vDataFrame.to_db¶

In [ ]:

vDataFrame.to_db(name: str,
                 usecols: list = [],
                 relation_type: str = "view",
                 inplace: bool = False,
                 db_filter = "",
                 nb_split: int = 0)

Saves the vDataFrame current relation to the Vertica Database. This method can also be used to materialize flex tables.

Parameters¶

Name	Type	Optional	Description
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	list	✓	vcolumns to select from the final vDataFrame relation. If empty, all the columns will be selected.
relation_type	str	✓	Type of the relation. view : View table : Table temporary : Temporary Table insert : Inserts into an existing table
inplace	bool	✓	If set to True, the vDataFrame will be replaced using the new relation.
db_filter	str / list	✓	Filter used before creating the relation in the DB. It can be a list of conditions or an expression. This parameter is very useful to create train and test sets on TS.
nb_split	int	✓	If this parameter is greater than 0, it will add to the final relation a new column '_vertica_ml\_python\_split_' which will contain values in [0;nb_split - 1] where each category will represent approximately 1 / nb_split of the entire distribution.

Returns¶

vDataFrame : self

Example¶

In [99]:

from verticapy.datasets import load_titanic
titanic = load_titanic()
# Doing some transformations
titanic.get_dummies()
titanic.normalize()

	123 fare Float	123 Float	Abc sex Varchar(20)	Abc boat Varchar(100)	123 pclass Float	123 age Float	Abc ticket Varchar(36)	Abc Varchar(164)	Abc embarked Varchar(20)	Abc cabin Varchar(30)	123 body Float	123 Float	Abc home.dest Varchar(100)	123 Float	123 Float	123 pclass_1 Float	123 Float	123 Float	123 embarked_Q Float	123 parch_0 Float	123 Float	123 Float	123 Float	123 Float	123 Float	123 Float	123 Float	123 sibsp_1 Float	123 Float	123 Float	123 Float	123 Float
1	2.2335228377568673306163744003		female	[null]	-1.52458485653939825566284767748	-1.9502503129565278908367342155	113781		S	C22 C26	[null]		Montreal, PQ / Chesterville, ON			1.718351957456489070218766430323			-0.30642369222116871970059157132	-1.82404116243169099688897026934								1.74835105897043756352888762989
2	2.2335228377568673306163744003		male	[null]	-1.52458485653939825566284767748	-0.0105614239550127329564098413	113781		S	C22 C26	-0.30177333429701812091999864		Montreal, PQ / Chesterville, ON			1.718351957456489070218766430323			-0.30642369222116871970059157132	-1.82404116243169099688897026934								1.74835105897043756352888762989
3	2.2335228377568673306163744003		female	[null]	-1.52458485653939825566284767748	-0.3569344398481404397207534796	113781		S	C22 C26	[null]		Montreal, PQ / Chesterville, ON			1.718351957456489070218766430323			-0.30642369222116871970059157132	-1.82404116243169099688897026934								1.74835105897043756352888762989
4	-0.6451344183800711827483251581		male	[null]	-1.52458485653939825566284767748	0.6129100046526171392194087075	112050		S	A36	[null]		Belfast, NI			1.718351957456489070218766430323			-0.30642369222116871970059157132	0.54778896869655520601485651247								-0.57150400207205686533461107422
5	0.2951864297839290254556257484		male	[null]	-1.52458485653939825566284767748	2.8296973063686344625112079923	PC 17609		C	[null]	-1.47183603843091257442431516		Montevideo, Uruguay			1.718351957456489070218766430323			-0.30642369222116871970059157132	0.54778896869655520601485651247								-0.57150400207205686533461107422
6	3.6766504196440590399722506719		male	[null]	-1.52458485653939825566284767748	1.1671068300816214700423585287	PC 17757		C	C62 C64	-0.41567324354899014736732149		New York, NY			1.718351957456489070218766430323			-0.30642369222116871970059157132	0.54778896869655520601485651247								1.74835105897043756352888762989
7	-0.1526950296281732549424535906		male	[null]	-1.52458485653939825566284767748	[null]	PC 17318		S	[null]	[null]		New York, NY			1.718351957456489070218766430323			-0.30642369222116871970059157132	0.54778896869655520601485651247								-0.57150400207205686533461107422
8	4.0564660234861111358187558479		male	[null]	-1.52458485653939825566284767748	-0.4262090430267659810736222072	PC 17558		C	B58 B60	[null]		Montreal, PQ			1.718351957456489070218766430323			-0.30642369222116871970059157132	-1.82404116243169099688897026934								-0.57150400207205686533461107422
9	0.7840642993307746538800662293		male	A	-1.52458485653939825566284767748	0.4050861951167405151608025246	13050		C	C6	[null]		Winnipeg, MN			1.718351957456489070218766430323			-0.30642369222116871970059157132	0.54778896869655520601485651247								-0.57150400207205686533461107422
10	-0.1512704219461523351898811560		male	[null]	-1.52458485653939825566284767748	-0.3569344398481404397207534796	13905		C	[null]	-0.16716435063559663511861709		San Francisco, CA			1.718351957456489070218766430323			-0.30642369222116871970059157132	0.54778896869655520601485651247								-0.57150400207205686533461107422
11	0.0291798844431641668026272294		male	[null]	-1.52458485653939825566284767748	1.0285576237243703873366210734	113784		S	T	[null]		Trenton, NJ			1.718351957456489070218766430323			-0.30642369222116871970059157132	0.54778896869655520601485651247								-0.57150400207205686533461107422
