fig = plt.figure(figsize=(10, 5))
ax = fig.add_subplot(1, 1, 1, projection=ccrs.PlateCarree())

# make the map global rather than have it zoom in to
# the extents of any plotted data
ax.set_global()

ax.stock_img()
ax.coastlines()

ax.tissot(facecolor='blue', alpha=0.7)

plt.show()

import cartopy.crs as ccrs
import matplotlib.pyplot as plt

# Create a list of integers from 1 - 60
zones = range(1, 61)

# Create a figure
fig = plt.figure(figsize=(18, 6))

# Loop through each zone in the list
for zone in zones:

    # Add GeoAxes object with specific UTM zone projection to the figure
    ax = fig.add_subplot(
        1, len(zones), zone,
        projection=ccrs.UTM(
            zone=zone,
            southern_hemisphere=True
        )
    )

    # Add coastlines, gridlines and zone number for the subplot
    ax.coastlines(resolution='110m')
    ax.gridlines()
    ax.set_title(zone)

# Add a supertitle for the figure
fig.suptitle("UTM Projection - Zones")

# Display the figure
plt.show()