Toolkit 0 & 1

[swastisingh2]

Tool 0:
input: some way to define an are of interest
GTFS file OR
feed in shapefile OR
GeoJSON OR
other…
output:
geographic areas
centroids of census tracts? block groups? blocks?
stats for the geographic areas
like population, cars per capita, race, income, …
https://www.census.gov/data/developers/guidance/api-user-guide.html?

Tool 1:
input: the geographic regions
Output:
services of interest (e.g., pulled from Yelp)

[NIHARSIMHADRI]

import folium
import geopandas as gpd

m = folium.Map(location=[block_groups["lat"].mean(), block_groups["lon"].mean()], zoom_start=8)

for _, row in block_groups.iterrows():
folium.GeoJson(
row.geometry,
style_function=lambda x: {
"color": "black",
"weight": 1,
"fillOpacity": 0,
}
).add_to(m)

for _, row in block_groups.iterrows():
folium.CircleMarker(
location=[row["lat"], row["lon"]],
radius=3,
color="red",
fill=True,
fill_color="red"
).add_to(m)

for _, row in block_groups.iterrows():
folium.Circle(
location=[row["lat"], row["lon"]],
radius=1000,
color="blue",
weight=1,
fill=False,
dash_array="5, 5"
).add_to(m)

m.save("block_groups_centroids_map.html")
print("Map saved to block_groups_centroids_map.html ✅")

[NIHARSIMHADRI]

Run the code above to see a visualization of the issue with hard-coding the radius to 1000 meters from each centroid for each block group.

[tylerharter]

Good start!

Let's also have a README describing what the tools are and how to use them.

[tylerharter]

Let's not put actual data in this repo. Just the tools.

[tylerharter]

Let's have a different file for each program. Let's use short, descriptive names for the programs, without special characters.

[tylerharter]

Let's have a main() function for this.

[tylerharter]

No hardcoding paths.

[tylerharter]

itertuples is much faster that iterrows.