vastorbit.VastFrame.to_db

VastFrame.to_db(name: str, usecols: Annotated[str | list[str], 'STRING representing one column or a list of columns'] | None = None, relation_type: Literal['view', 'table', 'insert'] = 'view', inplace: bool = False, db_filter: Annotated[str | list[str] | StringSQL | list[StringSQL], ''] = '', nb_split: int = 0, order_by: None | Annotated[str | list[str], 'STRING representing one column or a list of columns'] | dict = None) → VastFrame

Saves the VastFrame current relation to the VAST database.

Parameters:

• name (str) – Name of the relation. To save the relation in a specific schema, you can write '"my_schema"."my_relation"'. Use double quotes ‘”’ to avoid errors due to special characters.

• usecols (SQLColumns, optional) – VastColumn to select from the final VastFrame relation. If empty, all VastColumn are selected.

• relation_type (str, optional) –

  Type of the relation.

  • view:

    View.

  • table:

    Table.

  • insert:

    Inserts into an existing table.

• inplace (bool, optional) – If set to True, the VastFrame is replaced with the new relation.

• db_filter (SQLExpression, optional) – Filter used before creating the relation in the DB. It can be a list of conditions or an expression. This parameter is useful for creating train and test sets on TS.

• nb_split (int, optional) – If this parameter is greater than 0, it adds a new column '_vastorbit_split_' to the final relation. This column contains values in [0;nb_split - 1] where each category represents 1 / nb_split of the entire distribution.

• order_by (SQLColumns | dict, optional) – List of the VastColumn used to sort the data, using asc order or a dictionary of all sorting methods. For example, to sort by “column1” ASC and “column2” DESC, write: {"column1": "asc", "column2": "desc"}

Returns:

self

Return type:

VastFrame

Examples

We import vastorbit:

import vastorbit as vo

Hint

By assigning an alias to vastorbit, we mitigate the risk of code collisions with other libraries. This precaution is necessary because vastorbit uses commonly known function names like “average” and “median”, which can potentially lead to naming conflicts. The use of an alias ensures that the functions from vastorbit are used as intended without interfering with functions from other libraries.

For this example, we will use the Titanic dataset.

import vastorbit.datasets as vod

data = vod.load_titanic()

