{
  "cells": [
    {
      "cell_type": "code",
      "execution_count": null,
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      "source": [
        "%matplotlib inline"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "\n# Pyplot Text\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "collapsed": false
      },
      "outputs": [],
      "source": [
        "import numpy as np\nimport matplotlib.pyplot as plt\n\n# Fixing random state for reproducibility\nnp.random.seed(19680801)\n\nmu, sigma = 100, 15\nx = mu + sigma * np.random.randn(10000)\n\n# the histogram of the data\nn, bins, patches = plt.hist(x, 50, density=True, facecolor='g', alpha=0.75)\n\n\nplt.xlabel('Smarts')\nplt.ylabel('Probability')\nplt.title('Histogram of IQ')\nplt.text(60, .025, r'$\\mu=100,\\ \\sigma=15$')\nplt.xlim(40, 160)\nplt.ylim(0, 0.03)\nplt.grid(True)\nplt.show()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        ".. admonition:: References\n\n   The use of the following functions, methods, classes and modules is shown\n   in this example:\n\n   - `matplotlib.pyplot.hist`\n   - `matplotlib.pyplot.xlabel`\n   - `matplotlib.pyplot.ylabel`\n   - `matplotlib.pyplot.text`\n   - `matplotlib.pyplot.grid`\n   - `matplotlib.pyplot.show`\n\n"
      ]
    }
  ],
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      "file_extension": ".py",
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      "name": "python",
      "nbconvert_exporter": "python",
      "pygments_lexer": "ipython3",
      "version": "3.8.10"
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  "nbformat": 4,
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