vDataFrame.isin¶

In [ ]:

vDataFrame.isin(val: dict)

Looks if some specific records are in the vDataFrame and it returns the new vDataFrame of the search.

Parameters¶

Name	Type	Optional	Description
val	dict	❌	Dictionary of the different records. Each key of the dictionary must represent a vcolumn. For example, to check if Badr Ouali and Fouad Teban are in the vDataFrame. You can write the following dict: {"name": ["Teban", "Ouali"], "surname": ["Fouad", "Badr"]}

Returns¶

vDataFrame : The vDataFrame of the search.

Example¶

In [1]:

from verticapy.datasets import load_amazon
amazon = load_amazon()
display(amazon)

	📅 date Date	Abc state Varchar(32)	123 number Int
1	1998-01-01	ACRE	0
2	1998-01-01	ALAGOAS	0
3	1998-01-01	AMAPÁ	0
4	1998-01-01	AMAZONAS	0
5	1998-01-01	BAHIA	0
6	1998-01-01	CEARÁ	0
7	1998-01-01	DISTRITO FEDERAL	0
8	1998-01-01	ESPÍRITO SANTO	0
9	1998-01-01	GOIÁS	0
10	1998-01-01	MARANHÃO	0
11	1998-01-01	MATO GROSSO	0
12	1998-01-01	MATO GROSSO DO SUL	0
13	1998-01-01	MINAS GERAIS	0
14	1998-01-01	PARANÁ	0
15	1998-01-01	PARAÍBA	0
16	1998-01-01	PARÁ	0
17	1998-01-01	PERNAMBUCO	0
18	1998-01-01	PIAUÍ	0
19	1998-01-01	RIO DE JANEIRO	0
20	1998-01-01	RIO GRANDE DO NORTE	0
21	1998-01-01	RIO GRANDE DO SUL	0
22	1998-01-01	RONDÔNIA	0
23	1998-01-01	RORAIMA	0
24	1998-01-01	SANTA CATARINA	0
25	1998-01-01	SERGIPE	0
26	1998-01-01	SÃO PAULO	0
27	1998-01-01	TOCANTINS	0
28	1998-02-01	ACRE	0
29	1998-02-01	ALAGOAS	0
30	1998-02-01	AMAPÁ	0
31	1998-02-01	AMAZONAS	0
32	1998-02-01	BAHIA	0
33	1998-02-01	CEARÁ	0
34	1998-02-01	DISTRITO FEDERAL	0
35	1998-02-01	ESPÍRITO SANTO	0
36	1998-02-01	GOIÁS	0
37	1998-02-01	MARANHÃO	0
38	1998-02-01	MATO GROSSO	0
39	1998-02-01	MATO GROSSO DO SUL	0
40	1998-02-01	MINAS GERAIS	0
41	1998-02-01	PARANÁ	0
42	1998-02-01	PARAÍBA	0
43	1998-02-01	PARÁ	0
44	1998-02-01	PERNAMBUCO	0
45	1998-02-01	PIAUÍ	0
46	1998-02-01	RIO DE JANEIRO	0
47	1998-02-01	RIO GRANDE DO NORTE	0
48	1998-02-01	RIO GRANDE DO SUL	0
49	1998-02-01	RONDÔNIA	0
50	1998-02-01	RORAIMA	0
51	1998-02-01	SANTA CATARINA	0
52	1998-02-01	SERGIPE	0
53	1998-02-01	SÃO PAULO	0
54	1998-02-01	TOCANTINS	0
55	1998-03-01	ACRE	0
56	1998-03-01	ALAGOAS	0
57	1998-03-01	AMAPÁ	0
58	1998-03-01	AMAZONAS	0
59	1998-03-01	BAHIA	0
60	1998-03-01	CEARÁ	0
61	1998-03-01	DISTRITO FEDERAL	0
62	1998-03-01	ESPÍRITO SANTO	0
63	1998-03-01	GOIÁS	0
64	1998-03-01	MARANHÃO	0
65	1998-03-01	MATO GROSSO	0
66	1998-03-01	MATO GROSSO DO SUL	0
67	1998-03-01	MINAS GERAIS	0
68	1998-03-01	PARANÁ	0
69	1998-03-01	PARAÍBA	0
70	1998-03-01	PARÁ	0
71	1998-03-01	PERNAMBUCO	0
72	1998-03-01	PIAUÍ	0
73	1998-03-01	RIO DE JANEIRO	0
74	1998-03-01	RIO GRANDE DO NORTE	0
75	1998-03-01	RIO GRANDE DO SUL	0
76	1998-03-01	RONDÔNIA	0
77	1998-03-01	RORAIMA	0
78	1998-03-01	SANTA CATARINA	0
79	1998-03-01	SERGIPE	0
80	1998-03-01	SÃO PAULO	0
81	1998-03-01	TOCANTINS	0
82	1998-04-01	ACRE	0
83	1998-04-01	ALAGOAS	0
84	1998-04-01	AMAPÁ	0
85	1998-04-01	AMAZONAS	0
86	1998-04-01	BAHIA	0
87	1998-04-01	CEARÁ	0
88	1998-04-01	DISTRITO FEDERAL	0
89	1998-04-01	ESPÍRITO SANTO	0
90	1998-04-01	GOIÁS	0
91	1998-04-01	MARANHÃO	0
92	1998-04-01	MATO GROSSO	0
93	1998-04-01	MATO GROSSO DO SUL	0
94	1998-04-01	MINAS GERAIS	0
95	1998-04-01	PARANÁ	0
96	1998-04-01	PARAÍBA	0
97	1998-04-01	PARÁ	0
98	1998-04-01	PERNAMBUCO	0
99	1998-04-01	PIAUÍ	0
100	1998-04-01	RIO DE JANEIRO	0