12	-0.1408232989446655903376833021		male	[null]	-1.52458485653939825566284767748	0.8207338141884937632780148905	110489		S	D22	[null]		London / Winnipeg, MB			1.718351957456489070218766430323			-0.30642369222116871970059157132	0.54778896869655520601485651247								-0.57150400207205686533461107422
13	-0.0657939610248971500355350787		male	[null]	-1.52458485653939825566284767748	0.7514592110098682219251461628	113054		S	A21	[null]		Pomeroy, WA			1.718351957456489070218766430323			-0.30642369222116871970059157132	0.54778896869655520601485651247								-0.57150400207205686533461107422
14	0.3140216428171549458109700973		male	[null]	-1.52458485653939825566284767748	1.2363814332602470113952272564	PC 17591		C	B10	0.45410788164788714550314389		Omaha, NE			1.718351957456489070218766430323			-0.30642369222116871970059157132	0.54778896869655520601485651247								-0.57150400207205686533461107422
15	0.1070584377269744466099203220		male	[null]	-1.52458485653939825566284767748	[null]	112379		C	[null]	[null]		Philadelphia, PA			1.718351957456489070218766430323			-0.30642369222116871970059157132	0.54778896869655520601485651247								-0.57150400207205686533461107422
16	-0.1408232989446655903376833021		male	[null]	-1.52458485653939825566284767748	1.0285576237243703873366210734	113050		S	B38	[null]		Washington, DC			1.718351957456489070218766430323			-0.30642369222116871970059157132	0.54778896869655520601485651247								-0.57150400207205686533461107422
17	-0.0562965764780910183517188479		male	[null]	-1.52458485653939825566284767748	[null]	113798		S	[null]	[null]		[null]			1.718351957456489070218766430323			-0.30642369222116871970059157132	0.54778896869655520601485651247								-0.57150400207205686533461107422
18	-0.5501605729120098659101628500		male	[null]	-1.52458485653939825566284767748	0.1972623855808638911021963416	695		S	B51 B53 B55	[null]		New York, NY			1.718351957456489070218766430323			-0.30642369222116871970059157132	0.54778896869655520601485651247								-0.57150400207205686533461107422
19	0.2495192059290664218671637842		male	[null]	-1.52458485653939825566284767748	-0.1491106303122638156621472966	113059		S	[null]	[null]		Montevideo, Uruguay			1.718351957456489070218766430323			-0.30642369222116871970059157132	0.54778896869655520601485651247								-0.57150400207205686533461107422
20	0.2495192059290664218671637842		male	[null]	-1.52458485653939825566284767748	-0.9111312652771447705437033008	113059		S	[null]	[null]		Montevideo, Uruguay			1.718351957456489070218766430323			-0.30642369222116871970059157132	0.54778896869655520601485651247								-0.57150400207205686533461107422
21	-0.1512704219461523351898811560		male	[null]	-1.52458485653939825566284767748	1.3056560364388725527480959840	19924		S	[null]	[null]		Ascot, Berkshire / Rochester, NY			1.718351957456489070218766430323			-0.30642369222116871970059157132	0.54778896869655520601485651247								-0.57150400207205686533461107422
22	0.8526031246512557837894944406		male	[null]	-1.52458485653939825566284767748	0.4050861951167405151608025246	19877		S	C46	0.08134454227779687713008730		Little Onn Hall, Staffs			1.718351957456489070218766430323			-0.30642369222116871970059157132	0.54778896869655520601485651247								1.74835105897043756352888762989
23	0.5168705809216590287665906814		male	[null]	-1.52458485653939825566284767748	1.0978322269029959286894898011	W.E.P. 5734		S	E31	[null]		Amenia, ND			1.718351957456489070218766430323			-0.30642369222116871970059157132	0.54778896869655520601485651247								1.74835105897043756352888762989
24	-0.6451344183800711827483251581		male	[null]	-1.52458485653939825566284767748	[null]	112051		S	[null]	[null]		Liverpool, England / Belfast			1.718351957456489070218766430323			-0.30642369222116871970059157132	0.54778896869655520601485651247								-0.57150400207205686533461107422
25	1.9529549024289393108657488362		male	[null]	-1.52458485653939825566284767748	-0.2183852334908893570150160243	13508		C	C89	[null]		Los Angeles, CA			1.718351957456489070218766430323			-0.30642369222116871970059157132	0.54778896869655520601485651247								1.74835105897043756352888762989
26	0.3425935744877665123685628461		male	[null]	-1.52458485653939825566284767748	[null]	110465		S	A14	[null]		Stoughton, MA			1.718351957456489070218766430323			-0.30642369222116871970059157132	0.54778896869655520601485651247								-0.57150400207205686533461107422
27	-0.1591057641972673938290295464		male	[null]	-1.52458485653939825566284767748	1.1671068300816214700423585287	5727		S	E58	[null]		Victoria, BC			1.718351957456489070218766430323			-0.30642369222116871970059157132	0.54778896869655520601485651247								-0.57150400207205686533461107422
28	0.9344382883372654980562653750		male	[null]	-1.52458485653939825566284767748	0.4743607982953660565136712522	PC 17756		C	E52	[null]		Lakewood, NJ			1.718351957456489070218766430323			-0.30642369222116871970059157132	-1.82404116243169099688897026934								1.74835105897043756352888762989
29	-0.1408232989446655903376833021		male	[null]	-1.52458485653939825566284767748	[null]	113791		S	[null]	[null]		Roachdale, IN			1.718351957456489070218766430323			-0.30642369222116871970059157132	0.54778896869655520601485651247								-0.57150400207205686533461107422
