Numpy , Pandas And Matplot Lib Practice

Dataset with Diverse Features and Variations: Exploring a Multivariate Collectio

@kaggle.prathamsaraf1389_numpy_pandas_and_matplot_lib_practise

Table List

1 table(373.83 KB)

Output

@kaggle.prathamsaraf1389_numpy_pandas_and_matplot_lib_practise.output

373.83 KB
5000 rows
20 columns

feature1 Feature1	feature2 Feature2	feature3 Feature3	feature4 Feature4	feature5 Feature5	feature6 Feature6	feature7 Feature7	feature8 Feature8	feature9 Feature9	feature10 Feature10	feature11 Feature11	feature12 Feature12	feature13 Feature13	feature14 Feature14	feature15 Feature15	feature16 Feature16	feature17 Feature17	feature18 Feature18	feature19 Feature19	feature20 Feature20
44	0.7974169639365617	-0.9580908251995915	nan		158	1.4901478185352393	5.166124368721483	2.27794225961709		5	X	1	Category1	Option4	8.824344611530917	11.71113036294012	Yes	Low	nan
47	0.0268381787452141	-0.2441783090045446	D			2.1515347860014447	0.450312172608082	-3.3953558584438497		3	X		Category1	Option2		13.355832080263156	Yes	Low	cat
64	0.1999900022820793	-1.0147987443204454	B		474	1.410613113058646	6.786555096381965	-3.070746033071704		7	Z		Category1	Option2		13.44948362886787	Yes	Medium	dog
67	0.4741244931587874	0.4480401503586159	B		166	0.6350908903138338	1.9371581893140288	-0.246269151001595	6.004974702673276	20	X		Category1	Option2		7.687652301732686	Yes	Low	cat
	0.5985164510447496	0.0878392458369933	nan			0.3921043194086299	4.010937335047976	3.215086470728949	2.8911989957122874	3	Z		Category1	Option3	11.25937103731184	6.807769674231409	Yes	Low	cat
	0.8797531840343717	-0.1474991728507531	D		-40.59127236216466	0.7630043542565234	3.8461804783169895	-4.028923892741873		2	Y		Category1	Option3	11.857069985400551	12.311780684856473	Yes	Medium	nan
	0.6383377074253918	1.456409932503242	nan		839	0.5054385246032874	0.6941139282867889	-1.1045117306991514	3.973684643524716	4	Z	1	Category1	Option3	8.481114371650676	12.327733007071853	Yes	High	cat
	0.5223271169586728	0.1266728338825357	nan	1	840	3.156345294894787	5.71908169765312	-1.1493910157640832	8.114886846677456	3	X		Category1	Option1	11.946108928598838	12.995709026397446	Yes	Low	dog
36	0.9072932156271676	0.0930922488520769	nan			3.36139011780233	9.77729511278472	1.5319955482670389		17	X		Category3	Option3	12.543173850261304	10.40708687212008	Yes	High	nan
	0.9994264331840584	-1.5527222331379755	B		821	1.0785674702110688	2.461383343379276	0.5530251996125107	3.036719795304628	5	Y		Category1	Option4		12.653524261526478	No	High	cat


CREATE TABLE output (
  "feature1" DOUBLE,
  "feature2" DOUBLE,
  "feature3" DOUBLE,
  "feature4" VARCHAR,
  "feature5" DOUBLE,
  "feature6" DOUBLE,
  "feature7" DOUBLE,
  "feature8" DOUBLE,
  "feature9" DOUBLE,
  "feature10" DOUBLE,
  "feature11" BIGINT,
  "feature12" VARCHAR,
  "feature13" BIGINT,
  "feature14" VARCHAR,
  "feature15" VARCHAR,
  "feature16" DOUBLE,
  "feature17" DOUBLE,
  "feature18" VARCHAR,
  "feature19" VARCHAR,
  "feature20" VARCHAR
);