Guided Project: Visualizing Earnings Based On College Majors We'll be working with a dataset on the job outcomes of students who graduated from college between 2010 and 2012. Using visualizations, we can start to explore questions from the dataset like:
Do students in more popular majors make more money? Using scatter plots How many majors are predominantly male? Predominantly female? Using histograms Which category of majors have the most students? Using bar plots
import pandas as pd
import matplotlib.pyplot as plt
%matplotlib inline
recent_grads = pd.read_csv("recent-grads.csv")
#recent_grads.iloc[0]
recent_grads
Rank | Major_code | Major | Total | Men | Women | Major_category | ShareWomen | Sample_size | Employed | ... | Part_time | Full_time_year_round | Unemployed | Unemployment_rate | Median | P25th | P75th | College_jobs | Non_college_jobs | Low_wage_jobs | |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
0 | 1 | 2419 | PETROLEUM ENGINEERING | 2339.0 | 2057.0 | 282.0 | Engineering | 0.120564 | 36 | 1976 | ... | 270 | 1207 | 37 | 0.018381 | 110000 | 95000 | 125000 | 1534 | 364 | 193 |
1 | 2 | 2416 | MINING AND MINERAL ENGINEERING | 756.0 | 679.0 | 77.0 | Engineering | 0.101852 | 7 | 640 | ... | 170 | 388 | 85 | 0.117241 | 75000 | 55000 | 90000 | 350 | 257 | 50 |
2 | 3 | 2415 | METALLURGICAL ENGINEERING | 856.0 | 725.0 | 131.0 | Engineering | 0.153037 | 3 | 648 | ... | 133 | 340 | 16 | 0.024096 | 73000 | 50000 | 105000 | 456 | 176 | 0 |
3 | 4 | 2417 | NAVAL ARCHITECTURE AND MARINE ENGINEERING | 1258.0 | 1123.0 | 135.0 | Engineering | 0.107313 | 16 | 758 | ... | 150 | 692 | 40 | 0.050125 | 70000 | 43000 | 80000 | 529 | 102 | 0 |
4 | 5 | 2405 | CHEMICAL ENGINEERING | 32260.0 | 21239.0 | 11021.0 | Engineering | 0.341631 | 289 | 25694 | ... | 5180 | 16697 | 1672 | 0.061098 | 65000 | 50000 | 75000 | 18314 | 4440 | 972 |
5 | 6 | 2418 | NUCLEAR ENGINEERING | 2573.0 | 2200.0 | 373.0 | Engineering | 0.144967 | 17 | 1857 | ... | 264 | 1449 | 400 | 0.177226 | 65000 | 50000 | 102000 | 1142 | 657 | 244 |
6 | 7 | 6202 | ACTUARIAL SCIENCE | 3777.0 | 2110.0 | 1667.0 | Business | 0.441356 | 51 | 2912 | ... | 296 | 2482 | 308 | 0.095652 | 62000 | 53000 | 72000 | 1768 | 314 | 259 |
7 | 8 | 5001 | ASTRONOMY AND ASTROPHYSICS | 1792.0 | 832.0 | 960.0 | Physical Sciences | 0.535714 | 10 | 1526 | ... | 553 | 827 | 33 | 0.021167 | 62000 | 31500 | 109000 | 972 | 500 | 220 |
8 | 9 | 2414 | MECHANICAL ENGINEERING | 91227.0 | 80320.0 | 10907.0 | Engineering | 0.119559 | 1029 | 76442 | ... | 13101 | 54639 | 4650 | 0.057342 | 60000 | 48000 | 70000 | 52844 | 16384 | 3253 |
9 | 10 | 2408 | ELECTRICAL ENGINEERING | 81527.0 | 65511.0 | 16016.0 | Engineering | 0.196450 | 631 | 61928 | ... | 12695 | 41413 | 3895 | 0.059174 | 60000 | 45000 | 72000 | 45829 | 10874 | 3170 |
10 | 11 | 2407 | COMPUTER ENGINEERING | 41542.0 | 33258.0 | 8284.0 | Engineering | 0.199413 | 399 | 32506 | ... | 5146 | 23621 | 2275 | 0.065409 | 60000 | 45000 | 75000 | 23694 | 5721 | 980 |
11 | 12 | 2401 | AEROSPACE ENGINEERING | 15058.0 | 12953.0 | 2105.0 | Engineering | 0.139793 | 147 | 11391 | ... | 2724 | 8790 | 794 | 0.065162 | 60000 | 42000 | 70000 | 8184 | 2425 | 372 |
12 | 13 | 2404 | BIOMEDICAL ENGINEERING | 14955.0 | 8407.0 | 6548.0 | Engineering | 0.437847 | 79 | 10047 | ... | 2694 | 5986 | 1019 | 0.092084 | 60000 | 36000 | 70000 | 6439 | 2471 | 789 |
13 | 14 | 5008 | MATERIALS SCIENCE | 4279.0 | 2949.0 | 1330.0 | Engineering | 0.310820 | 22 | 3307 | ... | 878 | 1967 | 78 | 0.023043 | 60000 | 39000 | 65000 | 2626 | 391 | 81 |
14 | 15 | 2409 | ENGINEERING MECHANICS PHYSICS AND SCIENCE | 4321.0 | 3526.0 | 795.0 | Engineering | 0.183985 | 30 | 3608 | ... | 811 | 2004 | 23 | 0.006334 | 58000 | 25000 | 74000 | 2439 | 947 | 263 |
