Datasets:

mstz
/

heart_failure

age int8 40 95	has_anaemia bool 2 classes	creatinine_phosphokinase_concentration_in_blood float64 23 7.86k	has_diabetes bool 2 classes	heart_ejection_fraction float64 14 80	has_high_blood_pressure bool 2 classes	platelets_concentration_in_blood float64 25.1k 850k	serum_creatinine_concentration_in_blood float64 0.5 9.4	serum_sodium_concentration_in_blood float64 113 148	is_male bool 2 classes	is_smoker bool 2 classes	days_in_study int64 4 285	is_dead class label 2 classes
75	false	582	false	20	true	265,000	1.9	130	true	false	4	1yes
55	false	7,861	false	38	false	263,358.03	1.1	136	true	false	6	1yes
65	false	146	false	20	false	162,000	1.3	129	true	true	7	1yes
50	true	111	false	20	false	210,000	1.9	137	true	false	7	1yes
65	true	160	true	20	false	327,000	2.7	116	false	false	8	1yes
90	true	47	false	40	true	204,000	2.1	132	true	true	8	1yes
75	true	246	false	15	false	127,000	1.2	137	true	false	10	1yes
60	true	315	true	60	false	454,000	1.1	131	true	true	10	1yes
65	false	157	false	65	false	263,358.03	1.5	138	false	false	10	1yes
80	true	123	false	35	true	388,000	9.4	133	true	true	10	1yes
75	true	81	false	38	true	368,000	4	131	true	true	10	1yes
62	false	231	false	25	true	253,000	0.9	140	true	true	10	1yes
45	true	981	false	30	false	136,000	1.1	137	true	false	11	1yes
50	true	168	false	38	true	276,000	1.1	137	true	false	11	1yes
49	true	80	false	30	true	427,000	1	138	false	false	12	0no
82	true	379	false	50	false	47,000	1.3	136	true	false	13	1yes
87	true	149	false	38	false	262,000	0.9	140	true	false	14	1yes
45	false	582	false	14	false	166,000	0.8	127	true	false	14	1yes
70	true	125	false	25	true	237,000	1	140	false	false	15	1yes
48	true	582	true	55	false	87,000	1.9	121	false	false	15	1yes
65	true	52	false	25	true	276,000	1.3	137	false	false	16	0no
65	true	128	true	30	true	297,000	1.6	136	false	false	20	1yes
68	true	220	false	35	true	289,000	0.9	140	true	true	20	1yes
53	false	63	true	60	false	368,000	0.8	135	true	false	22	0no
75	false	582	true	30	true	263,358.03	1.83	134	false	false	23	1yes
80	false	148	true	38	false	149,000	1.9	144	true	true	23	1yes
95	true	112	false	40	true	196,000	1	138	false	false	24	1yes
70	false	122	true	45	true	284,000	1.3	136	true	true	26	1yes
58	true	60	false	38	false	153,000	5.8	134	true	false	26	1yes
82	false	70	true	30	false	200,000	1.2	132	true	true	26	1yes
94	false	582	true	38	true	263,358.03	1.83	134	true	false	27	1yes
85	false	23	false	45	false	360,000	3	132	true	false	28	1yes
50	true	249	true	35	true	319,000	1	128	false	false	28	1yes
50	true	159	true	30	false	302,000	1.2	138	false	false	29	0no
65	false	94	true	50	true	188,000	1	140	true	false	29	1yes
69	false	582	true	35	false	228,000	3.5	134	true	false	30	1yes
90	true	60	true	50	false	226,000	1	134	true	false	30	1yes
82	true	855	true	50	true	321,000	1	145	false	false	30	1yes
60	false	2,656	true	30	false	305,000	2.3	137	true	false	30	0no
60	false	235	true	38	false	329,000	3	142	false	false	30	1yes
70	false	582	false	20	true	263,358.03	1.83	134	true	true	31	1yes
50	false	124	true	30	true	153,000	1.2	136	false	true	32	1yes
70	false	571	true	45	true	185,000	1.2	139	true	true	33	1yes
72	false	127	true	50	true	218,000	1	134	true	false	33	0no
60	true	588	true	60	false	194,000	1.1	142	false	false	33	1yes
50	false	582	true	38	false	310,000	1.9	135	true	true	35	1yes
51	false	1,380	false	25	true	271,000	0.9	130	true	false	38	1yes
60	false	582	true	38	true	451,000	0.6	138	true	true	40	1yes
80	true	553	false	20	true	140,000	4.4	133	true	false	41	1yes
57	true	129	false	30	false	395,000	1	140	false	false	42	1yes
68	true	577	false	25	true	166,000	1	138	true	false	43	1yes
53	true	91	false	20	true	418,000	1.4	139	false	false	43	1yes
60	false	3,964	true	62	false	263,358.03	6.8	146	false	false	43	1yes
70	true	69	true	50	true	351,000	1	134	false	false	44	1yes