	123 pclass Integer	123 survived Integer	Abc name Varchar(164)	Abc sex Varchar(20)	123 age Double	123 sibsp Integer	123 parch Integer	Abc ticket Varchar(36)	123 fare Double	Abc cabin Varchar(30)	Abc embarked Varchar(20)	Abc boat Varchar(100)	123 body Integer	Abc home.dest Varchar(100)
1	3	1	McCormack, Mr. Thomas Joseph	male	[null]	0	0	367228	7.75	[null]	Q	[null]	[null]	[null]
2	3	1	McCoy, Miss. Agnes	female	[null]	2	0	367226	23.25	[null]	Q	16	[null]	[null]
3	3	1	McCoy, Miss. Alicia	female	[null]	2	0	367226	23.25	[null]	Q	16	[null]	[null]
4	3	1	McCoy, Mr. Bernard	male	[null]	2	0	367226	23.25	[null]	Q	16	[null]	[null]
5	3	1	McDermott, Miss. Brigdet Delia	female	[null]	0	0	330932	7.7875	[null]	Q	13	[null]	[null]
6	3	0	McEvoy, Mr. Michael	male	[null]	0	0	36568	15.5	[null]	Q	[null]	[null]	[null]
7	3	1	McGovern, Miss. Mary	female	[null]	0	0	330931	7.8792	[null]	Q	13	[null]	[null]
8	3	1	McGowan, Miss. Anna "Annie"	female	15.0	0	0	330923	8.0292	[null]	Q	[null]	[null]	[null]
9	3	0	McGowan, Miss. Katherine	female	35.0	0	0	9232	7.75	[null]	Q	[null]	[null]	[null]
10	3	0	McMahon, Mr. Martin	male	[null]	0	0	370372	7.75	[null]	Q	[null]	[null]	[null]
11	3	0	McNamee, Mr. Neal	male	24.0	1	0	376566	16.1	[null]	S	[null]	[null]	[null]
12	3	0	McNamee, Mrs. Neal (Eileen O'Leary)	female	19.0	1	0	376566	16.1	[null]	S	[null]	53	[null]
13	3	0	McNeill, Miss. Bridget	female	[null]	0	0	370368	7.75	[null]	Q	[null]	[null]	[null]
14	3	0	Meanwell, Miss. (Marion Ogden)	female	[null]	0	0	SOTON/O.Q. 392087	8.05	[null]	S	[null]	[null]	[null]
15	3	0	Meek, Mrs. Thomas (Annie Louise Rowley)	female	[null]	0	0	343095	8.05	[null]	S	[null]	[null]	[null]
16	3	0	Meo, Mr. Alfonzo	male	55.5	0	0	A.5. 11206	8.05	[null]	S	[null]	201	[null]
17	3	0	Mernagh, Mr. Robert	male	[null]	0	0	368703	7.75	[null]	Q	[null]	[null]	[null]
18	3	1	Midtsjo, Mr. Karl Albert	male	21.0	0	0	345501	7.775	[null]	S	15	[null]	[null]
19	3	0	Miles, Mr. Frank	male	[null]	0	0	359306	8.05	[null]	S	[null]	[null]	[null]
20	3	0	Mineff, Mr. Ivan	male	24.0	0	0	349233	7.8958	[null]	S	[null]	[null]	[null]
21	3	0	Minkoff, Mr. Lazar	male	21.0	0	0	349211	7.8958	[null]	S	[null]	[null]	[null]
22	3	0	Mionoff, Mr. Stoytcho	male	28.0	0	0	349207	7.8958	[null]	S	[null]	[null]	[null]
23	3	0	Mitkoff, Mr. Mito	male	[null]	0	0	349221	7.8958	[null]	S	[null]	[null]	[null]
24	3	1	Mockler, Miss. Helen Mary "Ellie"	female	[null]	0	0	330980	7.8792	[null]	Q	16	[null]	[null]
25	3	0	Moen, Mr. Sigurd Hansen	male	25.0	0	0	348123	7.65	F G73	S	[null]	309	[null]
26	3	1	Moor, Master. Meier	male	6.0	0	1	392096	12.475	E121	S	14	[null]	[null]
27	3	1	Moor, Mrs. (Beila)	female	27.0	0	1	392096	12.475	E121	S	14	[null]	[null]
28	3	0	Moore, Mr. Leonard Charles	male	[null]	0	0	A4. 54510	8.05	[null]	S	[null]	[null]	[null]
29	3	1	Moran, Miss. Bertha	female	[null]	1	0	371110	24.15	[null]	Q	16	[null]	[null]
30	3	0	Moran, Mr. Daniel J	male	[null]	1	0	371110	24.15	[null]	Q	[null]	[null]	[null]
31	3	0	Moran, Mr. James	male	[null]	0	0	330877	8.4583	[null]	Q	[null]	[null]	[null]
32	3	0	Morley, Mr. William	male	34.0	0	0	364506	8.05	[null]	S	[null]	[null]	[null]
33	3	0	Morrow, Mr. Thomas Rowan	male	[null]	0	0	372622	7.75	[null]	Q	[null]	[null]	[null]
34	3	1	Moss, Mr. Albert Johan	male	[null]	0	0	312991	7.775	[null]	S	B	[null]	[null]
35	3	1	Moubarek, Master. Gerios	male	[null]	1	1	2661	15.2458	[null]	C	C	[null]	[null]
36	3	1	Moubarek, Master. Halim Gonios ("William George")	male	[null]	1	1	2661	15.2458	[null]	C	C	[null]	[null]
37	3	1	Moubarek, Mrs. George (Omine "Amenia" Alexander)	female	[null]	0	2	2661	15.2458	[null]	C	C	[null]	[null]
38	3	1	Moussa, Mrs. (Mantoura Boulos)	female	[null]	0	0	2626	7.2292	[null]	C	[null]	[null]	[null]
39	3	0	Moutal, Mr. Rahamin Haim	male	[null]	0	0	374746	8.05	[null]	S	[null]	[null]	[null]
40	3	1	Mullens, Miss. Katherine "Katie"	female	[null]	0	0	35852	7.7333	[null]	Q	16	[null]	[null]
41	3	1	Mulvihill, Miss. Bertha E	female	24.0	0	0	382653	7.75	[null]	Q	15	[null]	[null]
42	3	0	Murdlin, Mr. Joseph	male	[null]	0	0	A./5. 3235	8.05	[null]	S	[null]	[null]	[null]
43	3	1	Murphy, Miss. Katherine "Kate"	female	[null]	1	0	367230	15.5	[null]	Q	16	[null]	[null]
44	3	1	Murphy, Miss. Margaret Jane	female	[null]	1	0	367230	15.5	[null]	Q	16	[null]	[null]
45	3	1	Murphy, Miss. Nora	female	[null]	0	0	36568	15.5	[null]	Q	16	[null]	[null]
46	3	0	Myhrman, Mr. Pehr Fabian Oliver Malkolm	male	18.0	0	0	347078	7.75	[null]	S	[null]	[null]	[null]
47	3	0	Naidenoff, Mr. Penko	male	22.0	0	0	349206	7.8958	[null]	S	[null]	[null]	[null]
48	3	1	Najib, Miss. Adele Kiamie "Jane"	female	15.0	0	0	2667	7.225	[null]	C	C	[null]	[null]
49	3	1	Nakid, Miss. Maria ("Mary")	female	1.0	0	2	2653	15.7417	[null]	C	C	[null]	[null]
50	3	1	Nakid, Mr. Sahid	male	20.0	1	1	2653	15.7417	[null]	C	C	[null]	[null]
51	3	1	Nakid, Mrs. Said (Waika "Mary" Mowad)	female	19.0	1	1	2653	15.7417	[null]	C	C	[null]	[null]
52	3	0	Nancarrow, Mr. William Henry	male	33.0	0	0	A./5. 3338	8.05	[null]	S	[null]	[null]	[null]
53	3	0	Nankoff, Mr. Minko	male	[null]	0	0	349218	7.8958	[null]	S	[null]	[null]	[null]
54	3	0	Nasr, Mr. Mustafa	male	[null]	0	0	2652	7.2292	[null]	C	[null]	[null]	[null]
55	3	0	Naughton, Miss. Hannah	female	[null]	0	0	365237	7.75	[null]	Q	[null]	[null]	[null]
56	3	0	Nenkoff, Mr. Christo	male	[null]	0	0	349234	7.8958	[null]	S	[null]	[null]	[null]
57	3	1	Nicola-Yarred, Master. Elias	male	12.0	1	0	2651	11.2417	[null]	C	C	[null]	[null]
58	3	1	Nicola-Yarred, Miss. Jamila	female	14.0	1	0	2651	11.2417	[null]	C	C	[null]	[null]
59	3	0	Nieminen, Miss. Manta Josefina	female	29.0	0	0	3101297	7.925	[null]	S	[null]	[null]	[null]
60	3	0	Niklasson, Mr. Samuel	male	28.0	0	0	363611	8.05	[null]	S	[null]	[null]	[null]
61	3	1	Nilsson, Miss. Berta Olivia	female	18.0	0	0	347066	7.775	[null]	S	D	[null]	[null]
62	3	1	Nilsson, Miss. Helmina Josefina	female	26.0	0	0	347470	7.8542	[null]	S	13	[null]	[null]
63	3	0	Nilsson, Mr. August Ferdinand	male	21.0	0	0	350410	7.8542	[null]	S	[null]	[null]	[null]
64	3	0	Nirva, Mr. Iisakki Antino Aijo	male	41.0	0	0	SOTON/O2 3101272	7.125	[null]	S	[null]	[null]	Finland Sudbury, ON
65	3	1	Niskanen, Mr. Juha	male	39.0	0	0	STON/O 2. 3101289	7.925	[null]	S	9	[null]	[null]
66	3	0	Nosworthy, Mr. Richard Cater	male	21.0	0	0	A/4. 39886	7.8	[null]	S	[null]	[null]	[null]
67	3	0	Novel, Mr. Mansouer	male	28.5	0	0	2697	7.2292	[null]	C	[null]	181	[null]
68	3	1	Nysten, Miss. Anna Sofia	female	22.0	0	0	347081	7.75	[null]	S	13	[null]	[null]
69	3	0	Nysveen, Mr. Johan Hansen	male	61.0	0	0	345364	6.2375	[null]	S	[null]	[null]	[null]
70	3	0	O'Brien, Mr. Thomas	male	[null]	1	0	370365	15.5	[null]	Q	[null]	[null]	[null]
71	3	0	O'Brien, Mr. Timothy	male	[null]	0	0	330979	7.8292	[null]	Q	[null]	[null]	[null]
72	3	1	O'Brien, Mrs. Thomas (Johanna "Hannah" Godfrey)	female	[null]	1	0	370365	15.5	[null]	Q	[null]	[null]	[null]
73	3	0	O'Connell, Mr. Patrick D	male	[null]	0	0	334912	7.7333	[null]	Q	[null]	[null]	[null]
74	3	0	O'Connor, Mr. Maurice	male	[null]	0	0	371060	7.75	[null]	Q	[null]	[null]	[null]
75	3	0	O'Connor, Mr. Patrick	male	[null]	0	0	366713	7.75	[null]	Q	[null]	[null]	[null]
76	3	0	Odahl, Mr. Nils Martin	male	23.0	0	0	7267	9.225	[null]	S	[null]	[null]	[null]
77	3	0	O'Donoghue, Ms. Bridget	female	[null]	0	0	364856	7.75	[null]	Q	[null]	[null]	[null]
78	3	1	O'Driscoll, Miss. Bridget	female	[null]	0	0	14311	7.75	[null]	Q	D	[null]	[null]
79	3	1	O'Dwyer, Miss. Ellen "Nellie"	female	[null]	0	0	330959	7.8792	[null]	Q	[null]	[null]	[null]
80	3	1	Ohman, Miss. Velin	female	22.0	0	0	347085	7.775	[null]	S	C	[null]	[null]
81	3	1	O'Keefe, Mr. Patrick	male	[null]	0	0	368402	7.75	[null]	Q	B	[null]	[null]
82	3	1	O'Leary, Miss. Hanora "Norah"	female	[null]	0	0	330919	7.8292	[null]	Q	13	[null]	[null]
83	3	1	Olsen, Master. Artur Karl	male	9.0	0	1	C 17368	3.1708	[null]	S	13	[null]	[null]
84	3	0	Olsen, Mr. Henry Margido	male	28.0	0	0	C 4001	22.525	[null]	S	[null]	173	[null]
85	3	0	Olsen, Mr. Karl Siegwart Andreas	male	42.0	0	1	4579	8.4042	[null]	S	[null]	[null]	[null]
86	3	0	Olsen, Mr. Ole Martin	male	[null]	0	0	Fa 265302	7.3125	[null]	S	[null]	[null]	[null]
87	3	0	Olsson, Miss. Elina	female	31.0	0	0	350407	7.8542	[null]	S	[null]	[null]	[null]
88	3	0	Olsson, Mr. Nils Johan Goransson	male	28.0	0	0	347464	7.8542	[null]	S	[null]	[null]	[null]
89	3	1	Olsson, Mr. Oscar Wilhelm	male	32.0	0	0	347079	7.775	[null]	S	A	[null]	[null]
90	3	0	Olsvigen, Mr. Thor Anderson	male	20.0	0	0	6563	9.225	[null]	S	[null]	89	Oslo, Norway Cameron, WI
91	3	0	Oreskovic, Miss. Jelka	female	23.0	0	0	315085	8.6625	[null]	S	[null]	[null]	[null]
92	3	0	Oreskovic, Miss. Marija	female	20.0	0	0	315096	8.6625	[null]	S	[null]	[null]	[null]
93	3	0	Oreskovic, Mr. Luka	male	20.0	0	0	315094	8.6625	[null]	S	[null]	[null]	[null]
94	3	0	Osen, Mr. Olaf Elon	male	16.0	0	0	7534	9.2167	[null]	S	[null]	[null]	[null]
95	3	1	Osman, Mrs. Mara	female	31.0	0	0	349244	8.6833	[null]	S	[null]	[null]	[null]
96	3	0	O'Sullivan, Miss. Bridget Mary	female	[null]	0	0	330909	7.6292	[null]	Q	[null]	[null]	[null]
97	3	0	Palsson, Master. Gosta Leonard	male	2.0	3	1	349909	21.075	[null]	S	[null]	4	[null]
98	3	0	Palsson, Master. Paul Folke	male	6.0	3	1	349909	21.075	[null]	S	[null]	[null]	[null]
99	3	0	Palsson, Miss. Stina Viola	female	3.0	3	1	349909	21.075	[null]	S	[null]	[null]	[null]
100	3	0	Palsson, Miss. Torborg Danira	female	8.0	3	1	349909	21.075	[null]	S	[null]	[null]	[null]

Rows: 1-100 | Columns: 14

Note

vastorbit offers a wide range of sample datasets that are ideal for training and testing purposes. You can explore the full list of available datasets in the Datasets, which provides detailed information on each dataset and how to use them effectively. These datasets are invaluable resources for honing your data analysis and machine learning skills within the vastorbit environment.

