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   "source": [
    "### <center>San Jose State University<br>Department of Applied Data Science<br><br>**DATA 200<br>Computational Programming for Data Analytics**<br><br>Spring 2024<br>Instructor: Ron Mak</center>"
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   "source": [
    "#### Module `matplotlib` contains Python's the most popular graphing library. It emulates the graphing capabilities of MATLAB, a commercial package of scientific and mathematical software. `matplotlib.pyplot` is a collection of plotting functions, usually imported as `plt`.\n",
    "#### A `matplotlib` plot is an object that contains multiple objects (the object-oriented *has-a* relationship) nested in a tree structure. \n",
    "#### The top visualization container is a `Figure` object. It is the outermost container which serves as the canvas upon which we can draw multiple plots."
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   "source": [
    "# Creating a simple visualization."
   ]
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   "metadata": {},
   "source": [
    "#### In this exercise, we will create our first simple plot using Matplotlib."
   ]
  },
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   "metadata": {},
   "source": [
    "## Import statements"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Import the necessary modules and enable plotting within a Jupyter notebook."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
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   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "%matplotlib inline"
   ]
  },
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   "metadata": {},
   "source": [
    "## Create a figure"
   ]
  },
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   "metadata": {},
   "source": [
    "#### Explicitly create a figure and set the dpi (dots per inch) to 200."
   ]
  },
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   "cell_type": "code",
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   "outputs": [],
   "source": [
    "plt.figure(dpi=200)"
   ]
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   "metadata": {},
   "source": [
    "## Plot data pairs"
   ]
  },
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   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Plot the following (x, y) data points: (1, 1), (2, 3), (4, 4), (5, 3). Therefore, the x values are `[1, 2, 4, 5]` and the y values are `[1, 3, 4, 3]`. Show the data points as circles connected by line segments: `-o`. Show the plot."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "plt.plot([1, 2, 4, 5], [1, 3, 4, 3], '-o')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Format strings"
   ]
  },
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   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### In the previous example, the argument string `'-o'` is a ***format string*** of the form '*color marker line-type*' where each item is optional.\n",
    "- #### For *color*, see [Specifying colors](https://matplotlib.org/stable/tutorials/colors/colors.html) and [List of named colors](https://matplotlib.org/stable/gallery/color/named_colors.html)\n",
    "- #### For *marker*, see [matplotlib.markers](https://matplotlib.org/stable/api/markers_api.html)\n",
    "- #### For *line-type*, see [Line Plot Styles in Matplotlib](https://medium.com/swlh/line-plot-styles-in-matplotlib-c6ffd7a34d46)\n",
    "#### Therefore, `'-o'` specifies a solid line with filled circles as markers, and the default color is black."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "plt.close()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Adapted from ***Data Visualization with Python***, by Mario Döbler and Tim Großmann, Packt 2019, ISBN 978-1-78995-646-7"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Additional material (c) 2024 by Ronald Mak"
   ]
  }
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