15 | 16 | 2402 | BIOLOGICAL ENGINEERING | 8925.0 | 6062.0 | 2863.0 | Engineering | 0.320784 | 55 | 6170 | ... | 1983 | 3413 | 589 | 0.087143 | 57100 | 40000 | 76000 | 3603 | 1595 | 524 |
16 | 17 | 2412 | INDUSTRIAL AND MANUFACTURING ENGINEERING | 18968.0 | 12453.0 | 6515.0 | Engineering | 0.343473 | 183 | 15604 | ... | 2243 | 11326 | 699 | 0.042876 | 57000 | 37900 | 67000 | 8306 | 3235 | 640 |
17 | 18 | 2400 | GENERAL ENGINEERING | 61152.0 | 45683.0 | 15469.0 | Engineering | 0.252960 | 425 | 44931 | ... | 7199 | 33540 | 2859 | 0.059824 | 56000 | 36000 | 69000 | 26898 | 11734 | 3192 |
18 | 19 | 2403 | ARCHITECTURAL ENGINEERING | 2825.0 | 1835.0 | 990.0 | Engineering | 0.350442 | 26 | 2575 | ... | 343 | 1848 | 170 | 0.061931 | 54000 | 38000 | 65000 | 1665 | 649 | 137 |
19 | 20 | 3201 | COURT REPORTING | 1148.0 | 877.0 | 271.0 | Law & Public Policy | 0.236063 | 14 | 930 | ... | 223 | 808 | 11 | 0.011690 | 54000 | 50000 | 54000 | 402 | 528 | 144 |
20 | 21 | 2102 | COMPUTER SCIENCE | 128319.0 | 99743.0 | 28576.0 | Computers & Mathematics | 0.222695 | 1196 | 102087 | ... | 18726 | 70932 | 6884 | 0.063173 | 53000 | 39000 | 70000 | 68622 | 25667 | 5144 |
21 | 22 | 1104 | FOOD SCIENCE | NaN | NaN | NaN | Agriculture & Natural Resources | NaN | 36 | 3149 | ... | 1121 | 1735 | 338 | 0.096931 | 53000 | 32000 | 70000 | 1183 | 1274 | 485 |
22 | 23 | 2502 | ELECTRICAL ENGINEERING TECHNOLOGY | 11565.0 | 8181.0 | 3384.0 | Engineering | 0.292607 | 97 | 8587 | ... | 1873 | 5681 | 824 | 0.087557 | 52000 | 35000 | 60000 | 5126 | 2686 | 696 |
23 | 24 | 2413 | MATERIALS ENGINEERING AND MATERIALS SCIENCE | 2993.0 | 2020.0 | 973.0 | Engineering | 0.325092 | 22 | 2449 | ... | 1040 | 1151 | 70 | 0.027789 | 52000 | 35000 | 62000 | 1911 | 305 | 70 |
24 | 25 | 6212 | MANAGEMENT INFORMATION SYSTEMS AND STATISTICS | 18713.0 | 13496.0 | 5217.0 | Business | 0.278790 | 278 | 16413 | ... | 2420 | 13017 | 1015 | 0.058240 | 51000 | 38000 | 60000 | 6342 | 5741 | 708 |
25 | 26 | 2406 | CIVIL ENGINEERING | 53153.0 | 41081.0 | 12072.0 | Engineering | 0.227118 | 565 | 43041 | ... | 10080 | 29196 | 3270 | 0.070610 | 50000 | 40000 | 60000 | 28526 | 9356 | 2899 |
26 | 27 | 5601 | CONSTRUCTION SERVICES | 18498.0 | 16820.0 | 1678.0 | Industrial Arts & Consumer Services | 0.090713 | 295 | 16318 | ... | 1751 | 12313 | 1042 | 0.060023 | 50000 | 36000 | 60000 | 3275 | 5351 | 703 |
27 | 28 | 6204 | OPERATIONS LOGISTICS AND E-COMMERCE | 11732.0 | 7921.0 | 3811.0 | Business | 0.324838 | 156 | 10027 | ... | 1183 | 7724 | 504 | 0.047859 | 50000 | 40000 | 60000 | 1466 | 3629 | 285 |
28 | 29 | 2499 | MISCELLANEOUS ENGINEERING | 9133.0 | 7398.0 | 1735.0 | Engineering | 0.189970 | 118 | 7428 | ... | 1662 | 5476 | 597 | 0.074393 | 50000 | 39000 | 65000 | 3445 | 2426 | 365 |
29 | 30 | 5402 | PUBLIC POLICY | 5978.0 | 2639.0 | 3339.0 | Law & Public Policy | 0.558548 | 55 | 4547 | ... | 1306 | 2776 | 670 | 0.128426 | 50000 | 35000 | 70000 | 1550 | 1871 | 340 |
... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
143 | 144 | 1105 | PLANT SCIENCE AND AGRONOMY | 7416.0 | 4897.0 | 2519.0 | Agriculture & Natural Resources | 0.339671 | 110 | 6594 | ... | 1246 | 4522 | 314 | 0.045455 | 32000 | 22900 | 40000 | 2089 | 3545 | 1231 |
144 | 145 | 2308 | SCIENCE AND COMPUTER TEACHER EDUCATION | 6483.0 | 2049.0 | 4434.0 | Education | 0.683943 | 59 | 5362 | ... | 1227 | 3247 | 266 | 0.047264 | 32000 | 28000 | 39000 | 4214 | 1106 | 591 |
145 | 146 | 5200 | PSYCHOLOGY | 393735.0 | 86648.0 | 307087.0 | Psychology & Social Work | 0.779933 | 2584 | 307933 | ... | 115172 | 174438 | 28169 | 0.083811 | 31500 | 24000 | 41000 | 125148 | 141860 | 48207 |
146 | 147 | 6002 | MUSIC | 60633.0 | 29909.0 | 30724.0 | Arts | 0.506721 | 419 | 47662 | ... | 24943 | 21425 | 3918 | 0.075960 | 31000 | 22300 | 42000 | 13752 | 28786 | 9286 |
