F0C-06-BasicPlots.ipynb

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    "# FLIP (00): Data Science \n",
    "**(Module 02: Data Visualization)**\n",
    "\n",
    "---\n",
    "- Materials in this module include resources collected from various open-source online repositories.\n",
    "- You are free to use,but NOT allowed to change and distribute this package.\n",
    "\n",
    "Prepared by and for \n",
    "**Student Members** |\n",
    "2006-2023 [TULIP Lab](http://www.tulip.org.au), Australia\n",
    "\n",
    "---"
   ]
  },
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   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Session G - Basic Plots \n",
    "\n",
    "Making basic plots - Lines, bars, pies, and scatterplots in this lesson.\n",
    "\n",
    "* Notebook by [Randal S. Olson](http://www.randalolson.com/)\n",
    "\n",
    "* Please see the [repository README file](https://github.com/rhiever/python-data-visualization-course#license-and-usage-terms) for the licenses and usage terms for the instructional material and code in this notebook. In general, I have licensed this material so that it is as widely usable and shareable as possible."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Line plots\n",
    "\n",
    "**Purpose**: Showing trends in data -- usually time series data with many time points.\n",
    "\n",
    "**matplotlib function**: [`plot(x, y)`](http://matplotlib.org/api/pyplot_api.html#matplotlib.pyplot.plot)\n",
    "\n",
    "* `x`: The x-coordinates of the lines or markers.\n",
    "\n",
    "* `y`: The y-coordinates of the lines or markers."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
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   "outputs": [],
   "source": [
    "x = np.linspace(0, 20)\n",
    "y1 = np.sin(x)\n",
    "y2 = np.sin(x - np.pi)\n",
    "\n",
    "plt.figure()\n",
    "\n",
    "plt.plot(x, y1)\n",
    "plt.plot(x, y2)\n",
    ";"
   ]
  },
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   "source": [
    "**Commonly used parameters**:\n",
    "\n",
    "* `color`: Set the color of the line.\n",
    "\n",
    "* `linestyle`: Set the line style, e.g., solid, dashed, or none.\n",
    "\n",
    "* `linewidth`: Set the line thickness.\n",
    "\n",
    "* `marker`: Set the marker style, e.g., circles, triangles, or none.\n",
    "\n",
    "* `markersize`: Set the marker size.\n",
    "\n",
    "* `label`: Set the label for the line that will show up in the legend."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "x = np.linspace(0, 20)\n",
    "y1 = np.sin(x)\n",
    "y2 = np.sin(x - np.pi)\n",
    "\n",
    "plt.figure()\n",
    "\n",
    "plt.plot(x,\n",
    "         y1,\n",
    "         color='black',\n",
    "         linestyle='-',\n",
    "         linewidth=2,\n",
    "         marker='s',\n",
    "         markersize=6,\n",
    "         label='y1')\n",
    "\n",
    "plt.plot(x,\n",
    "         y2,\n",
    "         color='gray',\n",
    "         linestyle='--',\n",
    "         linewidth=2,\n",
    "         marker='^',\n",
    "         markersize=6,\n",
    "         label='y2')\n",
    "\n",
    "plt.legend()\n",
    ";"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Vertical bar charts\n",
    "\n",
    "**Purpose**: Comparing categories **OR** showing temporal trends in data with few (< 4) time points.\n",
    "\n",
    "**matplotlib function**: [`bar(left, height)`](http://matplotlib.org/api/pyplot_api.html#matplotlib.pyplot.bar)\n",
    "\n",
    "* `left`: The x coordinate(s) of the left sides of the bars.\n",
    "\n",
    "* `height`: The height(s) of the bars."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "years = np.arange(2012, 2015)\n",
    "values = [2, 5, 9]\n",
    "\n",
    "plt.figure()\n",
    "\n",
    "plt.bar(years, values)\n",
    ";"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Commonly used parameters**:\n",
    "\n",
    "* `color`: Set the color of the bars.\n",
    "\n",
    "* `edgecolor`: Set the color of the lines on the edges of the bars.\n",
    "\n",
    "* `width`: Set the width of the bars.\n",
    "\n",
    "* `align`: Set the alignment of the bars, e.g., center them on the x coordinate(s).\n",
    "\n",
    "* `label`: Set the label for the bar that will show up in the legend."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "years = np.arange(2012, 2015)\n",
    "category1_values = [2, 5, 9]\n",
    "category2_values = [7, 6, 3]\n",
    "\n",
    "plt.figure()\n",
    "\n",
    "plt.bar(years - 0.2,\n",
    "        category1_values,\n",
    "        color='blue',\n",
    "        edgecolor='none',\n",
    "        width=0.4,\n",
    "        align='center',\n",
    "        label='y1')\n",
    "\n",
    "plt.bar(years + 0.2,\n",
    "        category2_values,\n",
    "        color='orange',\n",
    "        edgecolor='none',\n",
    "        width=0.4,\n",
    "        align='center',\n",
    "        label='y2')\n",
    "\n",
    "plt.xticks(years, [str(year) for year in years])\n",
    "\n",
    "plt.legend()\n",
    ";"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Horizontal bar charts\n",
    "\n",
    "**Purpose**: Comparing categories.\n",
    "\n",
    "**matplotlib function**: [`barh(bottom, width)`](http://matplotlib.org/api/pyplot_api.html#matplotlib.pyplot.barh)\n",
    "\n",
    "* `bottom`: The y coordinate(s) of the bars.\n",
    "\n",
