vDataFrame[].get_dummies¶

In [ ]:

vDataFrame[].get_dummies(prefix: str = "", 
                         prefix_sep: str = "_", 
                         drop_first: bool = True, 
                         use_numbers_as_suffix: bool = False)

Encodes the vcolumn using the One Hot Encoding algorithm.

Parameters¶

Name	Type	Optional	Description
prefix	str	✓	Prefix of the dummies.
prefix_sep	str	✓	Prefix delimitor of the dummies.
drop_first	bool	✓	Drops the first dummy to avoid the creation of correlated features.
use_numbers_as_suffix	bool	✓	Uses numbers as suffix instead of the vcolumns categories.

Returns¶

vDataFrame : self.parent

Example¶

In [79]:

from verticapy import vDataFrame
churn = vDataFrame("public.churn")
churn = churn.select(["InternetService", "MonthlyCharges", "churn"])
display(churn)

	Abc InternetService Varchar(20)	123 MonthlyCharges Float	Abc Churn Varchar(3)
1	DSL	65.6	No
2	DSL	59.9	No
3	Fiber optic	73.9	Yes
4	Fiber optic	98.0	Yes
5	Fiber optic	83.9	Yes
6	DSL	69.4	No
7	Fiber optic	109.7	No
8	Fiber optic	84.65	No
9	DSL	48.2	No
10	DSL	90.45	No
11	DSL	45.2	No
12	Fiber optic	116.8	No
13	Fiber optic	68.95	No
14	Fiber optic	101.3	No
15	DSL	45.05	No
16	Fiber optic	95.75	No
17	DSL	61.25	No
18	Fiber optic	72.1	No
19	DSL	62.7	Yes
20	DSL	25.1	Yes
21	No	25.2	No
22	Fiber optic	94.1	Yes
23	Fiber optic	83.75	No
24	No	19.85	No
25	No	20.35	Yes
26	DSL	30.5	Yes
27	Fiber optic	103.7	No
28	No	20.4	No
29	No	19.6	No
30	No	19.7	No
31	Fiber optic	91.2	No
32	No	20.45	No
33	Fiber optic	115.8	No
34	No	20.55	No
35	DSL	39.4	No
36	No	25.1	No
37	Fiber optic	89.8	No
38	Fiber optic	94.75	No
39	No	20.3	No
40	Fiber optic	75.75	No
41	DSL	49.25	Yes
42	DSL	78.2	No
43	No	25.5	No
44	DSL	61.6	No
45	DSL	45.0	No
46	DSL	85.15	No
47	DSL	51.45	No
48	Fiber optic	99.25	No
49	DSL	44.3	No
50	Fiber optic	94.2	No
51	DSL	81.25	No
52	Fiber optic	99.95	No
53	Fiber optic	91.55	No
54	Fiber optic	104.5	Yes
55	Fiber optic	95.0	Yes
56	DSL	50.35	No
57	DSL	64.5	No
58	No	19.4	No
59	Fiber optic	104.8	No
60	Fiber optic	109.4	No
61	DSL	50.3	No
62	DSL	71.4	No
63	Fiber optic	116.0	No
64	No	19.85	Yes
65	Fiber optic	99.75	Yes
66	Fiber optic	93.95	No
67	Fiber optic	90.8	No
68	DSL	84.35	Yes
69	DSL	58.25	No
70	Fiber optic	107.55	No
71	No	19.95	No
72	Fiber optic	111.2	Yes
73	DSL	40.2	Yes
74	Fiber optic	85.8	No
75	DSL	35.4	No
76	Fiber optic	73.85	Yes
77	DSL	88.1	No
78	Fiber optic	101.35	Yes
79	DSL	45.8	No
80	Fiber optic	94.65	No
81	No	20.5	No
82	Fiber optic	89.4	No
83	Fiber optic	86.25	Yes
84	DSL	74.85	No
85	Fiber optic	89.75	Yes
86	Fiber optic	109.95	No
87	Fiber optic	80.2	Yes
88	No	19.85	Yes
89	Fiber optic	90.35	No
90	Fiber optic	86.45	No
91	No	20.3	No
92	Fiber optic	101.25	No
93	Fiber optic	94.7	Yes
94	Fiber optic	70.9	Yes
95	DSL	54.2	Yes
96	Fiber optic	114.9	No
97	No	19.55	No
98	Fiber optic	86.85	No
99	No	25.35	No
100	Fiber optic	109.9	No

Rows: 1-100 of 7032 | Columns: 3

In [78]:

churn["InternetService"].get_dummies()