Let’s do some transformations.

data.get_dummies()
data.normalize()

	123 pclass Decimal(38, 11)	123 survived Decimal(38, 11)	Abc name Varchar(164)	Abc sex Varchar(20)	123 age Double	123 sibsp Decimal(38, 11)	123 parch Decimal(38, 12)	Abc ticket Varchar(36)	123 fare Double	Abc cabin Varchar(30)	Abc embarked Varchar(20)	Abc boat Varchar(100)	123 body Decimal(38, 13)	Abc home.dest Varchar(100)	123 pclass_1 Integer	123 pclass_2 Integer	123 sex_female Integer	123 sibsp_0 Integer	123 sibsp_1 Integer	123 sibsp_2 Integer	123 sibsp_3 Integer	123 sibsp_4 Integer	123 sibsp_5 Integer	123 parch_0 Integer	123 parch_1 Integer	123 parch_2 Integer	123 parch_3 Integer	123 parch_4 Integer	123 parch_5 Integer	123 parch_6 Integer	123 embarked_C Integer	123 embarked_Q Integer
1	0.84159476919	1.27152032699	McCormack, Mr. Thomas Joseph	male	[null]	-0.47890372851	-0.444829492449	367228	-0.4935497792041573	[null]	Q	[null]	[null]	[null]	0	0	0	1	0	0	0	0	0	1	0	0	0	0	0	0	0	1
2	0.84159476919	1.27152032699	McCoy, Miss. Agnes	female	[null]	1.44111152607	-0.444829492449	367226	-0.1940830323324008	[null]	Q	16	[null]	[null]	0	0	1	0	0	1	0	0	0	1	0	0	0	0	0	0	0	1
3	0.84159476919	1.27152032699	McCoy, Miss. Alicia	female	[null]	1.44111152607	-0.444829492449	367226	-0.1940830323324008	[null]	Q	16	[null]	[null]	0	0	1	0	0	1	0	0	0	1	0	0	0	0	0	0	0	1
4	0.84159476919	1.27152032699	McCoy, Mr. Bernard	male	[null]	1.44111152607	-0.444829492449	367226	-0.1940830323324008	[null]	Q	16	[null]	[null]	0	0	0	0	0	1	0	0	0	1	0	0	0	0	0	0	0	1
5	0.84159476919	1.27152032699	McDermott, Miss. Brigdet Delia	female	[null]	-0.47890372851	-0.444829492449	330932	-0.4928252628810805	[null]	Q	13	[null]	[null]	0	0	1	1	0	0	0	0	0	1	0	0	0	0	0	0	0	1
6	0.84159476919	-0.78585928738	McEvoy, Mr. Michael	male	[null]	-0.47890372851	-0.444829492449	36568	-0.34381640576827904	[null]	Q	[null]	[null]	[null]	0	0	0	1	0	0	0	0	0	1	0	0	0	0	0	0	0	1
7	0.84159476919	1.27152032699	McGovern, Miss. Mary	female	[null]	-0.47890372851	-0.444829492449	330931	-0.4910535789657166	[null]	Q	13	[null]	[null]	0	0	1	1	0	0	0	0	0	1	0	0	0	0	0	0	0	1
8	0.84159476919	1.27152032699	McGowan, Miss. Anna "Annie"	female	-1.0324449076416113	-0.47890372851	-0.444829492449	330923	-0.4881555136734093	[null]	Q	[null]	[null]	[null]	0	0	1	1	0	0	0	0	0	1	0	0	0	0	0	0	0	1
9	0.84159476919	-0.78585928738	McGowan, Miss. Katherine	female	0.35514377102512806	-0.47890372851	-0.444829492449	9232	-0.4935497792041573	[null]	Q	[null]	[null]	[null]	0	0	1	1	0	0	0	0	0	1	0	0	0	0	0	0	0	1
10	0.84159476919	-0.78585928738	McMahon, Mr. Martin	male	[null]	-0.47890372851	-0.444829492449	370372	-0.4935497792041573	[null]	Q	[null]	[null]	[null]	0	0	0	1	0	0	0	0	0	1	0	0	0	0	0	0	0	1
11	0.84159476919	-0.78585928738	McNamee, Mr. Neal	male	-0.40803000224157854	0.48110389878	-0.444829492449	376566	-0.33222414459904975	[null]	S	[null]	[null]	[null]	0	0	0	0	1	0	0	0	0	1	0	0	0	0	0	0	0	0
12	0.84159476919	-0.78585928738	McNamee, Mrs. Neal (Eileen O'Leary)	female	-0.7549271719082634	0.48110389878	-0.444829492449	376566	-0.33222414459904975	[null]	S	[null]	-1.1035139608573	[null]	0	0	1	0	1	0	0	0	0	1	0	0	0	0	0	0	0	0
13	0.84159476919	-0.78585928738	McNeill, Miss. Bridget	female	[null]	-0.47890372851	-0.444829492449	370368	-0.4935497792041573	[null]	Q	[null]	[null]	[null]	0	0	1	1	0	0	0	0	0	1	0	0	0	0	0	0	0	1
14	0.84159476919	-0.78585928738	Meanwell, Miss. (Marion Ogden)	female	[null]	-0.47890372851	-0.444829492449	SOTON/O.Q. 392087	-0.4877536486195427	[null]	S	[null]	[null]	[null]	0	0	1	1	0	0	0	0	0	1	0	0	0	0	0	0	0	0
15	0.84159476919	-0.78585928738	Meek, Mrs. Thomas (Annie Louise Rowley)	female	[null]	-0.47890372851	-0.444829492449	343095	-0.4877536486195427	[null]	S	[null]	[null]	[null]	0	0	1	1	0	0	0	0	0	1	0	0	0	0	0	0	0	0
16	0.84159476919	-0.78585928738	Meo, Mr. Alfonzo	male	1.777422166658536	-0.47890372851	-0.444829492449	A.5. 11206	-0.4877536486195427	[null]	S	[null]	0.4113751162628	[null]	0	0	0	1	0	0	0	0	0	1	0	0	0	0	0	0	0	0
17	0.84159476919	-0.78585928738	Mernagh, Mr. Robert	male	[null]	-0.47890372851	-0.444829492449	368703	-0.4935497792041573	[null]	Q	[null]	[null]	[null]	0	0	0	1	0	0	0	0	0	1	0	0	0	0	0	0	0	1
18	0.84159476919	1.27152032699	Midtsjo, Mr. Karl Albert	male	-0.6161683040415894	-0.47890372851	-0.444829492449	345501	-0.4930667683221061	[null]	S	15	[null]	[null]	0	0	0	1	0	0	0	0	0	1	0	0	0	0	0	0	0	0
19	0.84159476919	-0.78585928738	Miles, Mr. Frank	male	[null]	-0.47890372851	-0.444829492449	359306	-0.4877536486195427	[null]	S	[null]	[null]	[null]	0	0	0	1	0	0	0	0	0	1	0	0	0	0	0	0	0	0
20	0.84159476919	-0.78585928738	Mineff, Mr. Ivan	male	-0.40803000224157854	-0.47890372851	-0.444829492449	349233	-0.4907328597400346	[null]	S	[null]	[null]	[null]	0	0	0	1	0	0	0	0	0	1	0	0	0	0	0	0	0	0
21	0.84159476919	-0.78585928738	Minkoff, Mr. Lazar	male	-0.6161683040415894	-0.47890372851	-0.444829492449	349211	-0.4907328597400346	[null]	S	[null]	[null]	[null]	0	0	0	1	0	0	0	0	0	1	0	0	0	0	0	0	0	0
22	0.84159476919	-0.78585928738	Mionoff, Mr. Stoytcho	male	-0.13051226650823067	-0.47890372851	-0.444829492449	349207	-0.4907328597400346	[null]	S	[null]	[null]	[null]	0	0	0	1	0	0	0	0	0	1	0	0	0	0	0	0	0	0