147 | 148 | 2306 | PHYSICAL AND HEALTH EDUCATION TEACHING | 28213.0 | 15670.0 | 12543.0 | Education | 0.444582 | 259 | 23794 | ... | 7230 | 13651 | 1920 | 0.074667 | 31000 | 24000 | 40000 | 12777 | 9328 | 2042 |
148 | 149 | 6006 | ART HISTORY AND CRITICISM | 21030.0 | 3240.0 | 17790.0 | Humanities & Liberal Arts | 0.845934 | 204 | 17579 | ... | 6140 | 9965 | 1128 | 0.060298 | 31000 | 23000 | 40000 | 5139 | 9738 | 3426 |
149 | 150 | 6000 | FINE ARTS | 74440.0 | 24786.0 | 49654.0 | Arts | 0.667034 | 623 | 59679 | ... | 23656 | 31877 | 5486 | 0.084186 | 30500 | 21000 | 41000 | 20792 | 32725 | 11880 |
150 | 151 | 2901 | FAMILY AND CONSUMER SCIENCES | 58001.0 | 5166.0 | 52835.0 | Industrial Arts & Consumer Services | 0.910933 | 518 | 46624 | ... | 15872 | 26906 | 3355 | 0.067128 | 30000 | 22900 | 40000 | 20985 | 20133 | 5248 |
151 | 152 | 5404 | SOCIAL WORK | 53552.0 | 5137.0 | 48415.0 | Psychology & Social Work | 0.904075 | 374 | 45038 | ... | 13481 | 27588 | 3329 | 0.068828 | 30000 | 25000 | 35000 | 27449 | 14416 | 4344 |
152 | 153 | 1103 | ANIMAL SCIENCES | 21573.0 | 5347.0 | 16226.0 | Agriculture & Natural Resources | 0.752144 | 255 | 17112 | ... | 5353 | 10824 | 917 | 0.050862 | 30000 | 22000 | 40000 | 5443 | 9571 | 2125 |
153 | 154 | 6003 | VISUAL AND PERFORMING ARTS | 16250.0 | 4133.0 | 12117.0 | Arts | 0.745662 | 132 | 12870 | ... | 6253 | 6322 | 1465 | 0.102197 | 30000 | 22000 | 40000 | 3849 | 7635 | 2840 |
154 | 155 | 2312 | TEACHER EDUCATION: MULTIPLE LEVELS | 14443.0 | 2734.0 | 11709.0 | Education | 0.810704 | 142 | 13076 | ... | 2214 | 8457 | 496 | 0.036546 | 30000 | 24000 | 37000 | 10766 | 1949 | 722 |
155 | 156 | 5299 | MISCELLANEOUS PSYCHOLOGY | 9628.0 | 1936.0 | 7692.0 | Psychology & Social Work | 0.798920 | 60 | 7653 | ... | 3221 | 3838 | 419 | 0.051908 | 30000 | 20800 | 40000 | 2960 | 3948 | 1650 |
156 | 157 | 5403 | HUMAN SERVICES AND COMMUNITY ORGANIZATION | 9374.0 | 885.0 | 8489.0 | Psychology & Social Work | 0.905590 | 89 | 8294 | ... | 2405 | 5061 | 326 | 0.037819 | 30000 | 24000 | 35000 | 2878 | 4595 | 724 |
157 | 158 | 3402 | HUMANITIES | 6652.0 | 2013.0 | 4639.0 | Humanities & Liberal Arts | 0.697384 | 49 | 5052 | ... | 2225 | 2661 | 372 | 0.068584 | 30000 | 20000 | 49000 | 1168 | 3354 | 1141 |
158 | 159 | 4901 | THEOLOGY AND RELIGIOUS VOCATIONS | 30207.0 | 18616.0 | 11591.0 | Humanities & Liberal Arts | 0.383719 | 310 | 24202 | ... | 8767 | 13944 | 1617 | 0.062628 | 29000 | 22000 | 38000 | 9927 | 12037 | 3304 |
159 | 160 | 6007 | STUDIO ARTS | 16977.0 | 4754.0 | 12223.0 | Arts | 0.719974 | 182 | 13908 | ... | 5673 | 7413 | 1368 | 0.089552 | 29000 | 19200 | 38300 | 3948 | 8707 | 3586 |
160 | 161 | 2201 | COSMETOLOGY SERVICES AND CULINARY ARTS | 10510.0 | 4364.0 | 6146.0 | Industrial Arts & Consumer Services | 0.584776 | 117 | 8650 | ... | 2064 | 5949 | 510 | 0.055677 | 29000 | 20000 | 36000 | 563 | 7384 | 3163 |
161 | 162 | 1199 | MISCELLANEOUS AGRICULTURE | 1488.0 | 404.0 | 1084.0 | Agriculture & Natural Resources | 0.728495 | 24 | 1290 | ... | 335 | 936 | 82 | 0.059767 | 29000 | 23000 | 42100 | 483 | 626 | 31 |
162 | 163 | 5502 | ANTHROPOLOGY AND ARCHEOLOGY | 38844.0 | 11376.0 | 27468.0 | Humanities & Liberal Arts | 0.707136 | 247 | 29633 | ... | 14515 | 13232 | 3395 | 0.102792 | 28000 | 20000 | 38000 | 9805 | 16693 | 6866 |
163 | 164 | 6102 | COMMUNICATION DISORDERS SCIENCES AND SERVICES | 38279.0 | 1225.0 | 37054.0 | Health | 0.967998 | 95 | 29763 | ... | 13862 | 14460 | 1487 | 0.047584 | 28000 | 20000 | 40000 | 19957 | 9404 | 5125 |
164 | 165 | 2307 | EARLY CHILDHOOD EDUCATION | 37589.0 | 1167.0 | 36422.0 | Education | 0.968954 | 342 | 32551 | ... | 7001 | 20748 | 1360 | 0.040105 | 28000 | 21000 | 35000 | 23515 | 7705 | 2868 |