30	0.7034941872663995163535796169		male	[null]	-1.52458485653939825566284767748	2.7604227031900089211583392647	WE/P 5735		S	B22	1.08573465113609565580193423		Milwaukee, WI			1.718351957456489070218766430323			-0.30642369222116871970059157132	-1.82404116243169099688897026934								1.74835105897043756352888762989
31	0.7088754053506198705656298932		male	[null]	-1.52458485653939825566284767748	0.6129100046526171392194087075	PC 17599		C	C85	[null]		New York, NY			1.718351957456489070218766430323			-0.30642369222116871970059157132	0.54778896869655520601485651247								1.74835105897043756352888762989
32	0.3425935744877665123685628461		male	[null]	-1.52458485653939825566284767748	0.0587131792236128083964588863	F.C. 12750		S	B71	[null]		Montreal, PQ			1.718351957456489070218766430323			-0.30642369222116871970059157132	0.54778896869655520601485651247								1.74835105897043756352888762989
33	1.3763838824076139461519595697		male	[null]	-1.52458485653939825566284767748	1.3749306396174980941009647117	PC 17761		C	C86	-1.05765455024192338734314117		Deephaven, MN / Cedar Rapids, IA			1.718351957456489070218766430323			-0.30642369222116871970059157132	0.54778896869655520601485651247								1.74835105897043756352888762989
34	-0.0809897762997869607296410480		male	[null]	-1.52458485653939825566284767748	0.6129100046526171392194087075	PC 17580		C	A18	-0.32248240870646758027405734		Philadelphia, PA			1.718351957456489070218766430323			-0.30642369222116871970059157132	0.54778896869655520601485651247								-0.57150400207205686533461107422
35	-0.0433953293097095690724228800		female	[null]	-1.52458485653939825566284767748	0.4050861951167405151608025246	PC 17531		C	A29	[null]		New York, NY			1.718351957456489070218766430323			-0.30642369222116871970059157132	0.54778896869655520601485651247								-0.57150400207205686533461107422
36	3.5675102753859816971145080739		male	[null]	-1.52458485653939825566284767748	[null]	PC 17483		S	C95	[null]		[null]			1.718351957456489070218766430323			-0.30642369222116871970059157132	0.54778896869655520601485651247								-0.57150400207205686533461107422
37	-0.1180295760323308742965243482		male	[null]	-1.52458485653939825566284767748	-0.0105614239550127329564098413	113051		C	C111	[null]		New York, NY			1.718351957456489070218766430323			-0.30642369222116871970059157132	0.54778896869655520601485651247								-0.57150400207205686533461107422
38	4.3504898532399540829390122478		male	[null]	-1.52458485653939825566284767748	-0.7725820589198936878379658455	19950		S	C23 C25 C27	[null]		Winnipeg, MB			1.718351957456489070218766430323			-0.30642369222116871970059157132	-1.82404116243169099688897026934								-0.57150400207205686533461107422
39	4.3504898532399540829390122478		male	[null]	-1.52458485653939825566284767748	2.3447750841182556730411268988	19950		S	C23 C25 C27	[null]		Winnipeg, MB			1.718351957456489070218766430323			-0.30642369222116871970059157132	-1.82404116243169099688897026934								1.74835105897043756352888762989
40	-0.1408232989446655903376833021		male	[null]	-1.52458485653939825566284767748	[null]	113778		S	D34	[null]		Westcliff-on-Sea, Essex			1.718351957456489070218766430323			-0.30642369222116871970059157132	0.54778896869655520601485651247								-0.57150400207205686533461107422
41	-0.6451344183800711827483251581		male	[null]	-1.52458485653939825566284767748	[null]	112058		S	B102	[null]		[null]			1.718351957456489070218766430323			-0.30642369222116871970059157132	0.54778896869655520601485651247								-0.57150400207205686533461107422
42	0.3634878204907400020729585539		male	[null]	-1.52458485653939825566284767748	0.4743607982953660565136712522	113803		S	C123	[null]		Scituate, MA			1.718351957456489070218766430323			-0.30642369222116871970059157132	0.54778896869655520601485651247								1.74835105897043756352888762989
43	0.0861641917240009569055246142		male	[null]	-1.52458485653939825566284767748	1.1671068300816214700423585287	111320		S	E63	1.14786187436444403386411033		St Anne's-on-Sea, Lancashire			1.718351957456489070218766430323			-0.30642369222116871970059157132	0.54778896869655520601485651247								-0.57150400207205686533461107422
44	0.8592512938340200759681658021		male	[null]	-1.52458485653939825566284767748	-0.4262090430267659810736222072	PC 17593		C	B86	[null]		[null]			1.718351957456489070218766430323			-0.30642369222116871970059157132	0.54778896869655520601485651247								-0.57150400207205686533461107422
45	0.0131141087437869144462836933		male	[null]	-1.52458485653939825566284767748	2.8296973063686344625112079923	PC 17754		C	A5	[null]		New York, NY			1.718351957456489070218766430323			-0.30642369222116871970059157132	0.54778896869655520601485651247								-0.57150400207205686533461107422
46	2.2698503336484007843069714832		male	[null]	-1.52458485653939825566284767748	0.5436354014739915978665399799	PC 17582		S	C91	-0.17751888784032136479564644		Winnipeg, MB			1.718351957456489070218766430323			-0.30642369222116871970059157132	-1.82404116243169099688897026934								-0.57150400207205686533461107422
47	0.8592512938340200759681658021		male	[null]	-1.52458485653939825566284767748	1.0978322269029959286894898011	PC 17593		C	B82 B84	[null]		New York, NY			1.718351957456489070218766430323			-0.30642369222116871970059157132	0.54778896869655520601485651247								-0.57150400207205686533461107422