23	0.84159476919	-0.78585928738	Mitkoff, Mr. Mito	male	[null]	-0.47890372851	-0.444829492449	349221	-0.4907328597400346	[null]	S	[null]	[null]	[null]	0	0	0	1	0	0	0	0	0	1	0	0	0	0	0	0	0	0
24	0.84159476919	1.27152032699	Mockler, Miss. Helen Mary "Ellie"	female	[null]	-0.47890372851	-0.444829492449	330980	-0.4910535789657166	[null]	Q	16	[null]	[null]	0	0	1	1	0	0	0	0	0	1	0	0	0	0	0	0	0	1
25	0.84159476919	-0.78585928738	Moen, Mr. Sigurd Hansen	male	-0.3386505683082416	-0.47890372851	-0.444829492449	348123	-0.49548182273236224	F G73	S	[null]	1.5168347130802	[null]	0	0	0	1	0	0	0	0	0	1	0	0	0	0	0	0	0	0
26	0.84159476919	1.27152032699	Moor, Master. Meier	male	-1.6568598130416439	-0.47890372851	0.71049155044	392096	-0.40226072249647665	E121	S	14	[null]	[null]	0	0	0	1	0	0	0	0	0	0	1	0	0	0	0	0	0	0
27	0.84159476919	1.27152032699	Moor, Mrs. (Beila)	female	-0.19989170044156765	-0.47890372851	0.71049155044	392096	-0.40226072249647665	E121	S	14	[null]	[null]	0	0	1	1	0	0	0	0	0	0	1	0	0	0	0	0	0	0
28	0.84159476919	-0.78585928738	Moore, Mr. Leonard Charles	male	[null]	-0.47890372851	-0.444829492449	A4. 54510	-0.4877536486195427	[null]	S	[null]	[null]	[null]	0	0	0	1	0	0	0	0	0	1	0	0	0	0	0	0	0	0
29	0.84159476919	1.27152032699	Moran, Miss. Bertha	female	[null]	0.48110389878	-0.444829492449	371110	-0.17669464057855688	[null]	Q	16	[null]	[null]	0	0	1	0	1	0	0	0	0	1	0	0	0	0	0	0	0	1
30	0.84159476919	-0.78585928738	Moran, Mr. Daniel J	male	[null]	0.48110389878	-0.444829492449	371110	-0.17669464057855688	[null]	Q	[null]	[null]	[null]	0	0	0	0	1	0	0	0	0	1	0	0	0	0	0	0	0	1
31	0.84159476919	-0.78585928738	Moran, Mr. James	male	[null]	-0.47890372851	-0.444829492449	330877	-0.4798651148938821	[null]	Q	[null]	[null]	[null]	0	0	0	1	0	0	0	0	0	1	0	0	0	0	0	0	0	1
32	0.84159476919	-0.78585928738	Morley, Mr. William	male	0.2857643370917911	-0.47890372851	-0.444829492449	364506	-0.4877536486195427	[null]	S	[null]	[null]	[null]	0	0	0	1	0	0	0	0	0	1	0	0	0	0	0	0	0	0
33	0.84159476919	-0.78585928738	Morrow, Mr. Thomas Rowan	male	[null]	-0.47890372851	-0.444829492449	372622	-0.4935497792041573	[null]	Q	[null]	[null]	[null]	0	0	0	1	0	0	0	0	0	1	0	0	0	0	0	0	0	1
34	0.84159476919	1.27152032699	Moss, Mr. Albert Johan	male	[null]	-0.47890372851	-0.444829492449	312991	-0.4930667683221061	[null]	S	B	[null]	[null]	0	0	0	1	0	0	0	0	0	1	0	0	0	0	0	0	0	0
35	0.84159476919	1.27152032699	Moubarek, Master. Gerios	male	[null]	0.48110389878	0.71049155044	2661	-0.3487276604169759	[null]	C	C	[null]	[null]	0	0	0	0	1	0	0	0	0	0	1	0	0	0	0	0	1	0
36	0.84159476919	1.27152032699	Moubarek, Master. Halim Gonios ("William George")	male	[null]	0.48110389878	0.71049155044	2661	-0.3487276604169759	[null]	C	C	[null]	[null]	0	0	0	0	1	0	0	0	0	0	1	0	0	0	0	0	1	0
37	0.84159476919	1.27152032699	Moubarek, Mrs. George (Omine "Amenia" Alexander)	female	[null]	-0.47890372851	1.865812593329	2661	-0.3487276604169759	[null]	C	C	[null]	[null]	0	0	1	1	0	0	0	0	0	0	0	1	0	0	0	0	1	0
38	0.84159476919	1.27152032699	Moussa, Mrs. (Mantoura Boulos)	female	[null]	-0.47890372851	-0.444829492449	2626	-0.5036118618990484	[null]	C	[null]	[null]	[null]	0	0	1	1	0	0	0	0	0	1	0	0	0	0	0	0	1	0
39	0.84159476919	-0.78585928738	Moutal, Mr. Rahamin Haim	male	[null]	-0.47890372851	-0.444829492449	374746	-0.4877536486195427	[null]	S	[null]	[null]	[null]	0	0	0	1	0	0	0	0	0	1	0	0	0	0	0	0	0	0
40	0.84159476919	1.27152032699	Mullens, Miss. Katherine "Katie"	female	[null]	-0.47890372851	-0.444829492449	35852	-0.49387243047336754	[null]	Q	16	[null]	[null]	0	0	1	1	0	0	0	0	0	1	0	0	0	0	0	0	0	1
41	0.84159476919	1.27152032699	Mulvihill, Miss. Bertha E	female	-0.40803000224157854	-0.47890372851	-0.444829492449	382653	-0.4935497792041573	[null]	Q	15	[null]	[null]	0	0	1	1	0	0	0	0	0	1	0	0	0	0	0	0	0	1
42	0.84159476919	-0.78585928738	Murdlin, Mr. Joseph	male	[null]	-0.47890372851	-0.444829492449	A./5. 3235	-0.4877536486195427	[null]	S	[null]	[null]	[null]	0	0	0	1	0	0	0	0	0	1	0	0	0	0	0	0	0	0
43	0.84159476919	1.27152032699	Murphy, Miss. Katherine "Kate"	female	[null]	0.48110389878	-0.444829492449	367230	-0.34381640576827904	[null]	Q	16	[null]	[null]	0	0	1	0	1	0	0	0	0	1	0	0	0	0	0	0	0	1
44	0.84159476919	1.27152032699	Murphy, Miss. Margaret Jane	female	[null]	0.48110389878	-0.444829492449	367230	-0.34381640576827904	[null]	Q	16	[null]	[null]	0	0	1	0	1	0	0	0	0	1	0	0	0	0	0	0	0	1
45	0.84159476919	1.27152032699	Murphy, Miss. Nora	female	[null]	-0.47890372851	-0.444829492449	36568	-0.34381640576827904	[null]	Q	16	[null]	[null]	0	0	1	1	0	0	0	0	0	1	0	0	0	0	0	0	0	1
46	0.84159476919	-0.78585928738	Myhrman, Mr. Pehr Fabian Oliver Malkolm	male	-0.8243066058416003	-0.47890372851	-0.444829492449	347078	-0.4935497792041573	[null]	S	[null]	[null]	[null]	0	0	0	1	0	0	0	0	0	1	0	0	0	0	0	0	0	0
47	0.84159476919	-0.78585928738	Naidenoff, Mr. Penko	male	-0.5467888701082525	-0.47890372851	-0.444829492449	349206	-0.4907328597400346	[null]	S	[null]	[null]	[null]	0	0	0	1	0	0	0	0	0	1	0	0	0	0	0	0	0	0
48	0.84159476919	1.27152032699	Najib, Miss. Adele Kiamie "Jane"	female	-1.0324449076416113	-0.47890372851	-0.444829492449	2667	-0.5036930077272329	[null]	C	C	[null]	[null]	0	0	1	1	0	0	0	0	0	1	0	0	0	0	0	0	1	0
49	0.84159476919	1.27152032699	Nakid, Miss. Maria ("Mary")	female	-2.0037569827083286	-0.47890372851	1.865812593329	2653	-0.33914665656060783	[null]	C	C	[null]	[null]	0	0	1	1	0	0	0	0	0	0	0	1	0	0	0	0	1	0
