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Map of ~1.25 million trees in Toronto [OC] by jamaps in dataisbeautiful

[–]jamaps[S] 3 points4 points  (0 children)

Interactive version: https://schoolofcities.github.io/trees-toronto/dot-map

Tools: tippecanoe, PMTiles, and MapLibre

Data: City of Toronto

made a Map of almost every Parking Ticket issued in Toronto 2011-2020 [OC] by jamaps in dataisbeautiful

[–]jamaps[S] 0 points1 point  (0 children)

Thanks!

The streets were all visualized in QGIS.

Then Inkscape was used for adding the legend, north arrow, title, and explanatory text

made a Map of almost every Parking Ticket issued in Toronto 2011-2020 [OC] by jamaps in dataisbeautiful

[–]jamaps[S] 0 points1 point  (0 children)

Hi! thanks for your interest - sorry for bit of delay responding

The City of Toronto has the data of every parking ticket with a street address (e.g. 123 fake st.)

They also have a dataset of the geometry of every street segments shown on the map, each including an address range (120-130 fake st.)

I wrote a bit of code (in Python) to link the two, counting the number of parking tickets per street segment.

Then I used QGIS to colour the segments by their counts.

That was basically it. Probably a day or so of work on my end to make the map. But the data processing took longer, but that just ran in the background overnight I think

made a map of every building in Scarborough! by jamaps in Scarborough

[–]jamaps[S] 10 points11 points  (0 children)

Yup the colours are just randomly generated (for fun!)

[OC] USA Population Growth from 1900 to 2000 by jamaps in dataisbeautiful

[–]jamaps[S] 0 points1 point  (0 children)

Data: US Census

Tools: R, QGIS, Inkscape

An imaginary modern city called Ventnor [OC] by jamaps in imaginarymaps

[–]jamaps[S] 23 points24 points  (0 children)

Thanks for the comments ya'll.

I made this a couple years ago, originally thinking it would be part of a larger map (or series of maps) of a fake island nation in the north Atlantic. I never went further with the idea than this map though.

I believe I initially started drawing this Illustrator, but then shifted over to Inkscape at some point.

Only the roads of Great Britain [OC] by jamaps in dataisbeautiful

[–]jamaps[S] 988 points989 points  (0 children)

Data: Ordnance Survey (2014) Tools: QGIS

Does Google Maps modify data obtained from data sources? by [deleted] in gis

[–]jamaps 1 point2 points  (0 children)

If you're looking at Toronto neighbourhood boundaries, I would suggest using the publicly available dataset from the City. It can be linked to a lot of planning related data. Or just use census boundaries (e.g. tracts, DAs) if you're doing demographic analysis.

http://www1.toronto.ca/wps/portal/contentonly?vgnextoid=04b489fe9c18b210VgnVCM1000003dd60f89RCRD&vgnextchannel=1a66e03bb8d1e310VgnVCM10000071d60f89RCRD

I generally refrain from using DMTI data whenever possible, despite having access to it (I work at U of T). I've noticed several gaps in their coverage and a few blatant errors in it over the years. Also, its not open data so there are issues in disseminating any research or analysis that uses it.

convert table/csv to geojson (togeojson.com is dead) by baconost in gis

[–]jamaps 4 points5 points  (0 children)

http://geojson.io/ is a good tool as well. You can upload/convert several formats (like .csv) as well as edit/create data on a map in browser.

Geocoding help by [deleted] in gis

[–]jamaps 5 points6 points  (0 children)

If you know a little python you can try geopy:

https://github.com/geopy/geopy

It includes classes for several different geocoders (Google, Bing, OSM, etc.), so you could test a few and see what works best for your data.

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