Datasets:

supersam7
/

simulated_bank_data_2012_2026

age int64 17 89	job stringclasses 12 values	marital stringclasses 4 values	education stringclasses 8 values	default stringclasses 3 values	housing stringclasses 3 values	loan stringclasses 3 values	contact stringclasses 2 values	month stringclasses 10 values	day_of_week stringclasses 5 values	duration int64 0 959	campaign int64 1 10	pdays int64 962 962	poutcome stringclasses 3 values	emp.var.rate float64 -3.4 1.4	cons.price.idx float64 92.2 105	cons.conf.idx float64 -50.8 -26.9	euribor3m float64 0.1 6	nr.employed float64 4.76k 5.43k	y stringclasses 2 values	year int64 2.01k 2.03k
34	management	married	basic.4y	no	no	no	telephone	may	mon	162	3	962	nonexistent	-0.094762	95.580191	-43.071323	3.039005	5,055.863159	no	2,012
45	services	married	basic.9y	unknown	no	no	cellular	jul	mon	197	1	962	nonexistent	-2.381398	102.27885	-35.87196	5.338302	5,210.407255	no	2,012
38	retired	divorced	high.school	no	yes	no	cellular	jun	fri	403	1	962	nonexistent	0.172365	92.299641	-43.275772	3.666499	5,181.040817	no	2,012
52	blue-collar	married	university.degree	unknown	yes	no	telephone	jul	fri	331	3	962	failure	0.304274	103.179734	-33.560743	2.447284	5,275.28951	no	2,012
44	services	married	university.degree	unknown	no	no	cellular	may	tue	31	1	962	nonexistent	1.341584	97.453426	-43.534033	2.996327	5,003.08755	no	2,012
35	admin.	married	university.degree	unknown	no	yes	cellular	sep	fri	185	3	962	nonexistent	0.935435	93.56151	-37.969773	2.517717	5,379.024641	no	2,012
31	admin.	divorced	basic.9y	no	no	no	telephone	may	fri	162	1	962	failure	0.764481	100.077993	-39.632822	3.002993	5,074.628957	no	2,012
32	technician	single	basic.6y	no	no	yes	cellular	jul	tue	140	1	962	nonexistent	0.667174	93.407598	-33.071028	0.923466	5,366.51143	no	2,012
32	unemployed	married	university.degree	no	no	no	cellular	jun	wed	26	2	962	nonexistent	-2.292695	93.18824	-36.748409	3.83489	5,369.608404	no	2,012
42	admin.	single	professional.course	no	no	no	telephone	may	mon	305	3	962	nonexistent	-2.621199	101.167752	-43.696537	4.259384	5,213.857619	no	2,012
44	admin.	single	high.school	no	yes	no	cellular	apr	thu	278	1	962	nonexistent	-1.171441	95.105709	-35.659365	5.849092	5,199.45389	no	2,012
29	housemaid	single	high.school	unknown	yes	no	cellular	jun	mon	47	3	962	nonexistent	-0.093225	92.485684	-38.540817	4.34561	5,000.320212	no	2,012
45	technician	single	basic.4y	no	no	unknown	cellular	may	wed	387	4	962	nonexistent	-0.670059	95.640875	-37.806675	2.603561	5,371.803373	no	2,012
32	blue-collar	single	university.degree	unknown	no	no	telephone	may	tue	192	5	962	failure	0.372127	96.226157	-38.114405	3.893822	5,346.425367	no	2,012
29	blue-collar	single	professional.course	unknown	no	no	cellular	jun	mon	369	3	962	nonexistent	-1.289539	101.838593	-38.927477	1.046816	5,364.295547	no	2,012
56	admin.	single	university.degree	no	yes	no	telephone	apr	fri	333	3	962	nonexistent	-2.447808	95.187787	-36.996085	0.443529	4,974.221266	no	2,012
42	retired	married	university.degree	no	no	no	cellular	may	fri	512	2	962	nonexistent	-0.036658	104.019982	-35.795711	0.715247	5,160.690074	no	2,012
27	admin.	divorced	basic.9y	no	yes	no	cellular	sep	mon	211	5	962	nonexistent	0.470796	93.549611	-34.717831	5.270394	5,246.178936	no	2,012
51	blue-collar	married	university.degree	no	no	yes	telephone	may	tue	296	1	962	nonexistent	-1.91008	93.25998	-47.751076	1.326227	5,076.761137	no	2,012
49	retired	married	professional.course	no	no	no	telephone	may	tue	165	3	962	nonexistent	-2.761263	101.287593	-47.023178	1.297044	5,220.669266	yes	2,012
29	blue-collar	single	university.degree	no	no	no	telephone	may	fri	352	1	962	nonexistent	1.034807	100.128566	-49.890634	1.756551	5,124.294103	yes	2,012
42	services	single	basic.4y	unknown	no	no	telephone	may	tue	183	2	962	nonexistent	0.295594	93.112356	-42.407476	1.416566	5,197.798558	no	2,012