50	0.84159476919	1.27152032699	Nakid, Mr. Sahid	male	-0.6855477379749264	0.48110389878	0.71049155044	2653	-0.33914665656060783	[null]	C	C	[null]	[null]	0	0	0	0	1	0	0	0	0	0	1	0	0	0	0	0	1	0
51	0.84159476919	1.27152032699	Nakid, Mrs. Said (Waika "Mary" Mowad)	female	-0.7549271719082634	0.48110389878	0.71049155044	2653	-0.33914665656060783	[null]	C	C	[null]	[null]	0	0	1	0	1	0	0	0	0	0	1	0	0	0	0	0	1	0
52	0.84159476919	-0.78585928738	Nancarrow, Mr. William Henry	male	0.21638490315845416	-0.47890372851	-0.444829492449	A./5. 3338	-0.4877536486195427	[null]	S	[null]	[null]	[null]	0	0	0	1	0	0	0	0	0	1	0	0	0	0	0	0	0	0
53	0.84159476919	-0.78585928738	Nankoff, Mr. Minko	male	[null]	-0.47890372851	-0.444829492449	349218	-0.4907328597400346	[null]	S	[null]	[null]	[null]	0	0	0	1	0	0	0	0	0	1	0	0	0	0	0	0	0	0
54	0.84159476919	-0.78585928738	Nasr, Mr. Mustafa	male	[null]	-0.47890372851	-0.444829492449	2652	-0.5036118618990484	[null]	C	[null]	[null]	[null]	0	0	0	1	0	0	0	0	0	1	0	0	0	0	0	0	1	0
55	0.84159476919	-0.78585928738	Naughton, Miss. Hannah	female	[null]	-0.47890372851	-0.444829492449	365237	-0.4935497792041573	[null]	Q	[null]	[null]	[null]	0	0	1	1	0	0	0	0	0	1	0	0	0	0	0	0	0	1
56	0.84159476919	-0.78585928738	Nenkoff, Mr. Christo	male	[null]	-0.47890372851	-0.444829492449	349234	-0.4907328597400346	[null]	S	[null]	[null]	[null]	0	0	0	1	0	0	0	0	0	1	0	0	0	0	0	0	0	0
57	0.84159476919	1.27152032699	Nicola-Yarred, Master. Elias	male	-1.240583209441622	0.48110389878	-0.444829492449	2651	-0.42608861532982745	[null]	C	C	[null]	[null]	0	0	0	0	1	0	0	0	0	1	0	0	0	0	0	0	1	0
58	0.84159476919	1.27152032699	Nicola-Yarred, Miss. Jamila	female	-1.1018243415749482	0.48110389878	-0.444829492449	2651	-0.42608861532982745	[null]	C	C	[null]	[null]	0	0	1	0	1	0	0	0	0	1	0	0	0	0	0	0	1	0
59	0.84159476919	-0.78585928738	Nieminen, Miss. Manta Josefina	female	-0.06113283257489371	-0.47890372851	-0.444829492449	3101297	-0.49016870302979876	[null]	S	[null]	[null]	[null]	0	0	1	1	0	0	0	0	0	1	0	0	0	0	0	0	0	0
60	0.84159476919	-0.78585928738	Niklasson, Mr. Samuel	male	-0.13051226650823067	-0.47890372851	-0.444829492449	363611	-0.4877536486195427	[null]	S	[null]	[null]	[null]	0	0	0	1	0	0	0	0	0	1	0	0	0	0	0	0	0	0
61	0.84159476919	1.27152032699	Nilsson, Miss. Berta Olivia	female	-0.8243066058416003	-0.47890372851	-0.444829492449	347066	-0.4930667683221061	[null]	S	D	[null]	[null]	0	0	1	1	0	0	0	0	0	1	0	0	0	0	0	0	0	0
62	0.84159476919	1.27152032699	Nilsson, Miss. Helmina Josefina	female	-0.26927113437490463	-0.47890372851	-0.444829492449	347470	-0.4915365898477679	[null]	S	13	[null]	[null]	0	0	1	1	0	0	0	0	0	1	0	0	0	0	0	0	0	0
63	0.84159476919	-0.78585928738	Nilsson, Mr. August Ferdinand	male	-0.6161683040415894	-0.47890372851	-0.444829492449	350410	-0.4915365898477679	[null]	S	[null]	[null]	[null]	0	0	0	1	0	0	0	0	0	1	0	0	0	0	0	0	0	0
64	0.84159476919	-0.78585928738	Nirva, Mr. Iisakki Antino Aijo	male	0.7714203746251499	-0.47890372851	-0.444829492449	SOTON/O2 3101272	-0.5056250512554379	[null]	S	[null]	[null]	Finland Sudbury, ON	0	0	0	1	0	0	0	0	0	1	0	0	0	0	0	0	0	0
65	0.84159476919	1.27152032699	Niskanen, Mr. Juha	male	0.632661506758476	-0.47890372851	-0.444829492449	STON/O 2. 3101289	-0.49016870302979876	[null]	S	9	[null]	[null]	0	0	0	1	0	0	0	0	0	1	0	0	0	0	0	0	0	0
66	0.84159476919	-0.78585928738	Nosworthy, Mr. Richard Cater	male	-0.6161683040415894	-0.47890372851	-0.444829492449	A/4. 39886	-0.4925837574400549	[null]	S	[null]	[null]	[null]	0	0	0	1	0	0	0	0	0	1	0	0	0	0	0	0	0	0
67	0.84159476919	-0.78585928738	Novel, Mr. Mansouer	male	-0.09582254954156219	-0.47890372851	-0.444829492449	2697	-0.5036118618990484	[null]	C	[null]	0.2066603761115	[null]	0	0	0	1	0	0	0	0	0	1	0	0	0	0	0	0	1	0
68	0.84159476919	1.27152032699	Nysten, Miss. Anna Sofia	female	-0.5467888701082525	-0.47890372851	-0.444829492449	347081	-0.4935497792041573	[null]	S	13	[null]	[null]	0	0	1	1	0	0	0	0	0	1	0	0	0	0	0	0	0	0
69	0.84159476919	-0.78585928738	Nysveen, Mr. Johan Hansen	male	2.1590090532918893	-0.47890372851	-0.444829492449	345364	-0.5227719375682561	[null]	S	[null]	[null]	[null]	0	0	0	1	0	0	0	0	0	1	0	0	0	0	0	0	0	0
70	0.84159476919	-0.78585928738	O'Brien, Mr. Thomas	male	[null]	0.48110389878	-0.444829492449	370365	-0.34381640576827904	[null]	Q	[null]	[null]	[null]	0	0	0	0	1	0	0	0	0	1	0	0	0	0	0	0	0	1
71	0.84159476919	-0.78585928738	O'Brien, Mr. Timothy	male	[null]	-0.47890372851	-0.444829492449	330979	-0.49201960072981904	[null]	Q	[null]	[null]	[null]	0	0	0	1	0	0	0	0	0	1	0	0	0	0	0	0	0	1
72	0.84159476919	1.27152032699	O'Brien, Mrs. Thomas (Johanna "Hannah" Godfrey)	female	[null]	0.48110389878	-0.444829492449	370365	-0.34381640576827904	[null]	Q	[null]	[null]	[null]	0	0	1	0	1	0	0	0	0	1	0	0	0	0	0	0	0	1
73	0.84159476919	-0.78585928738	O'Connell, Mr. Patrick D	male	[null]	-0.47890372851	-0.444829492449	334912	-0.49387243047336754	[null]	Q	[null]	[null]	[null]	0	0	0	1	0	0	0	0	0	1	0	0	0	0	0	0	0	1
74	0.84159476919	-0.78585928738	O'Connor, Mr. Maurice	male	[null]	-0.47890372851	-0.444829492449	371060	-0.4935497792041573	[null]	Q	[null]	[null]	[null]	0	0	0	1	0	0	0	0	0	1	0	0	0	0	0	0	0	1