48	0.1602437911890887840392912145		male	[null]	-1.52458485653939825566284767748	[null]	113796		S	[null]	[null]		[null]			1.718351957456489070218766430323			-0.30642369222116871970059157132	0.54778896869655520601485651247								-0.57150400207205686533461107422
49	0.9404539317092125018647945756		male	[null]	-1.52458485653939825566284767748	1.0285576237243703873366210734	36973		S	C83	[null]		New York, NY			1.718351957456489070218766430323			-0.30642369222116871970059157132	0.54778896869655520601485651247								1.74835105897043756352888762989
50	-0.6451344183800711827483251581		male	[null]	-1.52458485653939825566284767748	0.6821846078312426805722774352	112059		S	B94	-0.56063676441513636284573238		[null]			1.718351957456489070218766430323			-0.30642369222116871970059157132	0.54778896869655520601485651247								-0.57150400207205686533461107422
51	1.1308764918726754421253100033		male	[null]	-1.52458485653939825566284767748	1.7213036555106258008653083499	12749		S	B69	1.47920706491563538352904952		Montreal, PQ			1.718351957456489070218766430323			-0.30642369222116871970059157132	-1.82404116243169099688897026934								1.74835105897043756352888762989
52	0.1621432680984500103760544607		male	[null]	-1.52458485653939825566284767748	0.8207338141884937632780148905	113038		S	B11	[null]		London / Middlesex			1.718351957456489070218766430323			-0.30642369222116871970059157132	0.54778896869655520601485651247								-0.57150400207205686533461107422
53	0.3399817937373948261555133826		male	[null]	-1.52458485653939825566284767748	[null]	17463		S	E46	[null]		Brighton, MA			1.718351957456489070218766430323			-0.30642369222116871970059157132	0.54778896869655520601485651247								-0.57150400207205686533461107422
54	0.3046040363005419856332979228		male	[null]	-1.52458485653939825566284767748	1.7213036555106258008653083499	680		S	C39	[null]		London / Birmingham			1.718351957456489070218766430323			-0.30642369222116871970059157132	0.54778896869655520601485651247								-0.57150400207205686533461107422
55	0.3425935744877665123685628461		male	[null]	-1.52458485653939825566284767748	0.8207338141884937632780148905	113789		S	[null]	-1.30616344315531689959184557		New York, NY			1.718351957456489070218766430323			-0.30642369222116871970059157132	0.54778896869655520601485651247								1.74835105897043756352888762989
56	-0.0620747852363678688681526427		male	14	-1.52458485653939825566284767748	[null]	PC 17600		C	[null]	[null]		New York, NY			1.718351957456489070218766430323			-0.30642369222116871970059157132	0.54778896869655520601485651247								-0.57150400207205686533461107422
57	-0.0997471107797290708051781039		female	[null]	-1.52458485653939825566284767748	1.3749306396174980941009647117	PC 17595		C	C49	[null]		Paris, France New York, NY			1.718351957456489070218766430323			-0.30642369222116871970059157132	0.54778896869655520601485651247								-0.57150400207205686533461107422
58	-0.1512704219461523351898811560		male	[null]	-1.52458485653939825566284767748	1.0978322269029959286894898011	694		S	[null]	-0.87127288055687825315661288		Bennington, VT			1.718351957456489070218766430323			-0.30642369222116871970059157132	0.54778896869655520601485651247								-0.57150400207205686533461107422
59	-0.1512704219461523351898811560		male	[null]	-1.52458485653939825566284767748	1.3749306396174980941009647117	113044		S	E60	[null]		London			1.718351957456489070218766430323			-0.30642369222116871970059157132	0.54778896869655520601485651247								-0.57150400207205686533461107422
60	3.3722592449189225195059404744		male	[null]	-1.52458485653939825566284767748	0.1626250839915511204257619778	113503		C	C132	-1.23368168272224379185264012		[null]			1.718351957456489070218766430323			-0.30642369222116871970059157132	0.54778896869655520601485651247								-0.57150400207205686533461107422
61	-0.0809897762997869607296410480		male	[null]	-1.52458485653939825566284767748	1.9291274650465024249239145329	11771		C	B37	0.97183474188412362935461138		Buffalo, NY			1.718351957456489070218766430323			-0.30642369222116871970059157132	0.54778896869655520601485651247								-0.57150400207205686533461107422
62	0.3399817937373948261555133826		male	[null]	-1.52458485653939825566284767748	0.7514592110098682219251461628	17464		S	D21	[null]		Southington / Noank, CT			1.718351957456489070218766430323			-0.30642369222116871970059157132	0.54778896869655520601485651247								1.74835105897043756352888762989
63	-0.1408232989446655903376833021		male	[null]	-1.52458485653939825566284767748	[null]	113028		S	C124	[null]		Portland, OR			1.718351957456489070218766430323			-0.30642369222116871970059157132	0.54778896869655520601485651247								-0.57150400207205686533461107422
64	-0.1185842232898643523868592161		male	[null]	-1.52458485653939825566284767748	[null]	PC 17612		C	[null]	[null]		Chicago, IL			1.718351957456489070218766430323			-0.30642369222116871970059157132	0.54778896869655520601485651247								-0.57150400207205686533461107422
65	-0.0752913455717032817193513095		male	[null]	-1.52458485653939825566284767748	-0.0798360271336382743092785690	113501		S	D6	-0.39496416913954068801326279		Springfield, MA			1.718351957456489070218766430323			-0.30642369222116871970059157132	0.54778896869655520601485651247								-0.57150400207205686533461107422