47	admin.	married	unknown	no	yes	no	telephone	may	tue	395	2	962	nonexistent	-1.748461	101.132663	-44.845578	2.411996	5,338.951502	no	2,012
60	admin.	single	university.degree	unknown	no	no	cellular	nov	wed	20	4	962	nonexistent	-0.264791	96.225551	-39.534766	3.739581	5,336.929221	no	2,012
26	admin.	married	university.degree	unknown	no	no	cellular	may	mon	417	1	962	nonexistent	0.041848	96.407552	-38.15041	2.166765	5,162.22787	no	2,012
48	technician	single	basic.6y	no	no	yes	cellular	jul	wed	214	1	962	success	0.697833	103.473815	-39.451199	3.341734	5,146.090067	no	2,012
47	admin.	married	high.school	no	no	unknown	cellular	may	fri	347	1	962	nonexistent	-0.388195	96.18219	-44.034493	5.339498	5,031.741782	no	2,012
48	blue-collar	married	basic.4y	no	yes	yes	telephone	jul	thu	512	1	962	nonexistent	1.284053	98.364185	-38.443798	2.800907	5,307.994602	no	2,012
41	technician	married	high.school	unknown	yes	yes	cellular	aug	wed	19	2	962	nonexistent	-2.275223	104.415757	-33.148235	0.969682	5,013.030991	no	2,012
44	services	married	university.degree	no	yes	no	telephone	nov	tue	438	2	962	nonexistent	0.643832	98.248583	-39.957403	4.0003	5,198.13303	no	2,012
17	retired	married	university.degree	no	no	no	cellular	may	mon	201	5	962	nonexistent	-1.671495	96.421215	-42.309481	2.596477	5,212.593607	no	2,012
36	blue-collar	married	unknown	no	no	no	telephone	sep	mon	155	1	962	nonexistent	0.404989	98.602964	-39.969267	2.426221	5,385.570018	no	2,012
26	blue-collar	divorced	basic.9y	no	yes	no	telephone	aug	fri	282	5	962	success	-1.759895	92.381378	-35.547669	2.403044	5,252.113892	no	2,012
40	unemployed	divorced	basic.9y	no	no	no	telephone	may	fri	290	1	962	success	0.276629	95.514753	-47.370694	3.029519	5,241.907358	no	2,012
18	technician	single	university.degree	no	yes	no	cellular	nov	mon	313	5	962	nonexistent	-0.680458	104.652646	-40.20738	3.769563	4,923.354874	no	2,012
67	housemaid	married	high.school	no	yes	unknown	cellular	aug	wed	505	1	962	nonexistent	-2.098593	95.533678	-37.974758	1.457216	5,164.155347	no	2,012
39	entrepreneur	married	high.school	no	no	yes	telephone	apr	thu	146	4	962	nonexistent	-1.224653	92.383995	-45.667373	5.112759	5,233.93937	no	2,012
58	management	divorced	basic.9y	no	yes	no	cellular	nov	wed	408	3	962	nonexistent	-2.189884	93.473717	-40.11797	3.706772	5,329.503734	no	2,012
39	management	married	high.school	no	no	no	cellular	oct	mon	543	3	962	failure	-0.784139	98.097574	-49.13062	5.174721	5,240.32269	no	2,012
48	blue-collar	married	basic.9y	no	yes	no	cellular	jun	fri	146	1	962	failure	-0.438971	99.186533	-34.306377	3.593383	5,183.685979	no	2,012
22	technician	single	basic.9y	no	yes	no	cellular	aug	tue	183	3	962	nonexistent	0.604753	103.035384	-37.345421	2.257787	5,412.48332	no	2,012
42	technician	married	high.school	no	no	no	telephone	nov	tue	580	1	962	nonexistent	-1.158651	94.867128	-44.50642	2.883574	5,033.787814	no	2,012
27	admin.	married	university.degree	unknown	no	no	cellular	aug	tue	2	4	962	nonexistent	-0.209727	93.511609	-44.392325	5.791274	5,236.803348	no	2,012
61	blue-collar	single	high.school	no	no	yes	telephone	jun	wed	87	4	962	nonexistent	-2.546943	96.524209	-42.869948	2.284352	5,125.087674	no	2,012
21	technician	single	high.school	unknown	no	no	cellular	aug	tue	254	3	962	nonexistent	1.395565	94.188704	-43.077016	3.993942	5,184.780719	no	2,012
26	technician	married	basic.9y	unknown	yes	no	telephone	may	thu	193	2	962	nonexistent	-1.55066	100.528678	-37.65008	4.443676	5,193.008979	no	2,012
53	admin.	single	high.school	unknown	yes	no	cellular	jun	mon	152	3	962	nonexistent	0.496798	99.514977	-49.5049	1.996797	4,870.338238	no	2,012
35	technician	single	basic.6y	no	yes	no	telephone	aug	wed	281	3	962	nonexistent	0.516143	97.137558	-46.190187	2.197425	5,296.483197	no	2,012