165 | 166 | 2603 | OTHER FOREIGN LANGUAGES | 11204.0 | 3472.0 | 7732.0 | Humanities & Liberal Arts | 0.690111 | 56 | 7052 | ... | 3685 | 3214 | 846 | 0.107116 | 27500 | 22900 | 38000 | 2326 | 3703 | 1115 |
166 | 167 | 6001 | DRAMA AND THEATER ARTS | 43249.0 | 14440.0 | 28809.0 | Arts | 0.666119 | 357 | 36165 | ... | 15994 | 16891 | 3040 | 0.077541 | 27000 | 19200 | 35000 | 6994 | 25313 | 11068 |
167 | 168 | 3302 | COMPOSITION AND RHETORIC | 18953.0 | 7022.0 | 11931.0 | Humanities & Liberal Arts | 0.629505 | 151 | 15053 | ... | 6612 | 7832 | 1340 | 0.081742 | 27000 | 20000 | 35000 | 4855 | 8100 | 3466 |
168 | 169 | 3609 | ZOOLOGY | 8409.0 | 3050.0 | 5359.0 | Biology & Life Science | 0.637293 | 47 | 6259 | ... | 2190 | 3602 | 304 | 0.046320 | 26000 | 20000 | 39000 | 2771 | 2947 | 743 |
169 | 170 | 5201 | EDUCATIONAL PSYCHOLOGY | 2854.0 | 522.0 | 2332.0 | Psychology & Social Work | 0.817099 | 7 | 2125 | ... | 572 | 1211 | 148 | 0.065112 | 25000 | 24000 | 34000 | 1488 | 615 | 82 |
170 | 171 | 5202 | CLINICAL PSYCHOLOGY | 2838.0 | 568.0 | 2270.0 | Psychology & Social Work | 0.799859 | 13 | 2101 | ... | 648 | 1293 | 368 | 0.149048 | 25000 | 25000 | 40000 | 986 | 870 | 622 |
171 | 172 | 5203 | COUNSELING PSYCHOLOGY | 4626.0 | 931.0 | 3695.0 | Psychology & Social Work | 0.798746 | 21 | 3777 | ... | 965 | 2738 | 214 | 0.053621 | 23400 | 19200 | 26000 | 2403 | 1245 | 308 |
172 | 173 | 3501 | LIBRARY SCIENCE | 1098.0 | 134.0 | 964.0 | Education | 0.877960 | 2 | 742 | ... | 237 | 410 | 87 | 0.104946 | 22000 | 20000 | 22000 | 288 | 338 | 192 |
173 rows × 21 columns
recent_grads.describe()
recent_grads = recent_grads.dropna()
#drop rows containing missing values
recent_grads
#only one row contained missing values and was dropped.
Rank | Major_code | Major | Total | Men | Women | Major_category | ShareWomen | Sample_size | Employed | ... | Part_time | Full_time_year_round | Unemployed | Unemployment_rate | Median | P25th | P75th | College_jobs | Non_college_jobs | Low_wage_jobs | |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
0 | 1 | 2419 | PETROLEUM ENGINEERING | 2339.0 | 2057.0 | 282.0 | Engineering | 0.120564 | 36 | 1976 | ... | 270 | 1207 | 37 | 0.018381 | 110000 | 95000 | 125000 | 1534 | 364 | 193 |
1 | 2 | 2416 | MINING AND MINERAL ENGINEERING | 756.0 | 679.0 | 77.0 | Engineering | 0.101852 | 7 | 640 | ... | 170 | 388 | 85 | 0.117241 | 75000 | 55000 | 90000 | 350 | 257 | 50 |
2 | 3 | 2415 | METALLURGICAL ENGINEERING | 856.0 | 725.0 | 131.0 | Engineering | 0.153037 | 3 | 648 | ... | 133 | 340 | 16 | 0.024096 | 73000 | 50000 | 105000 | 456 | 176 | 0 |
3 | 4 | 2417 | NAVAL ARCHITECTURE AND MARINE ENGINEERING | 1258.0 | 1123.0 | 135.0 | Engineering | 0.107313 | 16 | 758 | ... | 150 | 692 | 40 | 0.050125 | 70000 | 43000 | 80000 | 529 | 102 | 0 |
4 | 5 | 2405 | CHEMICAL ENGINEERING | 32260.0 | 21239.0 | 11021.0 | Engineering | 0.341631 | 289 | 25694 | ... | 5180 | 16697 | 1672 | 0.061098 | 65000 | 50000 | 75000 | 18314 | 4440 | 972 |
5 | 6 | 2418 | NUCLEAR ENGINEERING | 2573.0 | 2200.0 | 373.0 | Engineering | 0.144967 | 17 | 1857 | ... | 264 | 1449 | 400 | 0.177226 | 65000 | 50000 | 102000 | 1142 | 657 | 244 |
6 | 7 | 6202 | ACTUARIAL SCIENCE | 3777.0 | 2110.0 | 1667.0 | Business | 0.441356 | 51 | 2912 | ... | 296 | 2482 | 308 | 0.095652 | 62000 | 53000 | 72000 | 1768 | 314 | 259 |
7 | 8 | 5001 | ASTRONOMY AND ASTROPHYSICS | 1792.0 | 832.0 | 960.0 | Physical Sciences | 0.535714 | 10 | 1526 | ... | 553 | 827 | 33 | 0.021167 | 62000 | 31500 | 109000 | 972 | 500 | 220 |
8 | 9 | 2414 | MECHANICAL ENGINEERING | 91227.0 | 80320.0 | 10907.0 | Engineering | 0.119559 | 1029 | 76442 | ... | 13101 | 54639 | 4650 | 0.057342 | 60000 | 48000 | 70000 | 52844 | 16384 | 3253 |