75	0.84159476919	-0.78585928738	O'Connor, Mr. Patrick	male	[null]	-0.47890372851	-0.444829492449	366713	-0.4935497792041573	[null]	Q	[null]	[null]	[null]	0	0	0	1	0	0	0	0	0	1	0	0	0	0	0	0	0	1
76	0.84159476919	-0.78585928738	Odahl, Mr. Nils Martin	male	-0.4774094361749155	-0.47890372851	-0.444829492449	7267	-0.4650521371631353	[null]	S	[null]	[null]	[null]	0	0	0	1	0	0	0	0	0	1	0	0	0	0	0	0	0	0
77	0.84159476919	-0.78585928738	O'Donoghue, Ms. Bridget	female	[null]	-0.47890372851	-0.444829492449	364856	-0.4935497792041573	[null]	Q	[null]	[null]	[null]	0	0	1	1	0	0	0	0	0	1	0	0	0	0	0	0	0	1
78	0.84159476919	1.27152032699	O'Driscoll, Miss. Bridget	female	[null]	-0.47890372851	-0.444829492449	14311	-0.4935497792041573	[null]	Q	D	[null]	[null]	0	0	1	1	0	0	0	0	0	1	0	0	0	0	0	0	0	1
79	0.84159476919	1.27152032699	O'Dwyer, Miss. Ellen "Nellie"	female	[null]	-0.47890372851	-0.444829492449	330959	-0.4910535789657166	[null]	Q	[null]	[null]	[null]	0	0	1	1	0	0	0	0	0	1	0	0	0	0	0	0	0	1
80	0.84159476919	1.27152032699	Ohman, Miss. Velin	female	-0.5467888701082525	-0.47890372851	-0.444829492449	347085	-0.4930667683221061	[null]	S	C	[null]	[null]	0	0	1	1	0	0	0	0	0	1	0	0	0	0	0	0	0	0
81	0.84159476919	1.27152032699	O'Keefe, Mr. Patrick	male	[null]	-0.47890372851	-0.444829492449	368402	-0.4935497792041573	[null]	Q	B	[null]	[null]	0	0	0	1	0	0	0	0	0	1	0	0	0	0	0	0	0	1
82	0.84159476919	1.27152032699	O'Leary, Miss. Hanora "Norah"	female	[null]	-0.47890372851	-0.444829492449	330919	-0.49201960072981904	[null]	Q	13	[null]	[null]	0	0	1	1	0	0	0	0	0	1	0	0	0	0	0	0	0	1
83	0.84159476919	1.27152032699	Olsen, Master. Artur Karl	male	-1.448721511241633	-0.47890372851	0.71049155044	C 17368	-0.5820219164477153	[null]	S	13	[null]	[null]	0	0	0	1	0	0	0	0	0	0	1	0	0	0	0	0	0	0
84	0.84159476919	-0.78585928738	Olsen, Mr. Henry Margido	male	-0.13051226650823067	-0.47890372851	-0.444829492449	C 4001	-0.20809034791188621	[null]	S	[null]	0.1247744800509	[null]	0	0	0	1	0	0	0	0	0	1	0	0	0	0	0	0	0	0
85	0.84159476919	-0.78585928738	Olsen, Mr. Karl Siegwart Andreas	male	0.8407998085584869	-0.47890372851	0.71049155044	4579	-0.480910350442641	[null]	S	[null]	[null]	[null]	0	0	0	1	0	0	0	0	0	0	1	0	0	0	0	0	0	0
86	0.84159476919	-0.78585928738	Olsen, Mr. Ole Martin	male	[null]	-0.47890372851	-0.444829492449	Fa 265302	-0.5020024696400537	[null]	S	[null]	[null]	[null]	0	0	0	1	0	0	0	0	0	1	0	0	0	0	0	0	0	0
87	0.84159476919	-0.78585928738	Olsson, Miss. Elina	female	0.07762603529178022	-0.47890372851	-0.444829492449	350407	-0.4915365898477679	[null]	S	[null]	[null]	[null]	0	0	1	1	0	0	0	0	0	1	0	0	0	0	0	0	0	0
88	0.84159476919	-0.78585928738	Olsson, Mr. Nils Johan Goransson	male	-0.13051226650823067	-0.47890372851	-0.444829492449	347464	-0.4915365898477679	[null]	S	[null]	[null]	[null]	0	0	0	1	0	0	0	0	0	1	0	0	0	0	0	0	0	0
89	0.84159476919	1.27152032699	Olsson, Mr. Oscar Wilhelm	male	0.1470054692251172	-0.47890372851	-0.444829492449	347079	-0.4930667683221061	[null]	S	A	[null]	[null]	0	0	0	1	0	0	0	0	0	1	0	0	0	0	0	0	0	0
90	0.84159476919	-0.78585928738	Olsvigen, Mr. Thor Anderson	male	-0.6855477379749264	-0.47890372851	-0.444829492449	6563	-0.4650521371631353	[null]	S	[null]	-0.7350274285848	Oslo, Norway Cameron, WI	0	0	0	1	0	0	0	0	0	1	0	0	0	0	0	0	0	0
91	0.84159476919	-0.78585928738	Oreskovic, Miss. Jelka	female	-0.4774094361749155	-0.47890372851	-0.444829492449	315085	-0.47591988200928775	[null]	S	[null]	[null]	[null]	0	0	1	1	0	0	0	0	0	1	0	0	0	0	0	0	0	0
92	0.84159476919	-0.78585928738	Oreskovic, Miss. Marija	female	-0.6855477379749264	-0.47890372851	-0.444829492449	315096	-0.47591988200928775	[null]	S	[null]	[null]	[null]	0	0	1	1	0	0	0	0	0	1	0	0	0	0	0	0	0	0
93	0.84159476919	-0.78585928738	Oreskovic, Mr. Luka	male	-0.6855477379749264	-0.47890372851	-0.444829492449	315094	-0.47591988200928775	[null]	S	[null]	[null]	[null]	0	0	0	1	0	0	0	0	0	1	0	0	0	0	0	0	0	0
94	0.84159476919	-0.78585928738	Osen, Mr. Olaf Elon	male	-0.9630654737082742	-0.47890372851	-0.444829492449	7534	-0.46521249677597637	[null]	S	[null]	[null]	[null]	0	0	0	1	0	0	0	0	0	1	0	0	0	0	0	0	0	0
95	0.84159476919	1.27152032699	Osman, Mrs. Mara	female	0.07762603529178022	-0.47890372851	-0.444829492449	349244	-0.4755180169554212	[null]	S	[null]	[null]	[null]	0	0	1	1	0	0	0	0	0	1	0	0	0	0	0	0	0	0
96	0.84159476919	-0.78585928738	O'Sullivan, Miss. Bridget Mary	female	[null]	-0.47890372851	-0.444829492449	330909	-0.4958836877862288	[null]	Q	[null]	[null]	[null]	0	0	1	1	0	0	0	0	0	1	0	0	0	0	0	0	0	1
97	0.84159476919	-0.78585928738	Palsson, Master. Gosta Leonard	male	-1.934377548774992	2.40111915335	0.71049155044	349909	-0.23610497907085695	[null]	S	[null]	-1.6050650742281	[null]	0	0	0	0	0	0	1	0	0	0	1	0	0	0	0	0	0	0
98	0.84159476919	-0.78585928738	Palsson, Master. Paul Folke	male	-1.6568598130416439	2.40111915335	0.71049155044	349909	-0.23610497907085695	[null]	S	[null]	[null]	[null]	0	0	0	0	0	0	1	0	0	0	1	0	0	0	0	0	0	0
99	0.84159476919	-0.78585928738	Palsson, Miss. Stina Viola	female	-1.8649981148416548	2.40111915335	0.71049155044	349909	-0.23610497907085695	[null]	S	[null]	[null]	[null]	0	0	1	0	0	0	1	0	0	0	1	0	0	0	0	0	0	0
100	0.84159476919	-0.78585928738	Palsson, Miss. Torborg Danira	female	-1.51810094517497	2.40111915335	0.71049155044	349909	-0.23610497907085695	[null]	S	[null]	[null]	[null]	0	0	1	0	0	0	1	0	0	0	1	0	0	0	0	0	0	0