47	blue-collar	single	high.school	no	yes	no	cellular	oct	tue	314	6	962	nonexistent	-2.711844	92.387801	-41.558222	1.543732	5,233.575923	no	2,012
48	unemployed	married	basic.9y	no	yes	no	telephone	jul	wed	207	1	962	nonexistent	-0.637346	93.183353	-42.310311	3.60694	4,962.371845	no	2,012
33	services	single	high.school	no	yes	no	cellular	may	tue	313	4	962	nonexistent	-1.743763	101.697685	-41.377811	3.969506	5,213.511692	no	2,012
25	entrepreneur	married	high.school	unknown	yes	no	cellular	may	mon	136	4	962	nonexistent	1.062909	96.547122	-38.701618	5.721309	5,004.819453	no	2,012
32	retired	married	basic.6y	no	no	no	telephone	may	fri	71	1	962	nonexistent	0.814173	99.28422	-41.643889	1.212055	4,970.408022	no	2,012
33	entrepreneur	single	basic.6y	no	yes	no	telephone	may	thu	148	2	962	nonexistent	1.222872	98.205312	-39.796742	3.689503	5,324.010131	no	2,012
37	services	married	basic.9y	unknown	no	no	cellular	aug	wed	372	2	962	nonexistent	-0.089194	97.43091	-45.173525	1.801961	5,292.490188	no	2,012
28	services	married	basic.9y	no	no	yes	cellular	jul	tue	261	1	962	nonexistent	-1.041729	95.950561	-33.589318	3.64368	5,310.113826	no	2,012
22	blue-collar	divorced	basic.9y	no	yes	no	telephone	jun	wed	354	4	962	nonexistent	-0.279476	100.784062	-41.309849	4.500062	5,300.536244	yes	2,012
43	management	married	basic.9y	unknown	yes	no	cellular	jun	mon	203	1	962	nonexistent	1.334351	96.507187	-43.038011	4.892772	5,094.309249	no	2,012
43	housemaid	single	professional.course	no	no	yes	cellular	may	tue	177	4	962	nonexistent	-0.919075	93.538898	-38.719342	3.678094	5,393.76829	no	2,012
41	retired	single	basic.6y	no	no	no	cellular	jul	tue	300	2	962	nonexistent	-1.16132	95.546787	-34.360522	2.214435	5,006.365943	no	2,012
35	technician	single	university.degree	no	no	no	cellular	jul	fri	198	2	962	failure	-1.099281	93.438114	-43.557039	4.508849	4,890.931662	yes	2,012
54	blue-collar	married	university.degree	no	no	unknown	cellular	jul	tue	64	1	962	nonexistent	-0.291402	98.799505	-39.717982	1.825658	5,032.201905	no	2,012
41	technician	married	high.school	no	no	no	cellular	may	fri	304	2	962	nonexistent	-0.592446	95.448614	-42.222869	2.623974	4,938.038434	no	2,012
43	self-employed	divorced	professional.course	unknown	no	yes	cellular	aug	fri	279	3	962	nonexistent	0.440838	103.506543	-32.801306	5.514608	5,122.829066	no	2,012
30	technician	single	basic.4y	unknown	no	no	cellular	aug	wed	366	4	962	nonexistent	1.262004	104.618874	-39.704107	2.307424	5,426.358399	no	2,012
33	admin.	married	university.degree	no	no	no	telephone	nov	thu	448	3	962	failure	-2.786297	93.902744	-43.389023	2.38196	5,069.524044	no	2,012
22	self-employed	married	university.degree	no	yes	yes	cellular	jun	fri	451	2	962	nonexistent	-0.650527	98.096042	-39.705515	4.72525	5,151.103328	no	2,012
24	admin.	married	university.degree	no	yes	yes	cellular	may	tue	298	4	962	nonexistent	-1.146848	93.32626	-33.912911	2.321045	4,937.034349	no	2,012
42	admin.	single	basic.4y	unknown	no	no	cellular	may	thu	277	3	962	nonexistent	1.044376	97.159129	-41.587044	4.92067	5,025.131521	no	2,012
44	entrepreneur	single	basic.4y	no	no	no	cellular	aug	mon	447	3	962	nonexistent	0.839094	102.47663	-40.322146	4.467765	4,962.416205	no	2,012
51	entrepreneur	married	university.degree	unknown	yes	no	telephone	jun	fri	365	1	962	nonexistent	0.64744	98.351839	-41.039934	1.137847	5,104.641773	no	2,012
38	technician	single	basic.9y	no	no	yes	telephone	may	thu	164	2	962	success	-2.074927	96.305229	-39.977023	1.273818	4,965.00412	yes	2,012
22	blue-collar	married	basic.6y	no	no	no	telephone	aug	tue	414	1	962	nonexistent	-2.270564	100.233143	-41.913836	0.351737	5,290.473411	no	2,012
44	blue-collar	married	basic.6y	no	no	yes	cellular	aug	wed	139	4	962	nonexistent	-0.573892	96.226788	-42.013353	4.512501	5,055.379615	no	2,012
