A Coding Tutorial on Datashader on Rendering Massive Datasets with High-Performance Python Visual Analytics

The provided code demonstrates a comprehensive workflow for visualizing large datasets using Datashader in Python. Here's a breakdown of each section:

Section 1: Basic Point Plotting

• Objective: To create a basic scatter plot with Datashader.
• Code:

  python
   
  1N = 30_000
  2x = rng.normal(0, 1, N)
  3y = rng.normal(0, 1, N)
  4df = pd.DataFrame({"x": x.astype(np.float32), "y": y.astype(np.float32)})
  5
  6cv = ds.Canvas(plot_width=400, plot_height=400, x_range=(-4, 4), y_range=(-4, 4))
  7ag = cv.points(df, 'x', 'y', agg=rd.count())
  8img = tf.shade(ag)
  9show(img)

Section 2: Categorical Data Plotting

• Objective: To plot categorical data using Datashader.
• Code:

  python
   
  1N_cat = 10_000
  2x = rng.normal(0, 1, N_cat

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