Plotting points on a map with calculated distance - pandas

Question

This is my dataframe
import pandas as pd
from shapely.geometry import Point
import geopandas as gpd
from geopandas import GeoDataFrame
import matplotlib.pyplot as plt
d = {"STATE" : [ "NJ", "NJ", "NJ", "NJ"],
"CATEGORY": ["A", "B", "C", "D"],
"LATITUDE" : [ 40.794856, 40.790176, 40.826762, 40.495150],
"LONGITUDE" : [ -74.149086, -74.255100, -74.101990, -74.442890]}
df = pd.DataFrame(data=d)
df.plot(kind="scatter", x="LONGITUDE", y="LATITUDE", alpha=0.4)
plt.show()
I want to calculate the distance between points based on category column:
A -> B
A -> C
A -> D
and connect the dots with distance displayed between them as a label
#creating point object so I can calculate distance bwtween coordinates
df["point"] = [Point(xy) for xy in zip(df['LONGITUDE'], df['LATITUDE'])]
#Formula I use for calculating distance between two points, this works when I have two seperate columns
#df['lat_long_diff'] = df.apply(lambda x : geodesic((x['LATITUDE_A'],x['LONGITUDE_A']),(x['LATITUDE_other_points'],x['LONGITUDE_other_points'])).miles,axis=1)
Also if I could include the Map of New Jersey as background it would be great, just the outline map would do.

Answer 1

import cartopy
import cartopy.crs as ccrs
import cartopy.feature as cfeature
import matplotlib.pyplot as plt
from matplotlib.text import Text
import geopandas as gpd
import pandas as pd
import geopy.distance
def calc_dist(point_a, point_b):
return(geopy.distance.geodesic(point_a, point_b).miles)
def draw_lines(x, y, p1 , p2):
x1, x2 = x[p1], x[p2]
y1, y2 = y[p1], y[p2]
ax.plot([x1,x2],[y1,y2])
d = {"STATE" : [ "NJ", "NJ", "NJ", "NJ"],
"CATEGORY": ["A", "B", "C", "D"],
"LATITUDE" : [ 40.794856, 40.790176, 40.826762, 40.495150],
"LONGITUDE" : [ -74.149086, -74.255100, -74.101990, -74.442890]}
df = pd.DataFrame(d)
dist_list = []
for i in [1,2,3]:
dist = calc_dist((df.at[0, 'LATITUDE'], df.at[0, 'LONGITUDE']),
(df.at[i, 'LATITUDE'], df.at[i, 'LONGITUDE']))
dist_list.append(dist)
proj = ccrs.PlateCarree(central_longitude=0)
fig, ax = plt.subplots(subplot_kw=dict(projection=proj), figsize=(16,16))
ax.set_extent([df['LONGITUDE'].min()-1,
df['LONGITUDE'].max()+ 1,
df['LATITUDE'].min()- 1,
df['LATITUDE'].max()+1],
crs=ccrs.PlateCarree())
x = df['LONGITUDE'].tolist()
y = df['LATITUDE'].tolist()
ax.scatter(x, y)
draw_lines(x, y, 0, 1)
draw_lines(x, y, 0, 2)
draw_lines(x, y, 0, 3)
ax._add_text(Text(text=str(round(dist_list[0], 2)), x=-74.20, y=40.82))
ax._add_text(Text(text=str(round(dist_list[1], 2)), x=-74.12, y= 40.8))
ax._add_text(Text(text=str(round(dist_list[2], 2)), x=-74.29, y= 40.64))
ax.add_feature(cfeature.STATES.with_scale('10m'), zorder=0)
fig.canvas.draw()
fig.tight_layout()
plt.show()