18	technician	married	high.school	unknown	no	no	cellular	jul	mon	253	3	962	failure	0.97225	94.336244	-43.834252	1.261568	5,147.412152	no	2,012
77	blue-collar	single	university.degree	unknown	no	no	telephone	may	thu	249	3	962	nonexistent	0.220669	97.699603	-39.073212	3.28611	5,308.584175	yes	2,012
28	admin.	divorced	basic.4y	no	yes	no	telephone	aug	thu	170	2	962	nonexistent	-3.084414	100.023138	-39.04858	3.478689	5,281.195752	yes	2,012
35	admin.	married	university.degree	no	no	no	telephone	apr	tue	409	4	962	nonexistent	-3.168811	104.736742	-27.379027	4.681385	4,969.891644	no	2,012
33	technician	married	professional.course	no	no	no	cellular	jun	mon	154	2	962	failure	-2.047059	97.501571	-37.766763	5.116766	5,021.329815	no	2,012
18	blue-collar	single	university.degree	no	yes	no	telephone	may	mon	210	3	962	nonexistent	0.907777	93.981201	-42.689391	3.50932	5,018.103438	no	2,012
56	blue-collar	married	professional.course	no	no	no	telephone	nov	mon	283	3	962	failure	0.569216	102.273787	-40.85133	3.695893	5,086.370691	no	2,012
34	blue-collar	married	university.degree	unknown	no	no	telephone	jun	fri	422	5	962	nonexistent	0.378885	96.589229	-41.662245	2.766819	5,112.058667	no	2,012
36	technician	single	university.degree	no	yes	no	cellular	may	wed	476	3	962	nonexistent	-0.747053	98.305977	-47.664038	2.525468	5,260.254174	yes	2,012
27	management	married	professional.course	no	no	no	telephone	may	wed	214	3	962	nonexistent	0.804928	104.740115	-41.58268	3.128159	5,116.169266	yes	2,012
39	admin.	single	basic.9y	no	unknown	no	cellular	aug	wed	285	1	962	failure	1.034367	102.279392	-46.322695	2.644648	4,952.79269	no	2,012
52	admin.	married	basic.4y	no	yes	no	cellular	may	wed	316	3	962	nonexistent	0.429407	99.985232	-39.437283	2.738387	5,266.413825	no	2,012
46	technician	divorced	basic.4y	no	yes	unknown	telephone	aug	wed	139	2	962	nonexistent	-0.826967	103.026697	-36.597781	4.392066	4,947.588917	no	2,012
20	admin.	married	high.school	no	yes	no	cellular	nov	mon	254	5	962	nonexistent	-2.141501	103.208429	-43.348184	2.108218	5,295.917569	yes	2,012
41	blue-collar	married	high.school	unknown	no	no	cellular	apr	fri	325	3	962	nonexistent	-2.979016	93.970739	-36.903681	1.30231	5,118.821559	yes	2,012
22	admin.	married	basic.4y	unknown	no	no	cellular	jul	thu	245	2	962	failure	0.161026	99.001438	-46.048609	2.516927	5,413.680921	no	2,012
35	admin.	married	high.school	no	yes	no	telephone	aug	wed	83	2	962	nonexistent	-3.327759	100.456238	-39.513077	5.431239	4,930.342279	no	2,012
69	blue-collar	married	high.school	no	yes	no	cellular	nov	mon	317	3	962	nonexistent	-2.74507	99.872483	-39.291238	2.972734	5,117.22085	yes	2,012
48	self-employed	married	high.school	no	yes	no	telephone	jul	thu	202	3	962	nonexistent	-1.519502	94.805553	-41.473942	5.162224	4,970.874893	no	2,012
28	technician	married	university.degree	unknown	no	unknown	telephone	jul	wed	119	2	962	nonexistent	0.748419	96.023136	-49.853933	2.964897	5,073.323492	no	2,012
41	entrepreneur	married	university.degree	no	yes	no	telephone	aug	wed	300	2	962	nonexistent	-0.281164	97.688475	-42.851521	5.077887	5,411.178245	no	2,012
24	blue-collar	married	basic.9y	no	no	no	telephone	jul	tue	186	2	962	nonexistent	-2.508178	94.856542	-41.315395	0.547349	5,111.427256	no	2,012
46	housemaid	married	basic.6y	no	unknown	no	telephone	jun	mon	275	1	962	nonexistent	-0.47408	96.442125	-35.847641	4.045764	5,051.319573	no	2,012
23	retired	married	basic.9y	no	no	yes	cellular	aug	thu	146	1	962	nonexistent	0.385931	103.3893	-40.403906	3.584104	5,394.451269	no	2,012
29	technician	single	university.degree	unknown	yes	no	telephone	may	wed	34	2	962	nonexistent	-1.793669	99.867252	-36.754426	3.675576	5,241.922132	no	2,012
42	technician	single	basic.6y	no	no	no	telephone	jul	tue	324	2	962	nonexistent	0.835683	100.304947	-43.284665	4.409845	5,208.057567	no	2,012