9 | 10 | 2408 | ELECTRICAL ENGINEERING | 81527.0 | 65511.0 | 16016.0 | Engineering | 0.196450 | 631 | 61928 | ... | 12695 | 41413 | 3895 | 0.059174 | 60000 | 45000 | 72000 | 45829 | 10874 | 3170 |
10 | 11 | 2407 | COMPUTER ENGINEERING | 41542.0 | 33258.0 | 8284.0 | Engineering | 0.199413 | 399 | 32506 | ... | 5146 | 23621 | 2275 | 0.065409 | 60000 | 45000 | 75000 | 23694 | 5721 | 980 |
11 | 12 | 2401 | AEROSPACE ENGINEERING | 15058.0 | 12953.0 | 2105.0 | Engineering | 0.139793 | 147 | 11391 | ... | 2724 | 8790 | 794 | 0.065162 | 60000 | 42000 | 70000 | 8184 | 2425 | 372 |
12 | 13 | 2404 | BIOMEDICAL ENGINEERING | 14955.0 | 8407.0 | 6548.0 | Engineering | 0.437847 | 79 | 10047 | ... | 2694 | 5986 | 1019 | 0.092084 | 60000 | 36000 | 70000 | 6439 | 2471 | 789 |
13 | 14 | 5008 | MATERIALS SCIENCE | 4279.0 | 2949.0 | 1330.0 | Engineering | 0.310820 | 22 | 3307 | ... | 878 | 1967 | 78 | 0.023043 | 60000 | 39000 | 65000 | 2626 | 391 | 81 |
14 | 15 | 2409 | ENGINEERING MECHANICS PHYSICS AND SCIENCE | 4321.0 | 3526.0 | 795.0 | Engineering | 0.183985 | 30 | 3608 | ... | 811 | 2004 | 23 | 0.006334 | 58000 | 25000 | 74000 | 2439 | 947 | 263 |
15 | 16 | 2402 | BIOLOGICAL ENGINEERING | 8925.0 | 6062.0 | 2863.0 | Engineering | 0.320784 | 55 | 6170 | ... | 1983 | 3413 | 589 | 0.087143 | 57100 | 40000 | 76000 | 3603 | 1595 | 524 |
16 | 17 | 2412 | INDUSTRIAL AND MANUFACTURING ENGINEERING | 18968.0 | 12453.0 | 6515.0 | Engineering | 0.343473 | 183 | 15604 | ... | 2243 | 11326 | 699 | 0.042876 | 57000 | 37900 | 67000 | 8306 | 3235 | 640 |
17 | 18 | 2400 | GENERAL ENGINEERING | 61152.0 | 45683.0 | 15469.0 | Engineering | 0.252960 | 425 | 44931 | ... | 7199 | 33540 | 2859 | 0.059824 | 56000 | 36000 | 69000 | 26898 | 11734 | 3192 |
18 | 19 | 2403 | ARCHITECTURAL ENGINEERING | 2825.0 | 1835.0 | 990.0 | Engineering | 0.350442 | 26 | 2575 | ... | 343 | 1848 | 170 | 0.061931 | 54000 | 38000 | 65000 | 1665 | 649 | 137 |
19 | 20 | 3201 | COURT REPORTING | 1148.0 | 877.0 | 271.0 | Law & Public Policy | 0.236063 | 14 | 930 | ... | 223 | 808 | 11 | 0.011690 | 54000 | 50000 | 54000 | 402 | 528 | 144 |
20 | 21 | 2102 | COMPUTER SCIENCE | 128319.0 | 99743.0 | 28576.0 | Computers & Mathematics | 0.222695 | 1196 | 102087 | ... | 18726 | 70932 | 6884 | 0.063173 | 53000 | 39000 | 70000 | 68622 | 25667 | 5144 |
22 | 23 | 2502 | ELECTRICAL ENGINEERING TECHNOLOGY | 11565.0 | 8181.0 | 3384.0 | Engineering | 0.292607 | 97 | 8587 | ... | 1873 | 5681 | 824 | 0.087557 | 52000 | 35000 | 60000 | 5126 | 2686 | 696 |
23 | 24 | 2413 | MATERIALS ENGINEERING AND MATERIALS SCIENCE | 2993.0 | 2020.0 | 973.0 | Engineering | 0.325092 | 22 | 2449 | ... | 1040 | 1151 | 70 | 0.027789 | 52000 | 35000 | 62000 | 1911 | 305 | 70 |
24 | 25 | 6212 | MANAGEMENT INFORMATION SYSTEMS AND STATISTICS | 18713.0 | 13496.0 | 5217.0 | Business | 0.278790 | 278 | 16413 | ... | 2420 | 13017 | 1015 | 0.058240 | 51000 | 38000 | 60000 | 6342 | 5741 | 708 |
25 | 26 | 2406 | CIVIL ENGINEERING | 53153.0 | 41081.0 | 12072.0 | Engineering | 0.227118 | 565 | 43041 | ... | 10080 | 29196 | 3270 | 0.070610 | 50000 | 40000 | 60000 | 28526 | 9356 | 2899 |
26 | 27 | 5601 | CONSTRUCTION SERVICES | 18498.0 | 16820.0 | 1678.0 | Industrial Arts & Consumer Services | 0.090713 | 295 | 16318 | ... | 1751 | 12313 | 1042 | 0.060023 | 50000 | 36000 | 60000 | 3275 | 5351 | 703 |
27 | 28 | 6204 | OPERATIONS LOGISTICS AND E-COMMERCE | 11732.0 | 7921.0 | 3811.0 | Business | 0.324838 | 156 | 10027 | ... | 1183 | 7724 | 504 | 0.047859 | 50000 | 40000 | 60000 | 1466 | 3629 | 285 |
28 | 29 | 2499 | MISCELLANEOUS ENGINEERING | 9133.0 | 7398.0 | 1735.0 | Engineering | 0.189970 | 118 | 7428 | ... | 1662 | 5476 | 597 | 0.074393 | 50000 | 39000 | 65000 | 3445 | 2426 | 365 |
