mplleaflet | Easily convert matplotlib plots from Python | Data Visualization library

import json
from shapely.geometry import shape, Point

upzs = open('pensionadosactivosupz.geojson', encoding='utf-8')
upzs = json.load(upzs)

point = Point(-74.09008026123047,4.719461869021348) # longitude, latitude

for feature in upzs['f

points_x, points_y = np.random.random(size=(2,25))
origin_x, origin_y = np.random.random(size=(2,))

fig, ax = plt.subplots()
ax.plot(points_x, points_y, 'o', color='blue', alpha=0.5)
ax.plot(origin_x, origin_y, 'o', color='red', alpha=0.5

g = nx.MultiDiGraph()

df = pd.read_csv('G:\cluster_centroids.csv', delimiter=',')
df['pos'] = list(zip(df.longitude,df.latitude))
dict_pos = dict(zip(df.cluster_label,df.pos))
#print dict_pos


for row in csv.reader(open('G:\edges.csv', '

import mplleaflet
import matplotlib.pyplot as plt

lats = [54.3256, 53.2692, 53.8242, 53.2178]
lons = [2.9356, 3.6278, 2.9453, 3.2203] 

fig = plt.figure()    #This is missing in your code.
plt.plot(lons, lats, 'r.')

#And after this call 

import matplotlib.pyplot as plt
import mplleaflet
from random import randint


fig, ax = plt.subplots()
x = [randint(-10100, -9400)/100 for i in range(30)]
y = [randint(3700, 4000)/100 for i in range(30)]
ax.plot(x, y, 'bo')
mplleaflet.dis

 dic_pos = {u'0': [-77.51885109, 39.18193382],
 u'1': [-76.6688633, 39.18],
 u'2': [-77.2617, 39.1791792],
 u'3': [-77.1927, 39.1782],
 .....

import mplleaflet

fig, ax = plt.subplots()

nx.draw_networkx_nodes(GG,p