60	true	260	true	38	false	255,000	2.2	132	false	true	45	1yes
95	true	371	false	30	false	461,000	2	132	true	false	50	1yes
70	true	75	false	35	false	223,000	2.7	138	true	true	54	0no
60	true	607	false	40	false	216,000	0.6	138	true	true	54	0no
49	false	789	false	20	true	319,000	1.1	136	true	true	55	1yes
72	false	364	true	20	true	254,000	1.3	136	true	true	59	1yes
45	false	7,702	true	25	true	390,000	1	139	true	false	60	1yes
50	false	318	false	40	true	216,000	2.3	131	false	false	60	1yes
55	false	109	false	35	false	254,000	1.1	139	true	true	60	0no
45	false	582	false	35	false	385,000	1	145	true	false	61	1yes
45	false	582	false	80	false	263,358.03	1.18	137	false	false	63	0no
60	false	68	false	20	false	119,000	2.9	127	true	true	64	1yes
42	true	250	true	15	false	213,000	1.3	136	false	false	65	1yes
72	true	110	false	25	false	274,000	1	140	true	true	65	1yes
70	false	161	false	25	false	244,000	1.2	142	false	false	66	1yes
65	false	113	true	25	false	497,000	1.83	135	true	false	67	1yes
41	false	148	false	40	false	374,000	0.8	140	true	true	68	0no
58	false	582	true	35	false	122,000	0.9	139	true	true	71	0no
85	false	5,882	false	35	false	243,000	1	132	true	true	72	1yes
65	false	224	true	50	false	149,000	1.3	137	true	true	72	0no
69	false	582	false	20	false	266,000	1.2	134	true	true	73	1yes
60	true	47	false	20	false	204,000	0.7	139	true	true	73	1yes
70	false	92	false	60	true	317,000	0.8	140	false	true	74	0no
42	false	102	true	40	false	237,000	1.2	140	true	false	74	0no
75	true	203	true	38	true	283,000	0.6	131	true	true	74	0no
55	false	336	false	45	true	324,000	0.9	140	false	false	74	0no
70	false	69	false	40	false	293,000	1.7	136	false	false	75	0no
67	false	582	false	50	false	263,358.03	1.18	137	true	true	76	0no
60	true	76	true	25	false	196,000	2.5	132	false	false	77	1yes
79	true	55	false	50	true	172,000	1.8	133	true	false	78	0no
59	true	280	true	25	true	302,000	1	141	false	false	78	1yes
51	false	78	false	50	false	406,000	0.7	140	true	false	79	0no
55	false	47	false	35	true	173,000	1.1	137	true	false	79	0no
65	true	68	true	60	true	304,000	0.8	140	true	false	79	0no
44	false	84	true	40	true	235,000	0.7	139	true	false	79	0no
57	true	115	false	25	true	181,000	1.1	144	true	false	79	0no
70	false	66	true	45	false	249,000	0.8	136	true	true	80	0no
60	false	897	true	45	false	297,000	1	133	true	false	80	0no
42	false	582	false	60	false	263,358.03	1.18	137	false	false	82	0no
60	true	154	false	25	false	210,000	1.7	135	true	false	82	1yes
58	false	144	true	38	true	327,000	0.7	142	false	false	83	0no
58	true	133	false	60	true	219,000	1	141	true	false	83	0no
63	true	514	true	25	true	254,000	1.3	134	true	false	83	0no
70	true	59	false	60	false	255,000	1.1	136	false	false	85	0no
60	true	156	true	25	true	318,000	1.2	137	false	false	85	0no
63	true	61	true	40	false	221,000	1.1	140	false	false	86	0no

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Heart failure

The Heart failure dataset from Kaggle. Predict patient death from earth failure given some personal medical data .

Configurations and tasks

Configuration	Task	Description
death	Binary classification	Did the patient die?

Usage

from datasets import load_dataset

dataset = load_dataset("mstz/heart_failure", "death")["train"]

Features

Feature	Type
`age`	`int8`
`has_anaemia`	`int8`
`creatinine_phosphokinase_concentration_in_blood`	`float64`
`has_diabetes`	`int8`
`heart_ejection_fraction`	`float64`
`has_high_blood_pressure`	`int8`
`platelets_concentration_in_blood`	`float64`
`serum_creatinine_concentration_in_blood`	`float64`
`serum_sodium_concentration_in_blood`	`float64`
`sex`	`int8`
`is_smoker`	`int8`
`days_in_study`	`int64`

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Size of downloaded dataset files:

12.2 kB

Size of the auto-converted Parquet files:

12.3 kB

Number of rows:

299