29 | 30 | 5402 | PUBLIC POLICY | 5978.0 | 2639.0 | 3339.0 | Law & Public Policy | 0.558548 | 55 | 4547 | ... | 1306 | 2776 | 670 | 0.128426 | 50000 | 35000 | 70000 | 1550 | 1871 | 340 |
30 | 31 | 2410 | ENVIRONMENTAL ENGINEERING | 4047.0 | 2662.0 | 1385.0 | Engineering | 0.342229 | 26 | 2983 | ... | 930 | 1951 | 308 | 0.093589 | 50000 | 42000 | 56000 | 2028 | 830 | 260 |
... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
143 | 144 | 1105 | PLANT SCIENCE AND AGRONOMY | 7416.0 | 4897.0 | 2519.0 | Agriculture & Natural Resources | 0.339671 | 110 | 6594 | ... | 1246 | 4522 | 314 | 0.045455 | 32000 | 22900 | 40000 | 2089 | 3545 | 1231 |
144 | 145 | 2308 | SCIENCE AND COMPUTER TEACHER EDUCATION | 6483.0 | 2049.0 | 4434.0 | Education | 0.683943 | 59 | 5362 | ... | 1227 | 3247 | 266 | 0.047264 | 32000 | 28000 | 39000 | 4214 | 1106 | 591 |
145 | 146 | 5200 | PSYCHOLOGY | 393735.0 | 86648.0 | 307087.0 | Psychology & Social Work | 0.779933 | 2584 | 307933 | ... | 115172 | 174438 | 28169 | 0.083811 | 31500 | 24000 | 41000 | 125148 | 141860 | 48207 |
146 | 147 | 6002 | MUSIC | 60633.0 | 29909.0 | 30724.0 | Arts | 0.506721 | 419 | 47662 | ... | 24943 | 21425 | 3918 | 0.075960 | 31000 | 22300 | 42000 | 13752 | 28786 | 9286 |
147 | 148 | 2306 | PHYSICAL AND HEALTH EDUCATION TEACHING | 28213.0 | 15670.0 | 12543.0 | Education | 0.444582 | 259 | 23794 | ... | 7230 | 13651 | 1920 | 0.074667 | 31000 | 24000 | 40000 | 12777 | 9328 | 2042 |
148 | 149 | 6006 | ART HISTORY AND CRITICISM | 21030.0 | 3240.0 | 17790.0 | Humanities & Liberal Arts | 0.845934 | 204 | 17579 | ... | 6140 | 9965 | 1128 | 0.060298 | 31000 | 23000 | 40000 | 5139 | 9738 | 3426 |
149 | 150 | 6000 | FINE ARTS | 74440.0 | 24786.0 | 49654.0 | Arts | 0.667034 | 623 | 59679 | ... | 23656 | 31877 | 5486 | 0.084186 | 30500 | 21000 | 41000 | 20792 | 32725 | 11880 |
150 | 151 | 2901 | FAMILY AND CONSUMER SCIENCES | 58001.0 | 5166.0 | 52835.0 | Industrial Arts & Consumer Services | 0.910933 | 518 | 46624 | ... | 15872 | 26906 | 3355 | 0.067128 | 30000 | 22900 | 40000 | 20985 | 20133 | 5248 |
151 | 152 | 5404 | SOCIAL WORK | 53552.0 | 5137.0 | 48415.0 | Psychology & Social Work | 0.904075 | 374 | 45038 | ... | 13481 | 27588 | 3329 | 0.068828 | 30000 | 25000 | 35000 | 27449 | 14416 | 4344 |
152 | 153 | 1103 | ANIMAL SCIENCES | 21573.0 | 5347.0 | 16226.0 | Agriculture & Natural Resources | 0.752144 | 255 | 17112 | ... | 5353 | 10824 | 917 | 0.050862 | 30000 | 22000 | 40000 | 5443 | 9571 | 2125 |
153 | 154 | 6003 | VISUAL AND PERFORMING ARTS | 16250.0 | 4133.0 | 12117.0 | Arts | 0.745662 | 132 | 12870 | ... | 6253 | 6322 | 1465 | 0.102197 | 30000 | 22000 | 40000 | 3849 | 7635 | 2840 |
154 | 155 | 2312 | TEACHER EDUCATION: MULTIPLE LEVELS | 14443.0 | 2734.0 | 11709.0 | Education | 0.810704 | 142 | 13076 | ... | 2214 | 8457 | 496 | 0.036546 | 30000 | 24000 | 37000 | 10766 | 1949 | 722 |
155 | 156 | 5299 | MISCELLANEOUS PSYCHOLOGY | 9628.0 | 1936.0 | 7692.0 | Psychology & Social Work | 0.798920 | 60 | 7653 | ... | 3221 | 3838 | 419 | 0.051908 | 30000 | 20800 | 40000 | 2960 | 3948 | 1650 |
156 | 157 | 5403 | HUMAN SERVICES AND COMMUNITY ORGANIZATION | 9374.0 | 885.0 | 8489.0 | Psychology & Social Work | 0.905590 | 89 | 8294 | ... | 2405 | 5061 | 326 | 0.037819 | 30000 | 24000 | 35000 | 2878 | 4595 | 724 |
157 | 158 | 3402 | HUMANITIES | 6652.0 | 2013.0 | 4639.0 | Humanities & Liberal Arts | 0.697384 | 49 | 5052 | ... | 2225 | 2661 | 372 | 0.068584 | 30000 | 20000 | 49000 | 1168 | 3354 | 1141 |
158 | 159 | 4901 | THEOLOGY AND RELIGIOUS VOCATIONS | 30207.0 | 18616.0 | 11591.0 | Humanities & Liberal Arts | 0.383719 | 310 | 24202 | ... | 8767 | 13944 | 1617 | 0.062628 | 29000 | 22000 | 38000 | 9927 | 12037 | 3304 |
159 | 160 | 6007 | STUDIO ARTS | 16977.0 | 4754.0 | 12223.0 | Arts | 0.719974 | 182 | 13908 | ... | 5673 | 7413 | 1368 | 0.089552 | 29000 | 19200 | 38300 | 3948 | 8707 | 3586 |