66	0.2191275753792868004789518456		male	[null]	-1.52458485653939825566284767748	-0.0105614239550127329564098413	113801		S	[null]	[null]		London / New York, NY			1.718351957456489070218766430323			-0.30642369222116871970059157132	0.54778896869655520601485651247								-0.57150400207205686533461107422
67	-0.1512704219461523351898811560		male	[null]	-1.52458485653939825566284767748	-0.0105614239550127329564098413	110469		S	C106	[null]		Brockton, MA			1.718351957456489070218766430323			-0.30642369222116871970059157132	0.54778896869655520601485651247								-0.57150400207205686533461107422
68	0.3634878204907400020729585539		male	[null]	-1.52458485653939825566284767748	-0.7725820589198936878379658455	113773		S	D30	[null]		New York, NY			1.718351957456489070218766430323			-0.30642369222116871970059157132	0.54778896869655520601485651247								1.74835105897043756352888762989
69	0.7840642993307746538800662293		male	[null]	-1.52458485653939825566284767748	1.0978322269029959286894898011	13050		C	C6	1.32388900684476443837360928		Vancouver, BC			1.718351957456489070218766430323			-0.30642369222116871970059157132	0.54778896869655520601485651247								-0.57150400207205686533461107422
70	0.3399817937373948261555133826		male	[null]	-1.52458485653939825566284767748	1.6520290523320002595124396223	17463		S	E46	0.11240815389197106616117535		Dorchester, MA			1.718351957456489070218766430323			-0.30642369222116871970059157132	0.54778896869655520601485651247								-0.57150400207205686533461107422
71	0.9156809538573233879807283191		male	[null]	-1.52458485653939825566284767748	-0.1491106303122638156621472966	PC 17604		C	[null]	[null]		New York, NY			1.718351957456489070218766430323			-0.30642369222116871970059157132	0.54778896869655520601485651247								1.74835105897043756352888762989
72	-0.1408232989446655903376833021		male	[null]	-1.52458485653939825566284767748	2.4140496872968812143939956264	13509		S	E38	0.87864390704160106226134724		East Bridgewater, MA			1.718351957456489070218766430323			-0.30642369222116871970059157132	0.54778896869655520601485651247								-0.57150400207205686533461107422
73	1.0643948000450325203385963876		male	[null]	-1.52458485653939825566284767748	0.9592830205457448459837523458	19928		Q	C78	0.68190770015183119839778959		Fond du Lac, WI			1.718351957456489070218766430323			3.26081061156111681295118247921	0.54778896869655520601485651247								-0.57150400207205686533461107422
74	-0.0657939610248971500355350787		male	[null]	-1.52458485653939825566284767748	1.7213036555106258008653083499	113787		S	C30	[null]		Montreal, PQ			1.718351957456489070218766430323			-0.30642369222116871970059157132	0.54778896869655520601485651247								-0.57150400207205686533461107422
75	0.1602437911890887840392912145		male	[null]	-1.52458485653939825566284767748	1.1671068300816214700423585287	113796		S	[null]	[null]		Washington, DC			1.718351957456489070218766430323			-0.30642369222116871970059157132	0.54778896869655520601485651247								-0.57150400207205686533461107422
76	-0.0809897762997869607296410480		male	[null]	-1.52458485653939825566284767748	0.4743607982953660565136712522	PC 17596		C	C118	[null]		Brooklyn, NY			1.718351957456489070218766430323			-0.30642369222116871970059157132	-1.82404116243169099688897026934								-0.57150400207205686533461107422
77	1.5064980506988579502202419318		male	[null]	-1.52458485653939825566284767748	1.9291274650465024249239145329	35273		C	D48	-0.43638231795843960672138019		Lexington, MA			1.718351957456489070218766430323			-0.30642369222116871970059157132	-1.82404116243169099688897026934								-0.57150400207205686533461107422
78	-0.1512704219461523351898811560		male	[null]	-1.52458485653939825566284767748	2.3447750841182556730411268988	693		S	[null]	1.02360742790774727773975813		Isle of Wight, England			1.718351957456489070218766430323			-0.30642369222116871970059157132	0.54778896869655520601485651247								-0.57150400207205686533461107422
79	0.5321461742267420109668407071		male	[null]	-1.52458485653939825566284767748	2.4140496872968812143939956264	113509		C	B30	0.72332584897073011710590699		Providence, RI			1.718351957456489070218766430323			-0.30642369222116871970059157132	-1.82404116243169099688897026934								-0.57150400207205686533461107422
80	-0.1185842232898643523868592161		male	[null]	-1.52458485653939825566284767748	-0.1144733287229510449857129328	PC 17562		C	D43	0.25737167475811728163958625		?Havana, Cuba			1.718351957456489070218766430323			-0.30642369222116871970059157132	0.54778896869655520601485651247								-0.57150400207205686533461107422
81	-0.6451344183800711827483251581		male	[null]	-1.52458485653939825566284767748	[null]	112052		S	[null]	[null]		Belfast			1.718351957456489070218766430323			-0.30642369222116871970059157132	0.54778896869655520601485651247								-0.57150400207205686533461107422
82	-0.1037834992121216767708000020		male	[null]	-1.52458485653939825566284767748	1.0631949253136831580130554372	113043		S	C124	0.01921731904944849906791120		Surbiton Hill, Surrey			1.718351957456489070218766430323			-0.30642369222116871970059157132	0.54778896869655520601485651247								-0.57150400207205686533461107422
