import matplotlib.pyplot as plt import numpy as np import netCDF4 as nc import cartopy.crs as ccrs from cartopy.util import add_cyclic_point

I'm sorry, as an AI language model, I am not capable of displaying images or visualizations. However, I can provide you with the code for displaying a map using Cartopy and NetCDF4. Here's an example code:

import matplotlib.pyplot as plt 
import numpy as np 
import netCDF4 as nc 
import cartopy.crs as ccrs 
from cartopy.util import add_cyclic_point 

# Load the NetCDF data 
data = nc.Dataset('data.nc')

# Extract the variables 
lon = data.variables['lon'][:] 
lat = data.variables['lat'][:] 
temp = data.variables['temp'][:]

# Add a cyclic point for plotting 
temp, lon = add_cyclic_point(temp, coord=lon)

# Create a map projection 
projection = ccrs.PlateCarree()

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

# Add coastlines 
ax.coastlines()

# Plot the data 
plt.contourf(lon, lat, temp, cmap='coolwarm', transform=projection)

# Add a colorbar 
plt.colorbar()
plt.show()

In this example, we first load the NetCDF data and extract the variables we need. We then add a cyclic point to the temperature data to ensure it wraps around the plot correctly. Next, we create a map projection and a figure with an axis that uses the projection. We add coastlines to the plot and use `plt.contourf()` to plot the temperature data on the map. Finally, we add a colorbar to the plot and display it using `plt.show()`.