	Abc InternetService Varchar(20)	123 MonthlyCharges Float	Abc Churn Varchar(3)	123 InternetService_DSL Bool	123 InternetService_Fiber_optic Bool
1	DSL	65.6	No	1	0
2	DSL	59.9	No	1	0
3	Fiber optic	73.9	Yes	0	1
4	Fiber optic	98.0	Yes	0	1
5	Fiber optic	83.9	Yes	0	1
6	DSL	69.4	No	1	0
7	Fiber optic	109.7	No	0	1
8	Fiber optic	84.65	No	0	1
9	DSL	48.2	No	1	0
10	DSL	90.45	No	1	0
11	DSL	45.2	No	1	0
12	Fiber optic	116.8	No	0	1
13	Fiber optic	68.95	No	0	1
14	Fiber optic	101.3	No	0	1
15	DSL	45.05	No	1	0
16	Fiber optic	95.75	No	0	1
17	DSL	61.25	No	1	0
18	Fiber optic	72.1	No	0	1
19	DSL	62.7	Yes	1	0
20	DSL	25.1	Yes	1	0
21	No	25.2	No	0	0
22	Fiber optic	94.1	Yes	0	1
23	Fiber optic	83.75	No	0	1
24	No	19.85	No	0	0
25	No	20.35	Yes	0	0
26	DSL	30.5	Yes	1	0
27	Fiber optic	103.7	No	0	1
28	No	20.4	No	0	0
29	No	19.6	No	0	0
30	No	19.7	No	0	0
31	Fiber optic	91.2	No	0	1
32	No	20.45	No	0	0
33	Fiber optic	115.8	No	0	1
34	No	20.55	No	0	0
35	DSL	39.4	No	1	0
36	No	25.1	No	0	0
37	Fiber optic	89.8	No	0	1
38	Fiber optic	94.75	No	0	1
39	No	20.3	No	0	0
40	Fiber optic	75.75	No	0	1
41	DSL	49.25	Yes	1	0
42	DSL	78.2	No	1	0
43	No	25.5	No	0	0
44	DSL	61.6	No	1	0
45	DSL	45.0	No	1	0
46	DSL	85.15	No	1	0
47	DSL	51.45	No	1	0
48	Fiber optic	99.25	No	0	1
49	DSL	44.3	No	1	0
50	Fiber optic	94.2	No	0	1
51	DSL	81.25	No	1	0
52	Fiber optic	99.95	No	0	1
53	Fiber optic	91.55	No	0	1
54	Fiber optic	104.5	Yes	0	1
55	Fiber optic	95.0	Yes	0	1
56	DSL	50.35	No	1	0
57	DSL	64.5	No	1	0
58	No	19.4	No	0	0
59	Fiber optic	104.8	No	0	1
60	Fiber optic	109.4	No	0	1
61	DSL	50.3	No	1	0
62	DSL	71.4	No	1	0
63	Fiber optic	116.0	No	0	1
64	No	19.85	Yes	0	0
65	Fiber optic	99.75	Yes	0	1
66	Fiber optic	93.95	No	0	1
67	Fiber optic	90.8	No	0	1
68	DSL	84.35	Yes	1	0
69	DSL	58.25	No	1	0
70	Fiber optic	107.55	No	0	1
71	No	19.95	No	0	0
72	Fiber optic	111.2	Yes	0	1
73	DSL	40.2	Yes	1	0
74	Fiber optic	85.8	No	0	1
75	DSL	35.4	No	1	0
76	Fiber optic	73.85	Yes	0	1
77	DSL	88.1	No	1	0
78	Fiber optic	101.35	Yes	0	1
79	DSL	45.8	No	1	0
80	Fiber optic	94.65	No	0	1
81	No	20.5	No	0	0
82	Fiber optic	89.4	No	0	1
83	Fiber optic	86.25	Yes	0	1
84	DSL	74.85	No	1	0
85	Fiber optic	89.75	Yes	0	1
86	Fiber optic	109.95	No	0	1
87	Fiber optic	80.2	Yes	0	1
88	No	19.85	Yes	0	0
89	Fiber optic	90.35	No	0	1
90	Fiber optic	86.45	No	0	1
91	No	20.3	No	0	0
92	Fiber optic	101.25	No	0	1
93	Fiber optic	94.7	Yes	0	1
94	Fiber optic	70.9	Yes	0	1
95	DSL	54.2	Yes	1	0
96	Fiber optic	114.9	No	0	1
97	No	19.55	No	0	0
98	Fiber optic	86.85	No	0	1
99	No	25.35	No	0	0
100	Fiber optic	109.9	No	0	1

Out[78]:

Rows: 1-100 of 7032 | Columns: 5

In [80]:

# Number as suffix
churn["InternetService"].get_dummies(use_numbers_as_suffix = True)

	Abc InternetService Varchar(20)	123 MonthlyCharges Float	Abc Churn Varchar(3)	123 InternetService_0 Bool	123 InternetService_1 Bool
1	DSL	65.6	No	1	0
2	DSL	59.9	No	1	0
3	Fiber optic	73.9	Yes	0	1
4	Fiber optic	98.0	Yes	0	1
5	Fiber optic	83.9	Yes	0	1
6	DSL	69.4	No	1	0
7	Fiber optic	109.7	No	0	1
8	Fiber optic	84.65	No	0	1
9	DSL	48.2	No	1	0
10	DSL	90.45	No	1	0
11	DSL	45.2	No	1	0
12	Fiber optic	116.8	No	0	1
13	Fiber optic	68.95	No	0	1
14	Fiber optic	101.3	No	0	1
15	DSL	45.05	No	1	0
16	Fiber optic	95.75	No	0	1
17	DSL	61.25	No	1	0
18	Fiber optic	72.1	No	0	1
19	DSL	62.7	Yes	1	0
20	DSL	25.1	Yes	1	0
21	No	25.2	No	0	0
22	Fiber optic	94.1	Yes	0	1
23	Fiber optic	83.75	No	0	1
24	No	19.85	No	0	0
25	No	20.35	Yes	0	0
26	DSL	30.5	Yes	1	0
27	Fiber optic	103.7	No	0	1
28	No	20.4	No	0	0
29	No	19.6	No	0	0
30	No	19.7	No	0	0
31	Fiber optic	91.2	No	0	1
32	No	20.45	No	0	0
33	Fiber optic	115.8	No	0	1
34	No	20.55	No	0	0
35	DSL	39.4	No	1	0
36	No	25.1	No	0	0
37	Fiber optic	89.8	No	0	1
38	Fiber optic	94.75	No	0	1
39	No	20.3	No	0	0
40	Fiber optic	75.75	No	0	1
41	DSL	49.25	Yes	1	0
42	DSL	78.2	No	1	0
43	No	25.5	No	0	0
44	DSL	61.6	No	1	0
45	DSL	45.0	No	1	0
46	DSL	85.15	No	1	0
47	DSL	51.45	No	1	0
48	Fiber optic	99.25	No	0	1
49	DSL	44.3	No	1	0
50	Fiber optic	94.2	No	0	1
51	DSL	81.25	No	1	0
52	Fiber optic	99.95	No	0	1
53	Fiber optic	91.55	No	0	1
54	Fiber optic	104.5	Yes	0	1
55	Fiber optic	95.0	Yes	0	1
56	DSL	50.35	No	1	0
57	DSL	64.5	No	1	0
58	No	19.4	No	0	0
59	Fiber optic	104.8	No	0	1
60	Fiber optic	109.4	No	0	1
61	DSL	50.3	No	1	0
62	DSL	71.4	No	1	0
63	Fiber optic	116.0	No	0	1
64	No	19.85	Yes	0	0
65	Fiber optic	99.75	Yes	0	1
66	Fiber optic	93.95	No	0	1
67	Fiber optic	90.8	No	0	1
68	DSL	84.35	Yes	1	0
69	DSL	58.25	No	1	0
70	Fiber optic	107.55	No	0	1
71	No	19.95	No	0	0
72	Fiber optic	111.2	Yes	0	1
73	DSL	40.2	Yes	1	0
74	Fiber optic	85.8	No	0	1
75	DSL	35.4	No	1	0
76	Fiber optic	73.85	Yes	0	1
77	DSL	88.1	No	1	0
78	Fiber optic	101.35	Yes	0	1
79	DSL	45.8	No	1	0
80	Fiber optic	94.65	No	0	1
81	No	20.5	No	0	0
82	Fiber optic	89.4	No	0	1
83	Fiber optic	86.25	Yes	0	1
84	DSL	74.85	No	1	0
85	Fiber optic	89.75	Yes	0	1
86	Fiber optic	109.95	No	0	1
87	Fiber optic	80.2	Yes	0	1
88	No	19.85	Yes	0	0
89	Fiber optic	90.35	No	0	1
90	Fiber optic	86.45	No	0	1
91	No	20.3	No	0	0
92	Fiber optic	101.25	No	0	1
93	Fiber optic	94.7	Yes	0	1
94	Fiber optic	70.9	Yes	0	1
95	DSL	54.2	Yes	1	0
96	Fiber optic	114.9	No	0	1
97	No	19.55	No	0	0
98	Fiber optic	86.85	No	0	1
99	No	25.35	No	0	0
100	Fiber optic	109.9	No	0	1

Out[80]:

Rows: 1-100 of 7032 | Columns: 5

vDataFrame[].decode	Encodes the vcolumn using a user defined Encoding.
vDataFrame[].discretize	Discretizes the vcolumn.
vDataFrame[].label_encode	Encodes the vcolumn using the Label Encoding.
vDataFrame[].mean_encode	Encodes the vcolumn using the Mean Encoding of a response.

vDataFrame[].get_dummies¶

Parameters¶

Returns¶

Example¶

See Also¶