83	1.1308764918726754421253100033		male	[null]	-1.52458485653939825566284767748	-0.4954836462053915224264909349	12749		S	B24	[null]		Montreal, PQ			1.718351957456489070218766430323			-0.30642369222116871970059157132	0.54778896869655520601485651247								-0.57150400207205686533461107422
84	0.6199172032545055575359967857		male	[null]	-1.52458485653939825566284767748	-0.0798360271336382743092785690	113776		S	C2	[null]		Isleworth, England			1.718351957456489070218766430323			-0.30642369222116871970059157132	0.54778896869655520601485651247								1.74835105897043756352888762989
85	1.4233959359143042979868499122		male	[null]	-1.52458485653939825566284767748	-0.8418566620985192291908345731	PC 17758		C	C65	[null]		Madrid, Spain			1.718351957456489070218766430323			-0.30642369222116871970059157132	0.54778896869655520601485651247								1.74835105897043756352888762989
86	0.3425935744877665123685628461		male	[null]	-1.52458485653939825566284767748	1.1671068300816214700423585287	110465		S	C110	0.44375334444316241582611455		Worcester, MA			1.718351957456489070218766430323			-0.30642369222116871970059157132	0.54778896869655520601485651247								-0.57150400207205686533461107422
87	-0.6451344183800711827483251581		male	[null]	-1.52458485653939825566284767748	0.5436354014739915978665399799	19972		S	[null]	[null]		Rotterdam, Netherlands			1.718351957456489070218766430323			-0.30642369222116871970059157132	0.54778896869655520601485651247								-0.57150400207205686533461107422
88	1.9311887965245690182727787985		male	[null]	-1.52458485653939825566284767748	-0.5647582493840170637793596625	PC 17760		C	[null]	0.70261677456128065775184829		[null]			1.718351957456489070218766430323			-0.30642369222116871970059157132	0.54778896869655520601485651247								-0.57150400207205686533461107422
89	3.6766504196440590399722506719		male	[null]	-1.52458485653939825566284767748	[null]	PC 17757		C	[null]	[null]		[null]			1.718351957456489070218766430323			-0.30642369222116871970059157132	0.54778896869655520601485651247								-0.57150400207205686533461107422
90	0.3140216428171549458109700973		male	[null]	-1.52458485653939825566284767748	0.0587131792236128083964588863	PC 17590		S	A24	[null]		Trenton, NJ			1.718351957456489070218766430323			-0.30642369222116871970059157132	0.54778896869655520601485651247								-0.57150400207205686533461107422
91	0.3046040363005419856332979228		male	[null]	-1.52458485653939825566284767748	[null]	113767		S	A32	[null]		Seattle, WA			1.718351957456489070218766430323			-0.30642369222116871970059157132	0.54778896869655520601485651247								-0.57150400207205686533461107422
92	0.1170306915011208848779273644		male	[null]	-1.52458485653939825566284767748	0.4050861951167405151608025246	13049		C	A10	[null]		Winnipeg, MB			1.718351957456489070218766430323			-0.30642369222116871970059157132	0.54778896869655520601485651247								-0.57150400207205686533461107422
93	0.4831548657804972612890430621		male	[null]	-1.52458485653939825566284767748	1.7213036555106258008653083499	PC 17603		C	[null]	[null]		New York, NY			1.718351957456489070218766430323			-0.30642369222116871970059157132	0.54778896869655520601485651247								1.74835105897043756352888762989
94	-0.1408232989446655903376833021		male	[null]	-1.52458485653939825566284767748	0.1972623855808638911021963416	113790		S	[null]	-0.57099130161986109252276173		London			1.718351957456489070218766430323			-0.30642369222116871970059157132	0.54778896869655520601485651247								-0.57150400207205686533461107422
95	4.3386181225564464183342419593		male	[null]	-1.52458485653939825566284767748	2.1369512745823790489825207158	PC 17608		C	B57 B59 B63 B66	[null]		Haverford, PA / Cooperstown, NY			1.718351957456489070218766430323			-0.30642369222116871970059157132	-1.82404116243169099688897026934								1.74835105897043756352888762989
96	0.4166731739528543395023294464		male	[null]	-1.52458485653939825566284767748	1.3749306396174980941009647117	13507		S	E44	[null]		Duluth, MN			1.718351957456489070218766430323			-0.30642369222116871970059157132	0.54778896869655520601485651247								1.74835105897043756352888762989
97	-0.1408232989446655903376833021		male	[null]	-1.52458485653939825566284767748	1.7905782586892513422181770776	113792		S	[null]	[null]		New York, NY			1.718351957456489070218766430323			-0.30642369222116871970059157132	0.54778896869655520601485651247								-0.57150400207205686533461107422
98	-0.0620747852363678688681526427		male	[null]	-1.52458485653939825566284767748	1.7905782586892513422181770776	17764		C	A7	[null]		St James, Long Island, NY			1.718351957456489070218766430323			-0.30642369222116871970059157132	0.54778896869655520601485651247								-0.57150400207205686533461107422
99	0.4945517272366646193096225390		male	[null]	-1.52458485653939825566284767748	-0.4262090430267659810736222072	13695		S	C31	[null]		Huntington, WV			1.718351957456489070218766430323			-0.30642369222116871970059157132	0.54778896869655520601485651247								1.74835105897043756352888762989
100	-0.1512704219461523351898811560		male	[null]	-1.52458485653939825566284767748	[null]	113056		S	A19	[null]		Streatham, Surrey			1.718351957456489070218766430323			-0.30642369222116871970059157132	0.54778896869655520601485651247								-0.57150400207205686533461107422

