stress_data

Student_ID int64 1k 101k	Age int64 18 24	Gender stringclasses 2 values	Department stringclasses 5 values	CGPA float64 1.56 4	Sleep_Duration float64 3 12	Study_Hours float64 0 12.8	Social_Media_Hours float64 0 10	Physical_Activity int64 0 149	Stress_Level int64 2 10	Depression bool 2 classes
1,001	22	Female	Science	3.5	7.3	3.3	3.4	114	5	false
1,002	20	Male	Engineering	2.72	5.5	7.2	6	142	2	false
1,003	20	Male	Medical	3.01	5.4	2.3	1.8	137	3	false
1,004	21	Male	Engineering	3.63	8.1	2	4.6	130	3	false
1,005	19	Male	Arts	3.14	6.8	2.6	4.3	4	6	false
1,006	22	Female	Medical	3.31	6.5	3.5	4.1	129	2	false
1,007	18	Male	Science	2.14	4.4	4	3.1	73	8	true
1,008	18	Male	Engineering	3.27	7	3.4	7.6	68	4	false
1,009	21	Male	Business	2.71	4.8	8.6	0.3	82	5	false
1,010	24	Male	Engineering	3.36	5.7	1.5	3.7	59	3	false
1,011	23	Male	Science	3.35	3.8	4.4	1.7	95	6	false
1,012	21	Female	Business	2.06	5.4	1.5	3.1	127	2	false
1,013	24	Male	Engineering	2.05	5.1	6.5	5.3	107	4	false
1,014	24	Female	Medical	2.1	5.5	4.9	2.8	47	4	false
1,015	22	Female	Arts	2.91	5.1	0.6	2.4	72	3	true
1,016	23	Male	Arts	3.33	7.6	5.9	4.5	53	4	false
1,017	23	Female	Arts	3.15	5.3	3.8	2.5	24	6	false
1,018	19	Male	Business	3.2	5.9	2	3.5	145	5	false
1,019	21	Female	Medical	2.19	7.3	3.4	1.9	31	3	false
1,020	19	Female	Engineering	3.48	7.9	4.4	4.3	129	3	false
1,021	24	Female	Medical	3.33	9.9	3.6	4.8	117	2	false
1,022	19	Female	Science	3.62	7.6	3.1	3	17	6	false
1,023	21	Female	Science	2.13	6	0.8	6.5	116	3	false
1,024	18	Male	Arts	2	7.9	4.8	2.9	7	3	false
1,025	18	Male	Science	2.1	10.7	2.4	1.7	133	3	false
1,026	22	Female	Business	3.65	9.9	7.2	4.2	132	4	false
1,027	18	Female	Science	2.25	8.4	3.7	2.6	70	3	false
1,028	24	Male	Engineering	3.17	4.9	7.9	4.5	142	5	false
1,029	21	Male	Business	2.8	5.9	4.4	4.4	69	4	false
1,030	23	Female	Engineering	2.75	6	2.4	4.8	17	5	false
1,031	24	Male	Medical	3.03	10.5	0.3	1.7	45	3	false
1,032	19	Male	Arts	2.84	8.1	3.7	3	86	3	false
1,033	19	Male	Engineering	1.84	9.1	3	5.3	139	4	false
1,034	22	Female	Engineering	2.98	8.5	4.5	4	57	4	false
1,035	18	Female	Arts	3.49	6.2	7.3	1.4	72	2	false
1,036	20	Female	Engineering	2.08	8.6	4	2.8	99	3	false
1,037	24	Female	Engineering	2.51	6.3	2.3	3.9	63	5	false
1,038	23	Male	Medical	2.79	8.4	6.6	6.1	62	2	false
1,039	23	Female	Arts	2.38	7.1	5.7	1.4	56	6	false
1,040	20	Male	Arts	3.18	8	6.2	4.5	130	2	false
1,041	22	Female	Science	3.18	7.4	4.3	6.4	81	2	false
1,042	19	Female	Medical	2.57	4.6	3.8	2.6	58	6	false
1,043	23	Female	Business	3.34	7.6	1.1	2.2	18	5	false
1,044	23	Female	Arts	2.95	8.1	4.9	6.3	74	3	false
1,045	20	Female	Business	3.22	6.9	1.6	3.8	108	5	false
1,046	19	Female	Medical	2.43	4.6	7	2.5	35	6	false
1,047	23	Female	Arts	3.31	7	4.2	2.3	34	6	false
1,048	22	Female	Arts	2.47	6.4	3.2	3.5	39	4	false
1,049	24	Male	Science	2.52	4.5	0.5	3.8	110	6	false
1,050	18	Female	Medical	3.26	5.1	3.5	4.1	10	6	false
1,051	19	Female	Science	2.42	9.3	5.5	6.6	100	5	true