Rows: 1-100 of 1309 | Columns: 32

Let’s save the result in the Database.

data.to_db(
    name = '"default"."data_normalized"',
    usecols = ["fare", "sex", "survived"],
    relation_type = "table",
)
vo.VastFrame('"default"."data_normalized"')

	123 fare Double	Abc sex Varchar(20)	123 survived Decimal(38, 11)
1	-0.4935497792041573	male	1.27152032699
2	-0.1940830323324008	female	1.27152032699
3	-0.1940830323324008	female	1.27152032699
4	-0.1940830323324008	male	1.27152032699
5	-0.4928252628810805	female	1.27152032699
6	-0.34381640576827904	male	-0.78585928738
7	-0.4910535789657166	female	1.27152032699
8	-0.4881555136734093	female	1.27152032699
9	-0.4935497792041573	female	-0.78585928738
10	-0.4935497792041573	male	-0.78585928738
11	-0.33222414459904975	male	-0.78585928738
12	-0.33222414459904975	female	-0.78585928738
13	-0.4935497792041573	female	-0.78585928738
14	-0.4877536486195427	female	-0.78585928738
15	-0.4877536486195427	female	-0.78585928738
16	-0.4877536486195427	male	-0.78585928738
17	-0.4935497792041573	male	-0.78585928738
18	-0.4930667683221061	male	1.27152032699
19	-0.4877536486195427	male	-0.78585928738
20	-0.4907328597400346	male	-0.78585928738
21	-0.4907328597400346	male	-0.78585928738
22	-0.4907328597400346	male	-0.78585928738
23	-0.4907328597400346	male	-0.78585928738
24	-0.4910535789657166	female	1.27152032699
25	-0.49548182273236224	male	-0.78585928738
26	-0.40226072249647665	male	1.27152032699
27	-0.40226072249647665	female	1.27152032699
28	-0.4877536486195427	male	-0.78585928738
29	-0.17669464057855688	female	1.27152032699
30	-0.17669464057855688	male	-0.78585928738
31	-0.4798651148938821	male	-0.78585928738
32	-0.4877536486195427	male	-0.78585928738
33	-0.4935497792041573	male	-0.78585928738
34	-0.4930667683221061	male	1.27152032699
35	-0.3487276604169759	male	1.27152032699
36	-0.3487276604169759	male	1.27152032699
37	-0.3487276604169759	female	1.27152032699
38	-0.5036118618990484	female	1.27152032699
39	-0.4877536486195427	male	-0.78585928738
40	-0.49387243047336754	female	1.27152032699
41	-0.4935497792041573	female	1.27152032699
42	-0.4877536486195427	male	-0.78585928738
43	-0.34381640576827904	female	1.27152032699
44	-0.34381640576827904	female	1.27152032699
45	-0.34381640576827904	female	1.27152032699
46	-0.4935497792041573	male	-0.78585928738
47	-0.4907328597400346	male	-0.78585928738
48	-0.5036930077272329	female	1.27152032699
49	-0.33914665656060783	female	1.27152032699
50	-0.33914665656060783	male	1.27152032699
51	-0.33914665656060783	female	1.27152032699
52	-0.4877536486195427	male	-0.78585928738
53	-0.4907328597400346	male	-0.78585928738
54	-0.5036118618990484	male	-0.78585928738
55	-0.4935497792041573	female	-0.78585928738
56	-0.4907328597400346	male	-0.78585928738
57	-0.42608861532982745	male	1.27152032699
58	-0.42608861532982745	female	1.27152032699
59	-0.49016870302979876	female	-0.78585928738
60	-0.4877536486195427	male	-0.78585928738
61	-0.4930667683221061	female	1.27152032699
62	-0.4915365898477679	female	1.27152032699
63	-0.4915365898477679	male	-0.78585928738
64	-0.5056250512554379	male	-0.78585928738
65	-0.49016870302979876	male	1.27152032699
66	-0.4925837574400549	male	-0.78585928738
67	-0.5036118618990484	male	-0.78585928738
68	-0.4935497792041573	female	1.27152032699
69	-0.5227719375682561	male	-0.78585928738
70	-0.34381640576827904	male	-0.78585928738
71	-0.49201960072981904	male	-0.78585928738
72	-0.34381640576827904	female	1.27152032699
73	-0.49387243047336754	male	-0.78585928738
74	-0.4935497792041573	male	-0.78585928738
75	-0.4935497792041573	male	-0.78585928738
76	-0.4650521371631353	male	-0.78585928738
77	-0.4935497792041573	female	-0.78585928738
78	-0.4935497792041573	female	1.27152032699
79	-0.4910535789657166	female	1.27152032699
80	-0.4930667683221061	female	1.27152032699
81	-0.4935497792041573	male	1.27152032699
82	-0.49201960072981904	female	1.27152032699
83	-0.5820219164477153	male	1.27152032699
84	-0.20809034791188621	male	-0.78585928738
85	-0.480910350442641	male	-0.78585928738
86	-0.5020024696400537	male	-0.78585928738
87	-0.4915365898477679	female	-0.78585928738
88	-0.4915365898477679	male	-0.78585928738
89	-0.4930667683221061	male	1.27152032699
90	-0.4650521371631353	male	-0.78585928738
91	-0.47591988200928775	female	-0.78585928738
92	-0.47591988200928775	female	-0.78585928738
93	-0.47591988200928775	male	-0.78585928738
94	-0.46521249677597637	male	-0.78585928738
95	-0.4755180169554212	female	1.27152032699
96	-0.4958836877862288	female	-0.78585928738
97	-0.23610497907085695	male	-0.78585928738
98	-0.23610497907085695	male	-0.78585928738
99	-0.23610497907085695	female	-0.78585928738
100	-0.23610497907085695	female	-0.78585928738

Rows: 1-100 | Columns: 3

Let’s add a split column in the final relation.

data.to_db(
    name = '"default"."data_norm_split"',
    usecols = ["fare", "sex", "survived"],
    relation_type = "table",
    nb_split = 3,
)
vo.VastFrame('"default"."data_norm_split"')

	123 fare Double	Abc sex Varchar(20)	123 survived Decimal(38, 11)	123 _vastorbit_split_ Integer
1	-0.4935497792041573	male	1.27152032699	1
2	-0.1940830323324008	female	1.27152032699	0
3	-0.1940830323324008	female	1.27152032699	0
4	-0.1940830323324008	male	1.27152032699	2
5	-0.4928252628810805	female	1.27152032699	0
6	-0.34381640576827904	male	-0.78585928738	1
7	-0.4910535789657166	female	1.27152032699	1
8	-0.4881555136734093	female	1.27152032699	0
9	-0.4935497792041573	female	-0.78585928738	0
10	-0.4935497792041573	male	-0.78585928738	2
11	-0.33222414459904975	male	-0.78585928738	1
12	-0.33222414459904975	female	-0.78585928738	2
13	-0.4935497792041573	female	-0.78585928738	1
14	-0.4877536486195427	female	-0.78585928738	0
15	-0.4877536486195427	female	-0.78585928738	1
16	-0.4877536486195427	male	-0.78585928738	1
17	-0.4935497792041573	male	-0.78585928738	1
18	-0.4930667683221061	male	1.27152032699	0
19	-0.4877536486195427	male	-0.78585928738	2
20	-0.4907328597400346	male	-0.78585928738	2
21	-0.4907328597400346	male	-0.78585928738	0
22	-0.4907328597400346	male	-0.78585928738	2
23	-0.4907328597400346	male	-0.78585928738	2
24	-0.4910535789657166	female	1.27152032699	1
25	-0.49548182273236224	male	-0.78585928738	2
26	-0.40226072249647665	male	1.27152032699	1
27	-0.40226072249647665	female	1.27152032699	2
28	-0.4877536486195427	male	-0.78585928738	1
29	-0.17669464057855688	female	1.27152032699	2
30	-0.17669464057855688	male	-0.78585928738	2
31	-0.4798651148938821	male	-0.78585928738	0
32	-0.4877536486195427	male	-0.78585928738	1
33	-0.4935497792041573	male	-0.78585928738	0
34	-0.4930667683221061	male	1.27152032699	2
35	-0.3487276604169759	male	1.27152032699	0
36	-0.3487276604169759	male	1.27152032699	2
37	-0.3487276604169759	female	1.27152032699	2
38	-0.5036118618990484	female	1.27152032699	1
39	-0.4877536486195427	male	-0.78585928738	0
40	-0.49387243047336754	female	1.27152032699	0
41	-0.4935497792041573	female	1.27152032699	1
42	-0.4877536486195427	male	-0.78585928738	0
43	-0.34381640576827904	female	1.27152032699	1
44	-0.34381640576827904	female	1.27152032699	0
45	-0.34381640576827904	female	1.27152032699	0
46	-0.4935497792041573	male	-0.78585928738	1
47	-0.4907328597400346	male	-0.78585928738	0
48	-0.5036930077272329	female	1.27152032699	2
49	-0.33914665656060783	female	1.27152032699	2
50	-0.33914665656060783	male	1.27152032699	1
51	-0.33914665656060783	female	1.27152032699	0
52	-0.4877536486195427	male	-0.78585928738	0
53	-0.4907328597400346	male	-0.78585928738	1
54	-0.5036118618990484	male	-0.78585928738	2
55	-0.4935497792041573	female	-0.78585928738	0
56	-0.4907328597400346	male	-0.78585928738	1
57	-0.42608861532982745	male	1.27152032699	0
58	-0.42608861532982745	female	1.27152032699	1
59	-0.49016870302979876	female	-0.78585928738	2
60	-0.4877536486195427	male	-0.78585928738	0
61	-0.4930667683221061	female	1.27152032699	0
62	-0.4915365898477679	female	1.27152032699	0
63	-0.4915365898477679	male	-0.78585928738	0
64	-0.5056250512554379	male	-0.78585928738	2
65	-0.49016870302979876	male	1.27152032699	1
66	-0.4925837574400549	male	-0.78585928738	0
67	-0.5036118618990484	male	-0.78585928738	2
68	-0.4935497792041573	female	1.27152032699	2
69	-0.5227719375682561	male	-0.78585928738	1
70	-0.34381640576827904	male	-0.78585928738	0
71	-0.49201960072981904	male	-0.78585928738	0
72	-0.34381640576827904	female	1.27152032699	2
73	-0.49387243047336754	male	-0.78585928738	1
74	-0.4935497792041573	male	-0.78585928738	0
75	-0.4935497792041573	male	-0.78585928738	1
76	-0.4650521371631353	male	-0.78585928738	2
77	-0.4935497792041573	female	-0.78585928738	0
78	-0.4935497792041573	female	1.27152032699	1
79	-0.4910535789657166	female	1.27152032699	1
80	-0.4930667683221061	female	1.27152032699	1
81	-0.4935497792041573	male	1.27152032699	2
82	-0.49201960072981904	female	1.27152032699	1
83	-0.5820219164477153	male	1.27152032699	0
84	-0.20809034791188621	male	-0.78585928738	2
85	-0.480910350442641	male	-0.78585928738	2
86	-0.5020024696400537	male	-0.78585928738	2
87	-0.4915365898477679	female	-0.78585928738	0
88	-0.4915365898477679	male	-0.78585928738	1
89	-0.4930667683221061	male	1.27152032699	2
90	-0.4650521371631353	male	-0.78585928738	2
91	-0.47591988200928775	female	-0.78585928738	0
92	-0.47591988200928775	female	-0.78585928738	2
93	-0.47591988200928775	male	-0.78585928738	1
94	-0.46521249677597637	male	-0.78585928738	1
95	-0.4755180169554212	female	1.27152032699	2
96	-0.4958836877862288	female	-0.78585928738	0
97	-0.23610497907085695	male	-0.78585928738	2
98	-0.23610497907085695	male	-0.78585928738	0
99	-0.23610497907085695	female	-0.78585928738	2
100	-0.23610497907085695	female	-0.78585928738	1