160 | 161 | 2201 | COSMETOLOGY SERVICES AND CULINARY ARTS | 10510.0 | 4364.0 | 6146.0 | Industrial Arts & Consumer Services | 0.584776 | 117 | 8650 | ... | 2064 | 5949 | 510 | 0.055677 | 29000 | 20000 | 36000 | 563 | 7384 | 3163 |
161 | 162 | 1199 | MISCELLANEOUS AGRICULTURE | 1488.0 | 404.0 | 1084.0 | Agriculture & Natural Resources | 0.728495 | 24 | 1290 | ... | 335 | 936 | 82 | 0.059767 | 29000 | 23000 | 42100 | 483 | 626 | 31 |
162 | 163 | 5502 | ANTHROPOLOGY AND ARCHEOLOGY | 38844.0 | 11376.0 | 27468.0 | Humanities & Liberal Arts | 0.707136 | 247 | 29633 | ... | 14515 | 13232 | 3395 | 0.102792 | 28000 | 20000 | 38000 | 9805 | 16693 | 6866 |
163 | 164 | 6102 | COMMUNICATION DISORDERS SCIENCES AND SERVICES | 38279.0 | 1225.0 | 37054.0 | Health | 0.967998 | 95 | 29763 | ... | 13862 | 14460 | 1487 | 0.047584 | 28000 | 20000 | 40000 | 19957 | 9404 | 5125 |
164 | 165 | 2307 | EARLY CHILDHOOD EDUCATION | 37589.0 | 1167.0 | 36422.0 | Education | 0.968954 | 342 | 32551 | ... | 7001 | 20748 | 1360 | 0.040105 | 28000 | 21000 | 35000 | 23515 | 7705 | 2868 |
165 | 166 | 2603 | OTHER FOREIGN LANGUAGES | 11204.0 | 3472.0 | 7732.0 | Humanities & Liberal Arts | 0.690111 | 56 | 7052 | ... | 3685 | 3214 | 846 | 0.107116 | 27500 | 22900 | 38000 | 2326 | 3703 | 1115 |
166 | 167 | 6001 | DRAMA AND THEATER ARTS | 43249.0 | 14440.0 | 28809.0 | Arts | 0.666119 | 357 | 36165 | ... | 15994 | 16891 | 3040 | 0.077541 | 27000 | 19200 | 35000 | 6994 | 25313 | 11068 |
167 | 168 | 3302 | COMPOSITION AND RHETORIC | 18953.0 | 7022.0 | 11931.0 | Humanities & Liberal Arts | 0.629505 | 151 | 15053 | ... | 6612 | 7832 | 1340 | 0.081742 | 27000 | 20000 | 35000 | 4855 | 8100 | 3466 |
168 | 169 | 3609 | ZOOLOGY | 8409.0 | 3050.0 | 5359.0 | Biology & Life Science | 0.637293 | 47 | 6259 | ... | 2190 | 3602 | 304 | 0.046320 | 26000 | 20000 | 39000 | 2771 | 2947 | 743 |
169 | 170 | 5201 | EDUCATIONAL PSYCHOLOGY | 2854.0 | 522.0 | 2332.0 | Psychology & Social Work | 0.817099 | 7 | 2125 | ... | 572 | 1211 | 148 | 0.065112 | 25000 | 24000 | 34000 | 1488 | 615 | 82 |
170 | 171 | 5202 | CLINICAL PSYCHOLOGY | 2838.0 | 568.0 | 2270.0 | Psychology & Social Work | 0.799859 | 13 | 2101 | ... | 648 | 1293 | 368 | 0.149048 | 25000 | 25000 | 40000 | 986 | 870 | 622 |
171 | 172 | 5203 | COUNSELING PSYCHOLOGY | 4626.0 | 931.0 | 3695.0 | Psychology & Social Work | 0.798746 | 21 | 3777 | ... | 965 | 2738 | 214 | 0.053621 | 23400 | 19200 | 26000 | 2403 | 1245 | 308 |
172 | 173 | 3501 | LIBRARY SCIENCE | 1098.0 | 134.0 | 964.0 | Education | 0.877960 | 2 | 742 | ... | 237 | 410 | 87 | 0.104946 | 22000 | 20000 | 22000 | 288 | 338 | 192 |
172 rows × 21 columns
recent_grads.plot(x='Sample_size', y='Median', kind='scatter', title='Median vs. Sample_size')
<matplotlib.axes._subplots.AxesSubplot at 0x7f450b072cf8>
recent_grads.plot(x='Sample_size', y='Unemployment_rate', kind='scatter', title='Sample_Size vs. Unemployment_rate')
<matplotlib.axes._subplots.AxesSubplot at 0x7f450b15c748>
recent_grads.plot(x='Full_time', y='Median', kind='scatter', title='Full_time vs. Median')
<matplotlib.axes._subplots.AxesSubplot at 0x7f450b0c4be0>
recent_grads.plot(x='ShareWomen', y='Unemployment_rate', kind='scatter', title='ShareWomen vs. Unemployment_rate')
<matplotlib.axes._subplots.AxesSubplot at 0x7f4509051898>
recent_grads.plot(x='Men', y='Median', kind='scatter', title='Men vs. Median')
<matplotlib.axes._subplots.AxesSubplot at 0x7f4508fc55c0>
recent_grads.plot(x='Women', y='Median', kind='scatter', title='Women vs. Median')
<matplotlib.axes._subplots.AxesSubplot at 0x7f4508f23c88>
Observation:
Use the plots to explore the following questions: -Do students in more popular majors make more money?