Out[99]:

Rows: 1-100 of 1234 | Columns: 32

In [102]:

# Saving the result in the Database
from verticapy import *
titanic.to_db(name = '"public"."titanic_normalized"',
              usecols = ["fare", "sex", "survived"],
              relation_type = "table")
vDataFrame('"public"."titanic_normalized"')

	123 fare Numeric(46,28)	123 Numeric(63,30)	Abc sex Varchar(20)
1	[null]		male
2	-0.6451344183800711827483251581		male
3	-0.6451344183800711827483251581		male
4	-0.6451344183800711827483251581		male
5	-0.6451344183800711827483251581		male
6	-0.6451344183800711827483251581		male
7	-0.6451344183800711827483251581		male
8	-0.6451344183800711827483251581		male
9	-0.6451344183800711827483251581		male
10	-0.6451344183800711827483251581		male
11	-0.6451344183800711827483251581		male
12	-0.6451344183800711827483251581		male
13	-0.6451344183800711827483251581		male
14	-0.6451344183800711827483251581		male
15	-0.6451344183800711827483251581		male
16	-0.6451344183800711827483251581		male
17	-0.5849058045380454180622361488		male
18	-0.5689179073919519759856999059		male
19	-0.5501605729120098659101628500		male
20	-0.5266545461586646899927176788		male
21	-0.5228555923399422373191911865		male
22	-0.5228555923399422373191911865		male
23	-0.5228555923399422373191911865		male
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Out[102]:

Rows: 1-100 of 1234 | Columns: 3

In [104]:

# Adding a split column in the final relation
titanic.to_db(name = '"public"."titanic_normalized"',
              usecols = ["fare", "sex", "survived"],
              relation_type = "table",
              nb_split = 3)
vDataFrame('"public"."titanic_normalized"')

	123 fare Numeric(46,28)	123 Numeric(63,30)	Abc sex Varchar(20)	123 _verticapy_split_ Int
1	[null]		male	1
2	-0.6451344183800711827483251581		male	0
3	-0.6451344183800711827483251581		male	0
4	-0.6451344183800711827483251581		male	0
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6	-0.6451344183800711827483251581		male	0
7	-0.6451344183800711827483251581		male	1
8	-0.6451344183800711827483251581		male	1
9	-0.6451344183800711827483251581		male	1
10	-0.6451344183800711827483251581		male	1
11	-0.6451344183800711827483251581		male	2
12	-0.6451344183800711827483251581		male	2
13	-0.6451344183800711827483251581		male	2
14	-0.6451344183800711827483251581		male	2
15	-0.6451344183800711827483251581		male	0
16	-0.6451344183800711827483251581		male	0
17	-0.5849058045380454180622361488		male	2
18	-0.5689179073919519759856999059		male	0
19	-0.5501605729120098659101628500		male	0
20	-0.5266545461586646899927176788		male	1
21	-0.5228555923399422373191911865		male	0
22	-0.5228555923399422373191911865		male	1
23	-0.5228555923399422373191911865		male	2
24	-0.5226181577262720840270957807		male	0
25	-0.5217481973017846423648582139		male	0
26	-0.5217481973017846423648582139		male	1
27	-0.5217481973017846423648582139		male	2
28	-0.5169197269981884050168060422		male	0
29	-0.5148625935053501968940914466		male	1
30	-0.5131207731794659523432795499		male	1
31	-0.5126459039521256457590887383		male	0
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33	-0.5121710347247853391748979268		female	0
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60	-0.5078972116787225799171806229		male	2
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70	-0.5078174336485294084110365666		female	0
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81	-0.5078174336485294084110365666		male	1
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100	-0.5074223424513822733329898114		male	1

Out[104]:

Rows: 1-100 of 1234 | Columns: 4

In [106]:

