Datasets:

dartbrains
/

salary

salary int64 44.7k 113k	gender int64 0 2	departm stringclasses 7 values	years float64 1 34 ⌀	age float64 31 65 ⌀	publications int64 3 72
86,285	0	bio	26	64	72
77,125	0	bio	28	58	43
71,922	0	bio	10	38	23
70,499	0	bio	16	46	64
66,624	0	bio	11	41	23
64,451	0	bio	23	60	44
64,366	0	bio	23	53	22
59,344	0	bio	5	40	11
58,560	0	bio	8	38	8
58,294	0	bio	20	50	12
56,092	0	bio	2	40	4
54,452	0	bio	13	43	7
54,269	0	bio	26	56	12
55,125	0	bio	8	38	9
97,630	0	chem	34	64	43
82,444	0	chem	31	61	42
76,291	0	chem	29	65	33
75,382	0	chem	26	56	39
64,762	0	chem	25	null	29
62,607	0	chem	20	45	34
60,373	0	chem	26	56	43
58,892	0	chem	18	48	21
47,021	0	chem	4	34	12
44,687	0	chem	4	34	19
104,828	0	geol	null	50	44
71,456	0	geol	11	41	32
65,144	0	geol	7	37	12
52,766	0	geol	4	38	32
112,800	0	neuro	14	44	33
105,761	0	neuro	9	39	30
92,951	0	neuro	11	41	20
86,621	0	neuro	19	49	10
85,569	0	neuro	20	46	35
83,896	0	neuro	10	40	22
79,735	0	neuro	11	41	32
71,518	0	neuro	7	37	34
68,029	0	neuro	15	45	33
66,482	0	neuro	14	44	42
61,680	0	neuro	18	48	20
60,455	0	neuro	8	38	49
58,932	0	neuro	11	41	49
106,412	0	stat	23	53	29
86,980	0	stat	23	53	42
78,114	0	stat	8	38	24
74,085	0	stat	11	41	33
72,250	0	stat	26	56	9
69,596	0	stat	20	50	18
65,285	0	stat	20	50	15
62,557	0	stat	28	58	14
61,947	0	stat	22	58	17
58,565	0	stat	29	59	11
58,365	0	stat	18	48	21
53,656	0	stat	2	32	4
51,391	0	stat	5	35	8
96,936	0	physics	15	50	17
83,216	0	physics	11	37	19
72,044	0	physics	2	32	16
64,048	0	physics	23	53	4
58,888	0	physics	26	56	7
58,744	0	physics	20	50	9
55,944	0	physics	21	51	8
54,076	0	physics	19	49	12
82,142	0	math	9	39	9
70,509	0	math	23	53	7
60,320	0	math	14	44	7
55,814	0	math	8	38	6
53,638	0	math	4	42	8
53,517	2	math	5	35	5
59,139	1	bio	8	38	23
52,968	1	bio	18	48	32
55,949	1	chem	4	34	12
58,893	1	neuro	10	35	4
53,662	1	neuro	1	31	3
57,185	1	stat	9	39	7
52,254	1	stat	2	32	9
61,885	1	math	23	60	9
49,542	1	math	3	33	5

DartBrains salary teaching data

Two small tables used in the DartBrains course's data-analysis tutorials (pandas, polars, plotting) and their assignments.

file	rows	columns
`salary.csv`	77	`salary, gender, departm, years, age, publications`
`salary_exercise.csv`	52	`sx, rk, yr, dg, yd, sl`

salary_exercise.csv is the professor salary data from Weisberg (1985), Applied Linear Regression, 2nd ed., p. 194: 52 tenure-track professors in a small college. It was adapted from the WWS509 datasets page at Princeton (http://data.princeton.edu/wws509/datasets/#salary). Columns: sx sex, rk rank, yr years in current rank, dg highest degree, yd years since highest degree, sl academic-year salary in dollars.
salary.csv is a professor-salary teaching table used in the DartBrains pandas tutorial. Its original source is not recorded.

In the course notebooks, through dartbrains-tools:

from dartbrains_tools.data import salary
import pandas as pd

df = pd.read_csv(salary.get_file("salary.csv"))

or directly:

from huggingface_hub import hf_hub_download
path = hf_hub_download("dartbrains/salary", "salary.csv", repo_type="dataset")

These files previously lived in the DartBrains GitHub repository under data/salary/.