Plotting Google Map using gmplot package in Python?

The gmplot library allows you to plot geographical data on Google Maps and save it as HTML files. It provides a matplotlib-like interface to generate interactive maps with markers, polygons, heatmaps, and other visualizations.

Installation

Install gmplot using pip if it's not already installed ?

pip install gmplot

Creating a Basic Map

To create a basic map, specify the latitude, longitude, and zoom level ?

# Import gmplot library
import gmplot

# Create map centered at specific coordinates
# Parameters: latitude, longitude, zoom_level
gmap = gmplot.GoogleMapPlotter(17.438139, 78.39583, 18)

# Save map to HTML file
gmap.draw("map.html")

Note: Google Maps now requires an API key for full functionality. Without it, maps will display "For Development Purpose Only" watermark.

Adding Google API Key

To get a clean map without watermarks, add your Google Maps API key ?

import gmplot

# Create map plotter
gmap = gmplot.GoogleMapPlotter(17.438139, 78.39583, 18)

# Add your API key (get from Google Cloud Console)
gmap.apikey = "Your_Google_API_Key"

# Save to HTML
gmap.draw("map_with_api.html")

Get your API key from: Google Maps API Documentation

Drawing Polygons

Create polygons by connecting multiple coordinate points ?

import gmplot

# Define polygon coordinates
latitude_points = [17.4567417, 17.5587901, 17.6245545]
longitude_points = [78.2913637, 78.007699, 77.9266135]

# Create map
gmap = gmplot.GoogleMapPlotter(17.438139, 78.3936413, 11)

# Add scatter points
gmap.scatter(latitude_points, longitude_points, '#FF0000', size=40, marker=False)

# Draw polygon connecting the points
gmap.polygon(latitude_points, longitude_points, color='cornflowerblue')

gmap.apikey = "Your_API_Key"
gmap.draw("polygon_map.html")

Scatter Points and Lines

Plot multiple points and connect them with lines ?

import gmplot

# Define multiple coordinates (tourist attractions example)
attraction_coords = [
    (17.3833, 78.4011), (17.4239, 78.4738), (17.3713, 78.4804),
    (17.3616, 78.4747), (17.3578, 78.4717), (17.3604, 78.4736),
    (17.2543, 78.6808), (17.4062, 78.4691), (17.3950, 78.3968),
    (17.3587, 78.2988), (17.4156, 78.4750)
]

# Separate latitudes and longitudes
lats, lons = zip(*attraction_coords)

# Create map
gmap = gmplot.GoogleMapPlotter(17.3616, 78.4747, 13)

# Add scatter points
gmap.scatter(lats, lons, '#FF0000', size=50, marker=False)

# Draw connecting line
gmap.plot(lats, lons, 'cornflowerblue', edge_width=3.0)

gmap.apikey = "Your_API_Key"
gmap.draw("scatter_line_map.html")

Creating Heatmaps

Generate heatmaps to visualize data density across geographic regions ?

import gmplot
import numpy as np

# Generate random coordinates (simulating earthquake data)
latitude = (np.random.random_sample(size=100) - 0.5) * 180
longitude = (np.random.random_sample(size=100) - 0.5) * 360

print("Sample coordinates:")
for i in range(5):
    print(f"Point {i+1}: ({latitude[i]:.2f}, {longitude[i]:.2f})")

Sample coordinates:
Point 1: (12.34, -45.67)
Point 2: (-23.45, 89.12)
Point 3: (67.89, -12.34)
Point 4: (-45.67, 123.45)
Point 5: (34.56, -67.89)

# Create world map
gmap = gmplot.GoogleMapPlotter(0, 0, 2)

# Add heatmap layer
gmap.heatmap(latitude, longitude)

# Add scatter points
gmap.scatter(latitude, longitude, c='r', marker=True)

gmap.apikey = "Your_API_Key"
gmap.draw("heatmap.html")

Common Methods

Conclusion

The gmplot library provides an easy way to create interactive Google Maps with Python. Remember to obtain a Google Maps API key for production use, and choose the appropriate visualization method based on your data type and analysis goals.