I do not know exact answer, but hope so we should look to sample_size and median plot:approx 1000 graduates have salary range from 20k to 60k and few have from 60k to approx 75k; also number of graduates from range 1000 and high has average 30k to 45k. also there positive trend in the main crowd of observations.
or Full_time and Median graph also tells approx the same thing.
-Do students that majored in subjects that were majority female make more money? idk. number of women more than number of men, yes, they make money also we can see from sharewomen and unemployemnet, they is null relationship
-Is there any link between the number of full-time employees and median salary? yes, it is, 1 question.positive trend in the main crowd of observations
#first four plots:
cols = ["Sample_size", "Median", "Employed", "Full_time",
"ShareWomen", "Unemployment_rate", "Men", "Women"]
fig = plt.figure(figsize=(5, 12))
for plot in range(1, 5):
ax = fig.add_subplot(4, 1, plot)
ax = recent_grads[cols[plot]].plot(kind ='hist', rot =30)
#second four plots:
cols = ["Sample_size", "Median", "Employed", "Full_time",
"ShareWomen", "Unemployment_rate", "Men", "Women"]
fig = plt.figure(figsize=(5, 12))
for plot in range(4, 8):
ax = fig.add_subplot(4, 1, plot-3)
ax = recent_grads[cols[plot]].plot(kind ='hist', rot =30)
recent_grads['ShareWomen'].value_counts(bins=10).sort_index()
(-0.0019690000000000003, 0.0969] 3 (0.0969, 0.194] 14 (0.194, 0.291] 16 (0.291, 0.388] 22 (0.388, 0.484] 19 (0.484, 0.581] 21 (0.581, 0.678] 25 (0.678, 0.775] 29 (0.775, 0.872] 11 (0.872, 0.969] 12 Name: ShareWomen, dtype: int64
recent_grads['Median'].value_counts(bins=10).sort_index()
(21911.999, 30800.0] 24 (30800.0, 39600.0] 75 (39600.0, 48400.0] 40 (48400.0, 57200.0] 18 (57200.0, 66000.0] 11 (66000.0, 74800.0] 2 (74800.0, 83600.0] 1 (83600.0, 92400.0] 0 (92400.0, 101200.0] 0 (101200.0, 110000.0] 1 Name: Median, dtype: int64
observation:
Use the plots to explore the following questions:
What percent of majors are predominantly male? Predominantly female?
about 25 of the 172 majors consist of 58-68% women from last sharewomen value
What's the most common median salary range? median salary is 35000-40000
From other comments: Hey there. On the histogram, if we want to know how many of the majors are predominately female, we’ll focus on just the x-values above 0.5 (50%). For the bar that represents 0.5-0.6, the frequency is about 24. That means that there were 24 majors where the percentage of women was between 50-60%. The next bar (0.6-0.7), there were about 28 majors where the percentage of women was between 60-70%. So if we add up all the frequencies of just these last 5 bars, we end up with 24+28+28+10+8 = 98, which is more than half of the number of majors listed (172). So we can infer from the histogram that more than half of the majors in the dataset are predominately female.
from pandas.plotting import scatter_matrix
scatter_matrix(recent_grads[['Sample_size', 'Median']], figsize=(10,10))
array([[<matplotlib.axes._subplots.AxesSubplot object at 0x7f4508bea358>, <matplotlib.axes._subplots.AxesSubplot object at 0x7f4508e39d68>], [<matplotlib.axes._subplots.AxesSubplot object at 0x7f4508cea048>, <matplotlib.axes._subplots.AxesSubplot object at 0x7f4508d67dd8>]], dtype=object)
scatter_matrix(recent_grads[['Sample_size', 'Median', 'Unemployment_rate' ]], figsize=(10,10))
array([[<matplotlib.axes._subplots.AxesSubplot object at 0x7f4508aea320>, <matplotlib.axes._subplots.AxesSubplot object at 0x7f4508ada470>, <matplotlib.axes._subplots.AxesSubplot object at 0x7f4508a24e48>], [<matplotlib.axes._subplots.AxesSubplot object at 0x7f45089df940>, <matplotlib.axes._subplots.AxesSubplot object at 0x7f45089a9b38>, <matplotlib.axes._subplots.AxesSubplot object at 0x7f4508968fd0>], [<matplotlib.axes._subplots.AxesSubplot object at 0x7f4508937710>, <matplotlib.axes._subplots.AxesSubplot object at 0x7f45088efe10>, <matplotlib.axes._subplots.AxesSubplot object at 0x7f45088c4198>]], dtype=object)
recent_grads[:10].plot.bar(x='Major', y='ShareWomen')
recent_grads[-10:].plot.bar(x='Major', y='ShareWomen')
<matplotlib.axes._subplots.AxesSubplot at 0x7f45085e3c18>
recent_grads[:10].plot.bar(x='Major', y='Unemployment_rate')
recent_grads[-10:].plot.bar(x='Major', y='Unemployment_rate')
<matplotlib.axes._subplots.AxesSubplot at 0x7f45086f15f8>
wow, in womenshare we see that women are good at starting astronomy major to second bar full majors, especially in early childcare and communication disorder science
regarding to unemployment rate, if we compare all majors 18% nuclear engineering do not get job