# Using conditions to filter data
titanic.to_db(name = '"public"."titanic_normalized"',
              usecols = ["fare", "sex", "survived"],
              relation_type = "table",
              db_filter = "sex = 'female'")
vDataFrame('"public"."titanic_normalized"')

	123 fare Numeric(46,28)	123 Numeric(63,30)	Abc sex Varchar(20)
1	-0.5121710347247853391748979268		female
2	-0.5078972116787225799171806229		female
3	-0.5078174336485294084110365666		female
4	-0.5078174336485294084110365666		female
5	-0.5078174336485294084110365666		female
6	-0.5078174336485294084110365666		female
7	-0.5074223424513822733329898114		female
8	-0.5067898166405649849628476504		female
9	-0.5027534282081723789972257523		female
10	-0.5017239117232985943227000729		female
11	-0.5017239117232985943227000729		female
12	-0.5002195260110845030639835819		female
13	-0.5002195260110845030639835819		female
14	-0.4998244348139373679859368267		female
15	-0.4998244348139373679859368267		female
16	-0.4983998271319164482333643921		female
17	-0.4982421705484394664474130427		female
18	-0.4982421705484394664474130427		female
19	-0.4981623925182462949412689864		female
20	-0.4979249579045761416491735806		female
21	-0.4979249579045761416491735806		female
22	-0.4979249579045761416491735806		female
23	-0.4979249579045761416491735806		female
24	-0.4979249579045761416491735806		female
25	-0.4979249579045761416491735806		female
26	-0.4979249579045761416491735806		female
27	-0.4979249579045761416491735806		female
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57	-0.4954708337376814372220754665		female
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Out[106]:

Rows: 1-100 of 420 | Columns: 3

In [108]:

# Using multiple conditions to filter data
titanic.to_db(name = '"public"."titanic_normalized"',
              usecols = ["fare", "sex", "survived"],
              relation_type = "table",
              db_filter = ["sex = 'female'", "fare < 3"])
vDataFrame('"public"."titanic_normalized"')

	123 fare Numeric(46,28)	123 Numeric(63,30)	Abc sex Varchar(20)
1	-0.5121710347247853391748979268		female
2	-0.5078972116787225799171806229		female
3	-0.5078174336485294084110365666		female
4	-0.5078174336485294084110365666		female
5	-0.5078174336485294084110365666		female
6	-0.5078174336485294084110365666		female
7	-0.5074223424513822733329898114		female
8	-0.5067898166405649849628476504		female
9	-0.5027534282081723789972257523		female
10	-0.5017239117232985943227000729		female
11	-0.5017239117232985943227000729		female
12	-0.5002195260110845030639835819		female
13	-0.5002195260110845030639835819		female
14	-0.4998244348139373679859368267		female
15	-0.4998244348139373679859368267		female
16	-0.4983998271319164482333643921		female
17	-0.4982421705484394664474130427		female
18	-0.4982421705484394664474130427		female
19	-0.4981623925182462949412689864		female
20	-0.4979249579045761416491735806		female
21	-0.4979249579045761416491735806		female
22	-0.4979249579045761416491735806		female
23	-0.4979249579045761416491735806		female
24	-0.4979249579045761416491735806		female
25	-0.4979249579045761416491735806		female
26	-0.4979249579045761416491735806		female
27	-0.4979249579045761416491735806		female
28	-0.4979249579045761416491735806		female
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31	-0.4979249579045761416491735806		female
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60	-0.4946008733131939955598378998		female
61	-0.4946008733131939955598378998		female
62	-0.4946008733131939955598378998		female
63	-0.4946008733131939955598378998		female
64	-0.4946008733131939955598378998		female
65	-0.4946008733131939955598378998		female
66	-0.4922265271764924626388838421		female
67	-0.4922265271764924626388838421		female
68	-0.4922265271764924626388838421		female
69	-0.4922265271764924626388838421		female
70	-0.4922265271764924626388838421		female
71	-0.4922265271764924626388838421		female
72	-0.4910393541081416961784068132		female
73	-0.4905644848808013895942160017		female
74	-0.4805922311066549513262089594		female
75	-0.4805922311066549513262089594		female
76	-0.4805922311066549513262089594		female
77	-0.4805922311066549513262089594		female
78	-0.4805922311066549513262089594		female
79	-0.4801971399095078162481622042		female
80	-0.4770307119016026519447778728		female
81	-0.4748938003785712723159192209		female
82	-0.4675333273547965202609616420		female
83	-0.4651589812180949873400075843		female
84	-0.4630220696950636077111489324		female
85	-0.4630220696950636077111489324		female
86	-0.4585108120353306951613362227		female
87	-0.4585108120353306951613362227		female
88	-0.4582733774216605418692408169		female
89	-0.4581935993914673703630967606		female
90	-0.4464016467381528772644705284		female
91	-0.4464016467381528772644705284		female
92	-0.4456893428971424173881843111		female
93	-0.4456893428971424173881843111		female
94	-0.4456893428971424173881843111		female
95	-0.4456893428971424173881843111		female
96	-0.4456893428971424173881843111		female
97	-0.4456893428971424173881843111		female
98	-0.4456893428971424173881843111		female
99	-0.4456893428971424173881843111		female
100	-0.4453721302532790925899448490		female

Out[108]:

Rows: 1-100 of 397 | Columns: 3

vDataFrame.to_db¶

Parameters¶

Returns¶

Example¶

See Also¶