How to add map with cluster points with geopandas and contextily

Question

I'm new to geopandas and contextily and would like to understand how it works better. I have some geometry points to be plotted that have been clustered. On top of that I would like to add a map below it.

I have done this to generate my clusters.

from sklearn.preprocessing import StandardScaler

# Scale the latitude and longitude columns
scaler = StandardScaler()
mrt[['longitude', 'latitude']] = scaler.fit_transform(mrt[['latitude', 'longitude']])


from sklearn.cluster import KMeans

# Specify the number of clusters
num_clusters = 5

# Initialize the KMeans model
kmeans = KMeans(n_clusters=num_clusters)

# Fit the model to the data
kmeans.fit(mrt[['longitude', 'latitude']])

# Get the cluster labels for each data point
cluster_labels = kmeans.labels_

Then this is where i get stuck trying to plot the cluster points AND the background map together.

import matplotlib.pyplot as plt

# Plot the data points with their cluster labels
plt.scatter(mrt['longitude'], mrt['latitude'], c=cluster_labels)
plt.xlabel('Longitude')
plt.ylabel('Latitude')
plt.title('Clustering of Geo Location Coordinates')

sg = ctx.Place("Singapore", source=ctx.providers.OpenStreetMap.Mapnik)
x = plt.show()
y = sg.plot()

Basically I would like to put the bottom map 'sg' onto my plot.

enter image description here

I have tried add_basemap but can't seem to get it working. Not very familiar with this, any advice?

Answer 1

Firstly, create ax and fig, and use ax like parameters in code:

fig,ax = plt.subplots(1,1,figsize=(10,12))

# Plot the data points with their cluster labels
plt.scatter(mrt['longitude'], mrt['latitude'], c=cluster_labels,ax=ax)
plt.xlabel('Longitude')
plt.ylabel('Latitude')
plt.title('Clustering of Geo Location Coordinates')

sg = ctx.Place("Singapore", source=ctx.providers.OpenStreetMap.Mapnik,ax=ax)
plt.show()