    "* `width`: The width(s) of the bars."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "categories = ['A', 'B', 'C', 'D', 'E']\n",
    "values = [7, 12, 4, 2, 9]\n",
    "\n",
    "plt.figure()\n",
    "\n",
    "plt.barh(np.arange(len(categories)), values)\n",
    "\n",
    "plt.yticks(np.arange(len(categories)),\n",
    "           ['Category {}'.format(x) for x in categories])\n",
    ";"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "categories = ['A', 'B', 'C', 'D', 'E']\n",
    "values = [7, 12, 4, 2, 9]\n",
    "\n",
    "plt.figure()\n",
    "\n",
    "plt.barh(-np.arange(len(categories)), values)\n",
    "\n",
    "plt.yticks(-np.arange(len(categories)),\n",
    "           ['Category {}'.format(x) for x in categories])\n",
    ";"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Commonly used parameters**:\n",
    "\n",
    "* `color`: Set the color of the bars.\n",
    "\n",
    "* `edgecolor`: Set the color of the lines on the edges of the bars.\n",
    "\n",
    "* `height`: Set the height of the bars.\n",
    "\n",
    "* `align`: Set the alignment of the bars, e.g., center them on the y coordinate(s)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "categories = ['A', 'B', 'C', 'D', 'E']\n",
    "values = [7, 12, 4, 2, 9]\n",
    "\n",
    "plt.figure()\n",
    "\n",
    "plt.barh(-np.arange(len(categories)),\n",
    "         values,\n",
    "         color='blue',\n",
    "         edgecolor='none',\n",
    "         height=0.6,\n",
    "         align='center')\n",
    "\n",
    "plt.yticks(-np.arange(len(categories)),\n",
    "           ['Category {}'.format(x) for x in categories])\n",
    ";"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "\n",
    "categories = ['A', 'B', 'C', 'D', 'E']\n",
    "values = [7, 12, 4, 2, 9]\n",
    "\n",
    "category_values = pd.DataFrame({'categories': categories,\n",
    "                                'values': values})\n",
    "\n",
    "# Note that pandas' sort function has been deprecated in version \n",
    "# 0.17 and will be removed in a future version.\n",
    "\n",
    "# category_values.sort('values', ascending=False, inplace=True)\n",
    "category_values.sort_values(by='values', ascending=False, inplace=True)\n",
    "\n",
    "categories = category_values['categories'].values\n",
    "values = category_values['values'].values\n",
    "\n",
    "plt.figure()\n",
    "\n",
    "plt.barh(-np.arange(len(categories)),\n",
    "         values,\n",
    "         color='blue',\n",
    "         edgecolor='none',\n",
    "         height=0.6,\n",
    "         align='center')\n",
    "\n",
    "plt.yticks(-np.arange(len(categories)),\n",
    "           ['Category {}'.format(x) for x in categories])\n",
    ";"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Pie charts\n",
    "\n",
    "**Purpose**: Displaying a simple proportion.\n",
    "\n",
    "**matplotlib function**: [`pie(sizes)`](http://matplotlib.org/api/pyplot_api.html#matplotlib.pyplot.pie)\n",
    "\n",
    "* `sizes`: The size of the wedges as either a fraction or number."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "counts = [17, 14]\n",
    "\n",
    "plt.figure()\n",
    "\n",
    "plt.pie(counts)\n",
    ";"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "counts = [17, 14]\n",
    "\n",
    "plt.figure(figsize=(4, 4))\n",
    "\n",
    "plt.pie(counts)\n",
    ";"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Commonly used parameters**:\n",
    "\n",
    "* `colors`: Set the colors of the wedges.\n",
    "\n",
    "* `labels`: Set the labels of the wedges.\n",
    "\n",
    "* `startangle`: Set the angle that the wedges start at.\n",
    "\n",
    "* `autopct`: Set the percentage display format of the wedges."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "counts = [17, 14]\n",
    "\n",
    "plt.figure(figsize=(4, 4))\n",
    "\n",
    "plt.pie(counts,\n",
    "        colors=['blue', 'orange'],\n",
    "        labels=['Category A', 'Other categories'],\n",
    "        startangle=90,\n",
    "        autopct='%1.1f%%')\n",
    ";"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Scatter plots\n",
    "\n",
    "**Purpose**: Displaying relationships between variables.\n",
    "\n",
    "**matplotlib function**: [`scatter(x, y)`](http://matplotlib.org/api/pyplot_api.html#matplotlib.pyplot.scatter)\n",
    "\n",
    "* `x`, `y`: The values for the two variables."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "x = range(20)\n",
    "y = np.arange(50, 70) + (np.random.random(20) * 10.)\n",
    "\n",
    "plt.figure()\n",
    "\n",
    "plt.scatter(x, y)\n",
    ";"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Commonly used parameters**:\n",
    "\n",
    "* `c`: Set the color of the markers.\n",
    "\n",
    "* `s`: Set the size of the markers.\n",
    "\n",
    "* `marker`: Set the marker style, e.g., circles, triangles, or squares.\n",
    "\n",
    "* `edgecolor`: Set the color of the lines on the edges of the markers."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "x = np.arange(20)\n",
    "y = np.arange(50, 70) + (np.random.random(20) * 10.)\n",
    "\n",
    "plt.figure()\n",
    "\n",
    "plt.scatter(x,\n",
    "            y,\n",
    "            c='red',\n",
    "            s=40,\n",
    "            marker='s',\n",
    "            edgecolor='none')\n",
    ";"
   ]
  }
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