1,052	22	Female	Arts	3.49	4.6	3.2	2.6	81	7	false
1,053	21	Male	Business	3.37	7.5	5.4	4.1	126	2	false
1,054	21	Female	Arts	3.67	9.6	2.3	4.8	81	3	false
1,055	21	Male	Medical	3.49	7	5.2	3.4	131	3	false
1,056	20	Male	Arts	2.75	6.9	3.7	4.2	74	3	false
1,057	22	Male	Arts	2.32	7.9	4.8	2.5	107	3	false
1,058	18	Male	Engineering	3.24	6	4.6	4.9	131	2	false
1,059	22	Female	Business	3.25	7.8	6.9	4.1	62	3	false
1,060	20	Female	Engineering	3.42	7.4	4.2	1.1	8	3	true
1,061	23	Female	Business	2.86	8.2	4.4	4.7	130	2	false
1,062	22	Female	Business	2.1	4.6	1.3	5.4	134	8	true
1,063	22	Male	Engineering	2.26	4.8	6.4	3.4	148	6	false
1,064	24	Male	Medical	2.88	6.2	0	0	65	5	false
1,065	19	Female	Business	3.13	7	7.3	4.5	88	4	false
1,066	24	Female	Medical	2.81	7.6	2.3	2	81	4	false
1,067	20	Female	Business	2.2	6.5	2.6	1.1	114	3	false
1,068	18	Female	Engineering	2.22	3	3.8	3	11	7	false
1,069	22	Female	Medical	2.39	5.4	3.7	2.6	118	2	false
1,070	21	Female	Business	2.96	4.2	4	5.6	120	8	false
1,071	21	Male	Arts	2.44	7	2.6	1.9	100	5	true
1,072	20	Female	Business	2.58	8.2	6.1	3.6	141	4	false
1,073	21	Male	Business	3.44	5.3	2.9	5.8	38	3	false
1,074	24	Female	Medical	3.27	6.9	5.2	3.5	94	2	false
1,075	23	Male	Engineering	3.33	6.6	0.5	1.1	147	5	false
1,076	24	Male	Medical	3.13	5.7	2.8	5.1	142	5	false
1,077	20	Female	Engineering	2.07	6.1	6.3	3.2	45	6	false
1,078	18	Female	Arts	3.78	8.4	3.7	4.2	27	6	false
1,079	21	Male	Medical	3.15	5.8	3.7	3.2	52	4	true
1,080	20	Male	Business	2.86	8	4.6	5.2	46	4	false
1,081	23	Female	Engineering	3.24	3	3.6	4.8	37	8	false
1,082	20	Female	Business	3.17	6.7	8.7	5.7	132	5	false
1,083	23	Male	Engineering	2.75	6.7	1.4	3.5	61	5	false
1,084	22	Female	Science	3.86	3.6	7.4	4.9	108	5	false
1,085	22	Male	Business	3.49	8.8	1.9	3.7	81	5	false
1,086	18	Female	Engineering	3.76	8.9	4.4	4.2	30	6	false
1,087	18	Female	Arts	2.85	5.6	4.1	2.4	107	5	false
1,088	19	Male	Engineering	2.12	6.7	4.8	2.4	133	3	false
1,089	24	Male	Arts	2.68	8.9	1.6	2.8	55	3	false
1,090	20	Male	Arts	2.47	5.8	4.4	2.9	83	2	false
1,091	22	Male	Medical	3.54	6.3	6	3.6	59	3	false
1,092	23	Male	Arts	3.06	6.2	3	4.3	102	5	false
1,093	21	Male	Medical	2.15	7.4	2.8	3.7	82	4	false
1,094	22	Male	Medical	3.79	10	6	3	53	5	false
1,095	22	Female	Business	2.34	6.6	1.7	2.3	118	5	true
1,096	20	Female	Business	3.34	8.1	6	1.1	122	5	false
1,097	22	Male	Arts	2.65	7.5	5.4	3.7	135	2	false
1,098	21	Male	Arts	3.74	4.7	3.4	4.1	140	8	false
1,099	20	Female	Business	3.66	9	3.3	0	69	4	false
1,100	21	Female	Medical	2.48	7.1	2.9	4.9	142	5	false

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Student Depression & Lifestyle (100k Data)

A large-scale dataset for analyzing the impact of habits on mental health & acad

Dataset Info

Source: Kaggle
Original Size: 1.25 MB
Kaggle Downloads: 3,484
Files: 1

Files

student_lifestyle_100k.csv

Mirrored from Kaggle

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