{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "\n# Scatter plot with masked values\n\nMask some data points and add a line demarking\nmasked regions.\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "collapsed": false
      },
      "outputs": [],
      "source": [
        "import matplotlib.pyplot as plt\nimport numpy as np\n\n# Fixing random state for reproducibility\nnp.random.seed(19680801)\n\n\nN = 100\nr0 = 0.6\nx = 0.9 * np.random.rand(N)\ny = 0.9 * np.random.rand(N)\narea = (20 * np.random.rand(N))**2  # 0 to 10 point radii\nc = np.sqrt(area)\nr = np.sqrt(x ** 2 + y ** 2)\narea1 = np.ma.masked_where(r < r0, area)\narea2 = np.ma.masked_where(r >= r0, area)\nplt.scatter(x, y, s=area1, marker='^', c=c)\nplt.scatter(x, y, s=area2, marker='o', c=c)\n# Show the boundary between the regions:\ntheta = np.arange(0, np.pi / 2, 0.01)\nplt.plot(r0 * np.cos(theta), r0 * np.sin(theta))\n\nplt.show()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        ".. tags::\n\n   component: marker\n   plot-type: scatter\n   level: beginner\n\n"
      ]
    }
  ],
  "metadata": {
    "kernelspec": {
      "display_name": "Python 3",
      "language": "python",
      "name": "python3"
    },
    "language_info": {
      "codemirror_mode": {
        "name": "ipython",
        "version": 3
      },
      "file_extension": ".py",
      "mimetype": "text/x-python",
      "name": "python",
      "nbconvert_exporter": "python",
      "pygments_lexer": "ipython3",
      "version": "3.13.2"
    }
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  "nbformat": 4,
  "nbformat_minor": 0
}