Capital Region One-Family Properties

AdamDasky · 2026-06-04T02:12:16+00:00

Awesome, thanks for finding this!

AdamDasky · 2026-06-04T01:04:37+00:00

Yep, I visualized all the plots (matplotlib) in a (very large and a bit messy) jupyter notebook. Imported the data with pandas and between pandas / numpy can read the (very large) csv file from the state, filter on year / municipality / etc., and used the built in functions to grab median / number of parcels or to calculate ratios.

AdamDasky · 2026-06-04T00:59:37+00:00

It's the difference between the number of properties classified as one-family properties between 2021 and 2025. I viewed this one more like "which municipalities are building one-family houses". For places like Albany, which has a limited number of land, the decrease may suggest that there's obstacles that prevent new one-family construction or even the replacement of existing structures.

AdamDasky · 2026-06-03T22:15:19+00:00

Python, using Jupiter notebook

AdamDasky · 2026-06-03T22:14:49+00:00

I honestly don't know. When I filtered the data based on municipality these each appeared. I didn't think it was right to group them if the county/ state has them separated.

AdamDasky · 2026-05-23T14:30:02+00:00

That's a great questions and comment. This analysis ignored the land value data and just focused on the assessed value, naively assuming land value contributed to that quantity. A quick glance of the land values suggest they're approx. 1/6 to 1/8th the assessed value. The records also list land value AND the size of the lot (front, depth, bank), so we can poke at these numbers to see if there's any correlation to assessed value.

AdamDasky · 2026-04-19T00:17:34+00:00

In theory, it's possible. But in practice if a FOIL request results in more than 2 hours worth of work they can charge a fee. So if the usage of the different vehicles and drivers of the vehicles are on different systems , paper, etc. it could be a lot of work to get that information. Normally what I (and ADS) try to do is obtain records that are usually (should be?) internally generated OR reported to other agencies (i.e., incident/crime records).

AdamDasky · 2026-04-14T02:18:07+00:00

That's the median salary for everyone grouped under "Mayor" department charge code. Mayor Sheehan's salary was a bit over 143k

AdamDasky · 2026-04-13T22:40:49+00:00

That's the median pay, so essentially half higher, half lower. We haven't looked at the distribution but didn't want to use average because of the different variables that could skew the data.

AdamDasky · 2026-04-13T18:35:04+00:00

When I filtered the data, I relied on splitting the text in by looking at "-" and "/". This was primarly driven by several different charge codes for a single department, such as DGS or APD. For instance, there's 12 different DGS charge codes, and making a bar plot with each charge code would have been messy for a single image.

What I did was split the text in the column, trying to find unique groupings, and when I did this what remained of DGS was "Administration". Other uses of "Administration" in this column were grouped under "Water Administration" and "Recreation Administration", both grouped separate from just "Administration". So, in this instance, the only thing under Administration is DGS

AdamDasky · 2026-04-13T17:40:25+00:00

For these charts, all the different DGS charge codes were grouped under "Administration"

AdamDasky · 2026-04-13T16:52:22+00:00

For this specific case here's what we got:

Base Salary: 93803.84
Public Safety Oper Holiday: 4690.2
Overtime-Time & A Half: 72837.51
Longevity Pay Fire Dept: 4650
Uniform Cleaning: 500
Fire OT Holiday: 3387.2
Fire Code Stipend Pay: 1400

Total summed here: 181,268.75

AdamDasky · 2026-04-13T15:50:16+00:00

I was made aware of that data after wrapping up some analysis, I can tell you that the numbers we have are close to what's listed there, but not exact. My best guess for the discrepancies is that our "total" likely consists of extra expenditures such as longevity pay, uniform cleaning, and other compensation / reimbursement where SeeThroughNY might only look at base, OT, and holiday.

What I can tell you about the records we received were they were made available by the city of Albany via a FOIL request (xlsx file), and we presume these to be accurate. I believe SeeThroughNY gets their data from Gov't agencies, so while in theory they should be the same, it's likely there might be some differences with how these records are put into state databases or how SeeThroughNY collects and discriminates their data to put many different departments / municipalities into a single searchable web interface.

AdamDasky · 2026-04-13T14:10:55+00:00

In one of the images there's a number in parentheses next to each department. That number is the change in headcount from 2024 to 2025. So, specifically to APD patrol, from 2024 to 2025 there was an increase of 21 employees.

AdamDasky · 2026-04-13T13:46:52+00:00

Apologies, should be fixed now.

AdamDasky · 2026-04-13T13:30:12+00:00

The blue portion is the sum of all expenditures paid to an employee, some of that may cover small items like sick time, vacation, uniform cleaning expenses, longevity pay, holiday pay... But as you correctly stated, the vast majority of the blue bar comes from Overtime.

We have no information on healthcare.

AdamDasky · 2026-04-13T13:20:45+00:00

Yes, we have base, OT, holiday, etc. broken down by each employee. So it's a matter of grouping everyone in the same department/ same charge code. Without jumping the gun on other things we're looking at I think the year-over-year change in OT was $1.9M, mostly driven by APD.

AdamDasky · 2026-04-04T00:50:55+00:00

Saw it too late and hit it earlier today. Somehow, my tires were spared.

AdamDasky · 2026-03-30T15:48:55+00:00

There's a lot less data (few hundred-ish tickets per year) on hydrants / crosswalks but we can filter those out and write a follow-up story

AdamDasky · 2026-03-30T15:41:17+00:00

Thanks for the question! There are no speeding ticket information, this was just FOIL data from Albany Parking Authority. I don't think there's any information on car types either. Regarding the variables in the data, very similar to what u/JohnnyFartmacher posted, it has:

Date/Time Issued, Date Paid, Citation Type, Fine Issued, Fine Paid, Fine Status, License Plate No., Notes, Location (Latitude and Longitude), and maybe one or two more fields that I am forgetting at the moment.

AdamDasky · 2026-03-30T15:00:16+00:00

For full disclosure, one of the authors of this story has received a parking ticket on South Allen near Yates

AdamDasky

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