This script illustrates the following concepts:
  • Drawing a scatter plot with markers of different colors and sizes

  • Drawing outlined and filled markers on a polar map plot

  • Generating dummy data using “random”

  • Changing the marker colors on a polar map plot

  • Changing the marker sizes on a polar map plot

  • Turning off y-axis labels

See following URLs to see the reproduced NCL plot & script:

Import packages:

import numpy as np
import matplotlib.pyplot as plt

Create dummy data:

numpoints = 100
lon = np.random.uniform(0, 360, numpoints)
lat = np.random.uniform(5, 90, numpoints)
# Generate a figure
fig = plt.figure(figsize=(8, 8))

# Create axis with a polar projection
ax = fig.add_subplot(111, projection='polar')
ax.set_ylim([0, 90])

# Change orientation of projection

# Create array of marker colors
colors = ("limegreen", "orange", "green", "red", "yellow", "purple", "blue",
          "red", "brown", "crimson", "skyblue")

# Create array of marker sizes
bins = np.linspace(100, 2000, 10)

# Plot all points
# longitude points must be transformed from degrees to radians
# to be plotted on polar projection
for x in range(numpoints):
    ax.scatter((np.pi / 180.0) * lon[x],
               color=colors[x % 10],
               s=bins[x % 10],

# set the labels and locations of the angular gridlines
linelabels = ('0', '30E', '60E', '90E', '120E', '150E', '180', '150W', '120W',
              '90E', '60E', '30E')
lines, labels = plt.thetagrids(range(0, 360, 30), linelabels, fontsize=12)

# Create distance between the x tick labels and the axis
ax.tick_params(axis='x', pad=10)

# Set y-axis gridlines and turn off y-axis labels
ax.set_yticks([0, 20, 40, 60, 80, 100])

# Make gridlines dashed
NCL scatter 6

Total running time of the script: (0 minutes 0.589 seconds)

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