vDataFrame[].round¶

In [ ]:

vDataFrame[].round(n: int)

Rounds the vcolumn by keeping only the input number of digits after comma.

Parameters¶

Name	Type	Optional	Description
n	int	❌	Number of digits to keep after comma.

Returns¶

vDataFrame : self.parent

Example¶

In [64]:

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 [65]:

sm["val"].round(n = 1)

	123 val Numeric(11,7)	📅 time Timestamp	123 id Int
1	0E-7	2014-01-01 01:15:00	2
2	0.1000000	2014-01-01 02:30:00	5
3	0.1000000	2014-01-01 03:00:00	1
4	1.5000000	2014-01-01 05:00:00	3
5	0.1000000	2014-01-01 06:00:00	5
6	2.3000000	2014-01-01 07:15:00	9
7	0.1000000	2014-01-01 07:45:00	4
8	0.1000000	2014-01-01 10:45:00	8
9	0E-7	2014-01-01 11:00:00	0
10	0.5000000	2014-01-01 11:00:00	6
11	0.1000000	2014-01-01 11:15:00	5
12	0.6000000	2014-01-01 13:00:00	4
13	0.3000000	2014-01-01 13:45:00	0
14	0.2000000	2014-01-01 15:30:00	9
15	0.6000000	2014-01-01 16:45:00	7
16	1.4000000	2014-01-01 17:00:00	5
17	0.6000000	2014-01-01 17:15:00	1
18	0.4000000	2014-01-01 19:15:00	1
19	0.5000000	2014-01-01 22:30:00	9
20	0.4000000	2014-01-02 00:30:00	2
21	0.1000000	2014-01-02 01:30:00	3
22	0.1000000	2014-01-02 02:45:00	3
23	0.1000000	2014-01-02 03:00:00	6
24	0E-7	2014-01-02 03:30:00	1
25	0.1000000	2014-01-02 03:45:00	8
26	0.1000000	2014-01-02 04:45:00	7
27	0E-7	2014-01-02 05:30:00	1
28	0E-7	2014-01-02 06:45:00	1
29	0.1000000	2014-01-02 06:45:00	5
30	0.1000000	2014-01-02 10:15:00	1
31	0.3000000	2014-01-02 10:45:00	0
32	0.3000000	2014-01-02 11:15:00	0
33	0.4000000	2014-01-02 12:30:00	5
34	0.4000000	2014-01-02 13:45:00	0
35	0.3000000	2014-01-02 14:30:00	4
36	0.1000000	2014-01-02 15:30:00	0
37	0.2000000	2014-01-02 15:30:00	7
38	0.5000000	2014-01-02 16:00:00	8
39	0.9000000	2014-01-02 17:45:00	4
40	1.0000000	2014-01-02 19:30:00	9
41	1.5000000	2014-01-02 19:45:00	6
42	1.8000000	2014-01-02 20:15:00	8
43	0.1000000	2014-01-03 00:30:00	8
44	0.3000000	2014-01-03 00:45:00	6
45	0.1000000	2014-01-03 01:45:00	9
46	0.1000000	2014-01-03 02:45:00	6
47	0.1000000	2014-01-03 03:15:00	9
48	0.1000000	2014-01-03 04:30:00	3
49	0.1000000	2014-01-03 04:30:00	1
50	0.1000000	2014-01-03 05:45:00	8
51	0E-7	2014-01-03 06:30:00	7
52	0.1000000	2014-01-03 07:45:00	9
53	0.3000000	2014-01-03 07:45:00	2
54	0.1000000	2014-01-03 08:30:00	0
55	1.5000000	2014-01-03 09:15:00	4
56	0.1000000	2014-01-03 10:30:00	9
57	2.1000000	2014-01-03 11:00:00	4
58	0.1000000	2014-01-03 12:15:00	8
59	0.5000000	2014-01-03 19:45:00	7
60	0.7000000	2014-01-03 21:30:00	7
61	0.6000000	2014-01-03 22:15:00	5
62	1.9000000	2014-01-03 22:15:00	1
63	0.3000000	2014-01-03 23:30:00	4
64	0.1000000	2014-01-04 01:15:00	6
65	1.5000000	2014-01-04 01:30:00	1
66	0.4000000	2014-01-04 01:45:00	6
67	0.4000000	2014-01-04 02:15:00	6
68	0.2000000	2014-01-04 02:45:00	5
69	0.1000000	2014-01-04 05:45:00	8
70	0.3000000	2014-01-04 06:00:00	5
71	0.1000000	2014-01-04 06:45:00	8
72	0.1000000	2014-01-04 07:30:00	2
73	0.3000000	2014-01-04 07:45:00	4
74	0.2000000	2014-01-04 10:00:00	8
75	0.5000000	2014-01-04 10:45:00	7
76	1.3000000	2014-01-04 11:45:00	8
77	0.1000000	2014-01-04 12:00:00	2
78	1.4000000	2014-01-04 13:30:00	8
79	0.3000000	2014-01-04 17:15:00	2
80	0.4000000	2014-01-04 17:15:00	9
81	0.6000000	2014-01-04 18:00:00	4
82	0.8000000	2014-01-04 22:30:00	4
83	0.3000000	2014-01-04 23:45:00	0
84	0.3000000	2014-01-05 02:15:00	6
85	0.1000000	2014-01-05 04:00:00	9
86	0.1000000	2014-01-05 06:30:00	9
87	0.1000000	2014-01-05 08:00:00	4
88	0.2000000	2014-01-05 08:45:00	9
89	0.3000000	2014-01-05 10:00:00	3
90	0.6000000	2014-01-05 10:15:00	6
91	1.1000000	2014-01-05 11:30:00	6
92	0.6000000	2014-01-05 17:30:00	4
93	0.5000000	2014-01-05 19:45:00	4
94	0.5000000	2014-01-05 19:45:00	1
95	0.5000000	2014-01-05 23:30:00	9
96	0.1000000	2014-01-06 01:15:00	0
97	0.1000000	2014-01-06 02:45:00	8
98	0.1000000	2014-01-06 05:00:00	3
99	0E-7	2014-01-06 07:45:00	3
100	0.5000000	2014-01-06 07:45:00	2

Out[65]:

Rows: 1-100 of 11844 | Columns: 3

vDataFrame[].round¶

Parameters¶

Returns¶

Example¶

See Also¶