Of the 3919 files sent by the DEC, we were able to map the origin of 2611 comments (66%). An anonymized dataframe as been provided, "anon_w_locations.csv".
This csv contains:
17 of the 38 pro-renewal comments have been mapped, one being Greenidge itself. 2594 of the 3872 anti-renewal comments have been mapped. There have been 14 identified from out of state, 3 of which are pro-renewal and 11 being anti-renewal.
import folium
import pandas as pd
df = pd.read_csv("anon_w_locations.csv", index_col=0)
df = df.dropna()
df.head()
subject | month | day | year | city | region1 | postal_code | lat | lng | stance | |
---|---|---|---|---|---|---|---|---|---|---|
0 | Please Deny Title 5 Permit | 11.0 | 15.0 | 21.0 | Peekskill | New York | 10566 | 41.282600 | -73.924101 | 0 |
1 | Luc - Greenidge Generating Station | 11.0 | 19.0 | 21.0 | Ithaca | NY | 14850 | 42.435835 | -76.481422 | 0 |
2 | Jean - Deny Greenidge's Title V Air Permit | 10.0 | 9.0 | 21.0 | Mineola | NY | 11501-1365 | 40.748224 | -73.651264 | 0 |
3 | hua - Deny Greenidge's Title V Air Permit | 10.0 | 5.0 | 21.0 | Albany | NY | 12208-1010 | 42.641204 | -73.834502 | 0 |
4 | Grennidge Power Plant | 10.0 | 22.0 | 21.0 | Penn Yan | NY | 14527 | 42.716076 | -77.066421 | 1 |
print("\n")
print("Red dot - anti-renewal, Green dot - pro-renewal")
m = folium.Map(location=df[["lat", "lng"]].mean().to_list(), zoom_start=2)
markers_colors = ['red', 'green']
for lat, lng, city, suject, stance in zip(df['lat'], df['lng'], df['city'], df['subject'], df['stance']):
if stance == 0:
stance_string = "anti-renewal"
else:
stance_string = "pro-renewal"
folium.vector_layers.CircleMarker(
[lat, lng],
radius=2,
color = markers_colors[stance],
tooltip = str(city)+ ', '+stance_string,
fill=True,
fill_opacity=0.6).add_to(m)
m
Red dot - anti-renewal, Green dot - pro-renewal