Rows: 1-100 | Columns: 3

In [3]:

amazon.isin({"state": ["RIO DE JANEIRO", "PARÁ"], 
             "number": [0, 0]})

Out[3]:

	📅 date Date	Abc state Varchar(32)	123 number Int
1	1998-01-01	PARÁ	0
2	1998-01-01	RIO DE JANEIRO	0
3	1998-02-01	PARÁ	0
4	1998-02-01	RIO DE JANEIRO	0
5	1998-03-01	PARÁ	0
6	1998-03-01	RIO DE JANEIRO	0
7	1998-04-01	PARÁ	0
8	1998-04-01	RIO DE JANEIRO	0
9	1998-05-01	PARÁ	0
10	1998-05-01	RIO DE JANEIRO	0
11	1999-01-01	RIO DE JANEIRO	0
12	1999-02-01	RIO DE JANEIRO	0
13	1999-03-01	RIO DE JANEIRO	0
14	1999-12-01	RIO DE JANEIRO	0
15	2000-01-01	RIO DE JANEIRO	0
16	2000-03-01	RIO DE JANEIRO	0
17	2000-12-01	RIO DE JANEIRO	0
18	2001-01-01	RIO DE JANEIRO	0
19	2001-03-01	PARÁ	0
20	2001-03-01	RIO DE JANEIRO	0
21	2001-04-01	PARÁ	0
22	2002-01-01	RIO DE JANEIRO	0
23	2003-01-01	RIO DE JANEIRO	0
24	2004-05-01	RIO DE JANEIRO	0
25	2006-05-01	PARÁ	0
26	2006-12-01	RIO DE JANEIRO	0
27	2007-01-01	RIO DE JANEIRO	0
28	2007-04-01	PARÁ	0
29	2007-12-01	RIO DE JANEIRO	0
30	2008-05-01	PARÁ	0
31	2008-05-01	RIO DE JANEIRO	0
32	2008-11-01	RIO DE JANEIRO	0

Rows: 1-32 | Columns: 3