Rows: 1-100 | Columns: 4

Let’s use conditions to filter data.

data.to_db(
    name = '"default"."data_norm_filter"',
    usecols = ["fare", "sex", "survived"],
    relation_type = "table",
    db_filter = "sex = 'female'",
)
vo.VastFrame('"default"."data_norm_filter"')

	123 fare Double	Abc sex Varchar(20)	123 survived Decimal(38, 11)
1	-0.1940830323324008	female	1.27152032699
2	-0.1940830323324008	female	1.27152032699
3	-0.4928252628810805	female	1.27152032699
4	-0.4910535789657166	female	1.27152032699
5	-0.4881555136734093	female	1.27152032699
6	-0.4935497792041573	female	-0.78585928738
7	-0.33222414459904975	female	-0.78585928738
8	-0.4935497792041573	female	-0.78585928738
9	-0.4877536486195427	female	-0.78585928738
10	-0.4877536486195427	female	-0.78585928738
11	-0.4910535789657166	female	1.27152032699
12	-0.40226072249647665	female	1.27152032699
13	-0.17669464057855688	female	1.27152032699
14	-0.3487276604169759	female	1.27152032699
15	-0.5036118618990484	female	1.27152032699
16	-0.49387243047336754	female	1.27152032699
17	-0.4935497792041573	female	1.27152032699
18	-0.34381640576827904	female	1.27152032699
19	-0.34381640576827904	female	1.27152032699
20	-0.34381640576827904	female	1.27152032699
21	-0.5036930077272329	female	1.27152032699
22	-0.33914665656060783	female	1.27152032699
23	-0.33914665656060783	female	1.27152032699
24	-0.4935497792041573	female	-0.78585928738
25	-0.42608861532982745	female	1.27152032699
26	-0.49016870302979876	female	-0.78585928738
27	-0.4930667683221061	female	1.27152032699
28	-0.4915365898477679	female	1.27152032699
29	-0.4935497792041573	female	1.27152032699
30	-0.34381640576827904	female	1.27152032699
31	-0.4935497792041573	female	-0.78585928738
32	-0.4935497792041573	female	1.27152032699
33	-0.4910535789657166	female	1.27152032699
34	-0.4930667683221061	female	1.27152032699
35	-0.49201960072981904	female	1.27152032699
36	-0.4915365898477679	female	-0.78585928738
37	-0.47591988200928775	female	-0.78585928738
38	-0.47591988200928775	female	-0.78585928738
39	-0.4755180169554212	female	1.27152032699
40	-0.4958836877862288	female	-0.78585928738
41	-0.23610497907085695	female	-0.78585928738
42	-0.23610497907085695	female	-0.78585928738
43	-0.23610497907085695	female	-0.78585928738
44	0.1234966226162765	female	-0.78585928738
45	-0.37714415662981327	female	-0.78585928738
46	-0.37714415662981327	female	-0.78585928738
47	-0.21131106447340373	female	1.27152032699
48	-0.21131106447340373	female	1.27152032699
49	-0.48606311053236345	female	-0.78585928738
50	-0.4907328597400346	female	-0.78585928738
51	-0.4930667683221061	female	-0.78585928738
52	-0.4865461214144146	female	-0.78585928738
53	-0.08057547505036404	female	-0.78585928738
54	0.1234966226162765	female	-0.78585928738
55	-0.4941139359143931	female	1.27152032699
56	-0.36313684105032784	female	-0.78585928738
57	-0.36313684105032784	female	-0.78585928738
58	-0.25276885450162406	female	-0.78585928738
59	-0.25276885450162406	female	-0.78585928738
60	-0.4877536486195427	female	1.27152032699
61	0.700453121226459	female	-0.78585928738
62	0.700453121226459	female	-0.78585928738
63	0.700453121226459	female	-0.78585928738
64	0.700453121226459	female	-0.78585928738
65	0.700453121226459	female	-0.78585928738
66	-0.49548182273236224	female	1.27152032699
67	-0.3206318834298205	female	1.27152032699
68	-0.3206318834298205	female	1.27152032699
69	-0.3206318834298205	female	1.27152032699
70	-0.4929856224939215	female	1.27152032699
71	-0.4984610338528542	female	1.27152032699
72	-0.10424300827087386	female	-0.78585928738
73	-0.10424300827087386	female	-0.78585928738
74	-0.10424300827087386	female	-0.78585928738
75	-0.49387243047336754	female	1.27152032699
76	-0.49741386626056705	female	1.27152032699
77	-0.45321837055288045	female	-0.78585928738
78	-0.44114309850159994	female	-0.78585928738
79	-0.44114309850159994	female	-0.78585928738
80	-0.4787368014734105	female	1.27152032699
81	-0.33222414459904975	female	1.27152032699
82	-0.3487276604169759	female	1.27152032699
83	-0.3487276604169759	female	1.27152032699
84	-0.45313722472469586	female	1.27152032699
85	-0.45804847937339266	female	1.27152032699
86	-0.17669464057855688	female	-0.78585928738
87	-0.17669464057855688	female	-0.78585928738
88	-0.295515317563157	female	-0.78585928738
89	-0.295515317563157	female	-0.78585928738
90	-0.4915365898477679	female	-0.78585928738
91	-0.5036118618990484	female	1.27152032699
92	-0.5080401056656939	female	1.27152032699
93	-0.3640217169862457	female	1.27152032699
94	-0.3640217169862457	female	-0.78585928738
95	-0.3640217169862457	female	-0.78585928738
96	3.4398493387799545	female	1.27152032699
97	2.2847288143544615	female	-0.78585928738
98	2.2847288143544615	female	-0.78585928738
99	0.8629051372085099	female	1.27152032699
100	0.35131739933161144	female	1.27152032699

Rows: 1-100 | Columns: 3

Note

The VastFrame.to_db() method enables you to save the VastFrame into various types of relations, including views, temporary tables, and regular tables. It also allows for inserting elements into an existing table, as well as ordering the data using the order_by parameter.

See also

VastFrame.to_csv() : Creates a CSV file of the current VastFrame structure.

VastFrame.to_json() : Creates a JSON file of the current VastFrame structure.