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Simulated Bank Marketing Dataset (2012-2026)

Description

Simulated extension of UCI Bank Marketing dataset for predicting term deposit subscriptions. Original data from 2008-2010; simulated for 2012-2026 with similar distributions.

Data Source

Based on UCI ML Repository: https://archive.ics.uci.edu/dataset/222/bank+marketing
41,188 instances, 21 features. Quinlan, J. (1987). Credit Approval [Dataset]. UCI Machine Learning Repository. https://doi.org/10.24432/C5FS30.

Features

age: Numeric, client's age.
job: Categorical, type of job (e.g., admin, blue-collar).
marital: Categorical, marital status (e.g., married, single).
education: Categorical, education level (e.g., university.degree, high.school).
default: Categorical, has credit in default? (yes/no/unknown).
housing: Categorical, has housing loan? (yes/no/unknown).
loan: Categorical, has personal loan? (yes/no/unknown).
contact: Categorical, contact type (cellular/telephone).
month: Categorical, last contact month.
day_of_week: Categorical, last contact day of week.
duration: Numeric, last contact duration (seconds).
campaign: Numeric, contacts during this campaign.
pdays: Numeric, days since last contact (999 if none).
previous: Numeric, contacts before this campaign.
poutcome: Categorical, previous campaign outcome (success/failure/nonexistent).
emp.var.rate: Numeric, employment variation rate.
cons.price.idx: Numeric, consumer price index.
cons.conf.idx: Numeric, consumer confidence index.
euribor3m: Numeric, Euribor 3-month rate.
nr.employed: Numeric, number of employees.
y: Categorical, subscribed to term deposit? (yes/no).

Usage

Load with pandas or R: df = pd.read_csv('simulated_bank_data_2012_2026.csv')

Citation

Original: [Moro et al., 2014] S. Moro, P. Cortez and P. Rita. A Data-Driven Approach to Predict the Success of Bank Telemarketing. Decision Support Systems, Elsevier, 62:22-31, June 2014

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Size of downloaded dataset files:

38.9 MB

Size of the auto-converted Parquet files:

12.2 MB

Number of rows:

205,935