Datasets:

mnemoraorg
/

calorie-burnt-15k

User_ID int64 10M 20M	Gender stringclasses 2 values	Age int64 20 79	Height float64 123 222	Weight float64 36 132	Duration float64 1 30	Heart_Rate float64 67 128	Body_Temp float64 37.1 41.5
14,733,363	male	68	190	94	29	105	40.8
14,861,698	female	20	166	60	14	94	40.3
11,179,863	male	69	179	79	5	88	38.7
16,180,408	female	34	179	71	13	100	40.5
17,771,927	female	27	154	58	10	81	39.8
15,130,815	female	36	151	50	23	96	40.7
19,602,372	female	33	158	56	22	95	40.5
11,117,088	male	41	175	85	25	100	40.7
12,132,339	male	60	186	94	21	97	40.4
17,964,668	female	26	146	51	16	90	40.2
13,723,164	female	36	177	76	1	74	37.8
13,681,290	female	21	157	56	17	100	40
15,566,424	male	66	171	79	11	90	40
12,891,699	female	32	157	54	18	93	40.4
13,823,829	male	53	182	85	2	82	38.1
17,557,348	female	39	156	62	28	104	40.8
12,198,133	male	39	182	82	4	82	38.6
15,236,104	male	46	169	67	11	89	40.2
11,042,324	female	27	171	65	4	85	38.6
16,864,285	male	50	188	86	14	94	40.2
11,674,347	male	67	189	93	8	77	39.2
19,797,300	female	31	148	50	8	84	39.5
14,711,095	female	33	157	60	3	80	38.7
14,434,854	female	20	165	59	29	100	41
14,893,804	male	48	182	85	1	80	37.7
17,231,597	male	29	176	75	10	83	39.7
10,901,446	male	33	173	73	7	78	39.3
15,874,362	male	42	190	88	3	83	38.9
15,569,252	female	62	159	59	29	106	41.2
15,615,743	male	38	171	75	2	81	38.2
13,363,046	male	20	183	88	16	97	40.5
17,572,853	female	25	160	59	24	102	40.3
17,157,339	female	24	165	59	18	91	40.2
18,328,111	female	42	165	68	22	93	40.8
19,303,479	male	22	182	84	29	114	41
10,699,201	female	74	158	59	10	93	39.6
15,283,313	female	70	154	59	10	88	40
16,324,247	female	26	182	80	21	96	40.5
14,277,710	male	44	184	86	25	114	40.8
10,888,188	male	61	183	86	1	81	38.3
13,379,795	female	68	157	57	13	92	40.1
17,181,524	female	61	176	70	20	104	40.5
15,988,442	male	63	179	80	25	108	40.8
19,538,533	female	54	171	66	20	98	40.1
14,591,877	female	54	169	66	3	80	38.9
14,274,480	female	47	155	55	16	93	40.5
16,818,429	male	33	184	86	8	86	39.9
17,476,522	female	24	171	66	24	105	40.6
16,369,885	male	24	195	98	20	96	40.6
17,816,292	male	48	152	59	2	79	38
15,995,398	male	35	193	93	10	83	39.7
17,615,432	male	21	168	71	3	78	38.5
10,146,087	female	21	179	73	9	90	39.6
17,967,445	female	22	158	62	25	105	40.6
19,670,291	female	69	174	69	2	80	38.1
10,580,576	male	53	191	101	21	106	40.7
15,854,213	female	68	155	58	15	100	40.3
11,138,472	female	69	164	65	23	113	40.4
18,276,801	male	28	198	101	19	95	40.6
13,823,902	male	70	188	89	7	82	39.3
19,222,133	female	36	170	64	9	84	39.6
13,231,909	female	77	177	80	16	98	40.6
12,726,617	female	32	167	63	9	99	39.7
12,538,968	female	62	185	77	13	84	40.4
10,941,668	female	64	151	56	20	97	40.4
12,628,985	male	45	175	79	27	104	40.6
17,691,320	male	45	158	61	20	97	40.7
17,822,027	female	22	177	71	10	93	39.8
13,777,657	male	45	169	69	22	113	40.6
19,423,359	female	66	174	69	28	111	40.9
14,701,930	male	31	182	83	20	101	40.9
11,513,205	female	57	163	68	29	109	40.7
11,842,710	male	53	192	93	5	90	39.1
12,576,313	female	22	179	67	8	77	39.5
12,367,125	male	67	192	92	24	108	40.7
16,913,504	female	27	168	64	2	76	38.2
19,439,155	male	57	178	83	2	79	38.1
16,137,644	female	49	168	68	20	99	40.6
11,622,081	female	39	168	63	29	108	40.7
17,374,074	male	47	165	72	20	96	40.3
19,096,890	male	62	197	101	17	103	40.3
19,628,507	male	41	187	89	23	99	40.7
16,918,679	female	34	144	50	7	83	39.3
11,194,130	female	40	163	62	27	111	41.2
18,863,486	female	55	155	57	11	92	39.8
11,754,581	male	44	189	88	13	94	40
15,161,631	female	45	160	60	16	99	40.4
18,735,761	female	49	164	64	19	105	40.4
15,878,611	female	46	166	68	12	101	40.1
19,249,559	male	25	202	100	9	94	39.8
15,469,030	male	68	171	80	22	95	40.5
11,157,560	female	25	169	64	14	101	40.2
19,576,971	female	31	174	67	9	93	39.5
15,048,071	male	57	184	91	7	95	39.2
18,707,469	female	27	159	59	14	88	39.9
12,598,637	male	40	201	98	24	110	40.7
14,342,169	female	57	171	74	2	73	38.6
19,208,771	female	23	155	62	5	74	39.2
11,790,318	male	23	189	87	23	110	40
11,756,583	male	43	183	88	26	107	40.7

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Calorie Burnt 15k

A comprehensive dataset combining exercise and calorie records for approximately 15,000 entries. It is intended for research and analysis on physical activity, calorie expenditure, biometric tracking, and health patterns.

Description

This dataset collates two sources:

Exercise Data: Contains user demographics and biometric measurements during exercise sessions.
Calories Data: Logs calorie burn totals per user corresponding to activities tracked in the exercise dataset.

This unified dataset supports detailed epidemiological, machine learning, or personal tracking studies to correlate biometric and demographic features with calorie expenditure.

Columns & definitions

From Exercise Data (raw_exercise.csv):

User_ID: Unique numerical ID for each individual.
Gender: Participant's gender (e.g., 'male', 'female').
Age: Age of participant (years).
Height: Height in centimeters.
Weight: Weight in kilograms.
Duration: Duration of exercise (minutes).
Heart_Rate: Heart rate measured during or after exercise (beats per minute).
Body_Temp: Body temperature measured during or after exercise (degrees Celsius).

From Calorie Burn Data (raw_calories.csv):

User_ID: Unique numerical ID (to match/merge with above).
Calories: Calories burned as recorded/calculated for each session.

Usage notes

Merging: Merge by User_ID for a complete record per exercise session.
Applications: Useful for regression, classification, health analytics, personalized fitness algorithms, and educational demos.
Preprocessing: Check for duplicates/missing values when merging. Normalize units if using for modeling.

Downloads last month: 80

Size of downloaded dataset files:

677 kB

Size of the auto-converted Parquet files:

228 kB

Number of rows:

15,000

Collection including mnemoraorg/calorie-burnt-15k

(Public) Education—Texts

Collection

Diverse open, texts datasets from global sources—curated for classroom use, homework, and research across subjects and grade levels. • 10 items • Updated 8 days ago • 2