	6
12	0.4100000	2014-01-09 12:30:00	5
13	0.1250000	2014-01-09 14:00:00	8
14	0.2980000	2014-01-10 12:15:00	6
15	0.4890000	2014-01-11 12:45:00	4
16	0.0530000	2014-01-11 13:00:00	8
17	11.4050000	2014-01-12 12:15:00	6
18	0.0600000	2014-01-13 12:15:00	4
19	0.0720000	2014-01-13 12:45:00	1
20	0.0410000	2014-01-13 13:15:00	4
21	0.0200000	2014-01-13 13:30:00	7
22	0.0990000	2014-01-14 13:00:00	0
23	0.2000000	2014-01-14 14:00:00	0
24	0.0490000	2014-01-15 12:00:00	9
25	0.0450000	2014-01-16 12:30:00	4
26	0.2630000	2014-01-16 12:45:00	1
27	0.5130000	2014-01-16 12:45:00	2
28	0.1280000	2014-01-18 13:45:00	5
29	0.0200000	2014-01-19 12:00:00	4
30	0.1200000	2014-01-19 14:00:00	2
31	0.1390000	2014-01-19 14:00:00	8
32	0.7810000	2014-01-20 12:15:00	7
33	0.1720000	2014-01-20 12:45:00	8
34	1.0850000	2014-01-20 12:45:00	7
35	0.1440000	2014-01-21 12:00:00	7
36	0.3270000	2014-01-21 12:30:00	0
37	0.1080000	2014-01-21 13:30:00	0
38	1.2030000	2014-01-21 13:30:00	6
39	0.1970000	2014-01-22 13:30:00	2
40	0.1680000	2014-01-24 12:15:00	0
41	0.0700000	2014-01-25 12:45:00	5
42	0.2630000	2014-01-26 12:15:00	3
43	0.1930000	2014-01-26 13:00:00	1
44	0.3230000	2014-01-27 12:00:00	4
45	0.4810000	2014-01-28 13:45:00	8
46	1.7190000	2014-01-29 13:00:00	0
47	1.0090000	2014-01-30 12:15:00	6
48	2.4450000	2014-01-30 13:30:00	6
49	0.1350000	2014-01-31 13:15:00	2
50	1.6460000	2014-01-31 13:45:00	1
51	0.1040000	2014-02-01 12:00:00	7
52	1.2380000	2014-02-02 12:15:00	1
53	0.7440000	2014-02-02 13:30:00	4
54	0.6060000	2014-02-02 14:00:00	4
55	0.1870000	2014-02-04 12:00:00	0
56	0.0580000	2014-02-04 12:45:00	9
57	0.0880000	2014-02-04 13:15:00	9
58	0.6730000	2014-02-04 13:15:00	2
59	0.2860000	2014-02-04 13:45:00	2
60	0.0580000	2014-02-05 12:30:00	5
61	0.9030000	2014-02-05 12:45:00	3
62	0.0590000	2014-02-05 14:00:00	1
63	0.4240000	2014-02-06 12:30:00	5
64	0.1420000	2014-02-07 12:45:00	9
65	0.5600000	2014-02-09 13:30:00	9
66	0.0270000	2014-02-10 12:15:00	8
67	0.0490000	2014-02-11 12:00:00	9
68	0.1540000	2014-02-12 12:15:00	3
69	0.0250000	2014-02-12 12:45:00	1
70	0.0330000	2014-02-14 13:45:00	0
71	0.2180000	2014-02-15 12:15:00	7
72	0.1180000	2014-02-15 12:45:00	9
73	0.0170000	2014-02-15 13:15:00	2
74	0.2680000	2014-02-15 13:15:00	1
75	0.0310000	2014-02-15 13:45:00	0
76	0.0880000	2014-02-16 13:45:00	9
77	0.0350000	2014-02-17 12:45:00	6
78	0.0490000	2014-02-17 12:45:00	0
79	0.4710000	2014-02-17 13:15:00	5
80	0.1170000	2014-02-18 12:15:00	9
81	0.0710000	2014-02-18 12:45:00	9
82	0.1500000	2014-02-18 13:00:00	1
83	0.2900000	2014-02-19 12:00:00	9
84	0.2980000	2014-02-21 12:30:00	1
85	0.5710000	2014-02-21 13:15:00	0
86	0.2300000	2014-02-21 14:00:00	3
87	0.0560000	2014-02-22 13:30:00	3
88	0.1740000	2014-02-23 12:00:00	0
89	0.0570000	2014-02-23 12:45:00	5
90	0.0630000	2014-02-25 13:00:00	4
91	14.6030000	2014-02-25 13:00:00	7
92	0.1240000	2014-02-26 12:00:00	8
93	0.3880000	2014-02-26 12:15:00	0
94	0.0780000	2014-02-26 13:30:00	7
95	0.0670000	2014-02-26 14:00:00	4
96	0.1640000	2014-02-27 14:00:00	4
97	0.1180000	2014-02-28 12:00:00	6
98	0.2990000	2014-02-28 12:00:00	2
99	0.0370000	2014-02-28 12:30:00	0
100	0.3920000	2014-03-02 12:30:00	2

Out[127]:

Rows: 1-100 of 1151 | Columns: 3

vDataFrame.at_time	Filters the data at the input time.
vDataFrame.first	Filters the data by only keeping the first records.
vDataFrame.filter	Filters the data using the input expression.
vDataFrame.last	Filters the data by only keeping the last records.

vDataFrame.between_time¶

Parameters¶

Returns¶

Example¶

See Also¶