Creating a World Map with Land and Borders

This function creates a global map with land and borders using the Cartopy and Matplotlib libraries.

Technology Stack : Cartopy, Matplotlib, NumPy

Code Type : Geographic Information Visualization

Code Difficulty : Intermediate

                
                    
import numpy as np
import cartopy.crs as ccrs
import cartopy.feature as cfeature
import matplotlib.pyplot as plt

def plot_world_map_with_land_and_borders():
    # Create a figure and an axis
    fig, ax = plt.subplots(subplot_kw={'projection': ccrs.PlateCarree()})

    # Add land and borders
    ax.add_feature(cfeature.LAND)
    ax.add_feature(cfeature.BORDERS)

    # Set the extent of the map
    ax.set_extent([0, 180, -90, 90])

    # Show the plot
    plt.show()

# Code Explanation
# This function creates a world map with land and borders using Cartopy and Matplotlib. It first creates a figure and an axis with a PlateCarree projection, which is suitable for world maps. It then adds land and borders using the features provided by Cartopy. The extent of the map is set to cover the entire world, and the plot is displayed using Matplotlib.

# Technical Stack Explanation
# This code uses the Cartopy library to create geographic plots, specifically a world map. Cartopy is built on top of Matplotlib and provides a high-level interface for drawing maps. The code also uses NumPy for numerical operations, which are often used in data manipulation and analysis.

# Code Explanation in English
# This function generates a world map with land and borders using the Cartopy and Matplotlib libraries. It initializes a figure and an axis with a PlateCarree projection, which is ideal for world maps. It then adds land and border features to the map using the Cartopy feature library. The map's extent is set to encompass the entire globe, and the map is displayed using Matplotlib.

# Technical Stack Explanation in English
# The code utilizes the Cartopy library to create geographic plots, particularly a world map. Cartopy is built upon Matplotlib and offers a high-level interface for drawing maps. NumPy is also employed for numerical operations, commonly used in data manipulation and analysis.