MBTA Salary Analysis
I have updated the code to include year 2015 data, thanks to Matthew Rocheleau, the Boston Globe staff reporter on the 22 Dec 2015 MBTA overtime article.
An example of extracting text tables from PDF, then loading with Pandas to look for interesting aspects of the data.
For example, in 2014, the top MBTA earner was a Technician with an estimated $145 K of overtime on top of an $89 K salary. Excessive overtime can be a concern for worker performance and safety in any field, with possible drastic consequences for the public when working in sensitive areas like transportation and medicine.
The Washingtonian published a 9 Dec 2015 article by Luke Mullins and Michael Gaynor that explores at length issues with WMATA and overtime abuses.
Note: I exclude Backpay as it represents a retroactive increase in base salary for the previous year. Backpay is last year's pay, paid out this year.
Contents
Examples of MBTA Salary Plots and Statistics
We currently have 2013-2015 salary data. Other trend analyses may find it useful to request prior years data.
2015 MBTA Salary
python salary.py EMP-2015-Gross-Bpay-Ovt.xlsx 2015
yields plots and the output:
Highest earning MBTA staff $256080 in 2015 was a Foreperson,Section, including estimated $171257 overtime.
| type | max | median | 90th | subtot | num |
|---|---|---|---|---|---|
| signal | 182049 | 117083 | 151384 | 2e+07 | 157 |
| maint | 256080 | 97309 | 134881 | 2e+08 | 1743 |
| ops | 145266 | 96538 | 113948 | 1e+07 | 128 |
| police | 203553 | 93684 | 136959 | 3e+07 | 271 |
| heavy | 178438 | 80498 | 103964 | 5e+07 | 678 |
| bus-ft | 120281 | 75542 | 91287 | 1e+08 | 1304 |
| subway | 158950 | 73563 | 94860 | 4e+07 | 628 |
| bus-pt | 54738 | 40934 | 49124 | 2e+07 | 410 |
| rest | 231589 | 87497 | 122225 | 1e+08 | 1149 |
| all | 256080 | 82319 | 118860 | 5e+08 | 6468 |
2014 MBTA Salary
python salary.py Wages2014.txt 2014
yields plots and the output:
Highest earning MBTA staff $235194 in 2014 was a Technician,Power Equip, including estimated $145401 overtime.
| type | max | median | 90th | subtot | num |
|---|---|---|---|---|---|
| signal | 179689 | 110775 | 127210 | 2e+07 | 155 |
| police | 221910 | 107261 | 165080 | 3e+07 | 259 |
| maint | 235194 | 95772 | 131344 | 2e+08 | 1727 |
| ops | 138506 | 93504 | 115208 | 1e+07 | 131 |
| heavy | 224458 | 90492 | 120647 | 6e+07 | 670 |
| bus-ft | 196809 | 88447 | 109504 | 1e+08 | 1337 |
| subway | 185242 | 84203 | 111710 | 4e+07 | 576 |
| bus-pt | 66435 | 33326 | 52231 | 1e+07 | 345 |
| rest | 220000 | 86463 | 129061 | 1e+08 | 1132 |
| all | 235194 | 89251 | 123618 | 5e+08 | 6332 |
MBTA 2013 Salary
python salary.py "FOIA 14-11 final.txt" 2013
yields plots and the output:
Highest earning MBTA staff $238770 in 2013 was a General Manager
| type | max | median | 90th | subtot | num |
|---|---|---|---|---|---|
| signal | 164161 | 109078 | 122121 | 1e+07 | 139 |
| police | 205400 | 108173 | 162941 | 3e+07 | 245 |
| maint | 209113 | 87132 | 113655 | 1e+08 | 1705 |
| ops | 127287 | 82337 | 98121 | 1e+07 | 131 |
| heavy | 154684 | 72266 | 99978 | 5e+07 | 654 |
| bus-ft | 192440 | 69327 | 87284 | 9e+07 | 1279 |
| subway | 133214 | 66729 | 87589 | 3e+07 | 517 |
| bus-pt | 53263 | 34434 | 42247 | 1e+07 | 358 |
| rest | 238770 | 78120 | 112847 | 9e+07 | 1098 |
| all | 238770 | 75818 | 108951 | 5e+08 | 6126 |
Obtaining Salary Data
You will need to download and convert the salary data first. Each year's format is a little different.
2015 Salary Data
I obtained this data from Matthew Rocheleau, the Boston Globe staff reporter on the 22 Dec 2015 MBTA overtime article. We anticipate a request for the whole year 2015 data once we're into 2016.
2014 Salary Data
-
Extract text from PDF, using pdftotext:
pdftotext -layout Wages2014.pdf
2013 Salary Data
-
Extract text from PDF, using pdftotext:
pdftotext -layout "FOIA 14-11 final.pdf"
3. The last three lines of this .txt file are missing a space between the salary and "2013". Just open in a text editor and manually add one additional space before 2013 in these last three lines.
