2-Bar Chart with Error.ipynb

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"
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "RECREATE GRAPHS USING MATPLOTLIB!\n",
    "# Bar Chart with Error\n",
    "First, we are going to look at the chart called `bar_chart.png`.\n",
    "\n",
    "![bar_chart](attachment:image.png)\n",
    "\n",
    "The data you will need to recreate this chart is in the lists `past_years_averages`, `years`, and `error`.\n",
    "\n",
    "Save your recreated chart to a file called `my_bar_chart.png`.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Instructions**\n",
    "\n",
    "**1.**\n",
    "First, create a figure of width 10 and height 8.\n",
    "\n",
    "\n",
    "**2.**\n",
    "Plot the blue bars, which have the heights listed in past_years_averages.\n",
    "\n",
    "\n",
    "***Hint***\n",
    "The x-values of this bar graph would be range(len(past_years_averages)), not years.\n",
    "\n",
    "\n",
    "**3.**\n",
    "Add error bars of cap size 5 and heights corresponding to the list error.\n",
    "\n",
    "\n",
    "**4.**\n",
    "Set the axis to go from -0.5 to 6.5 on the x-axis and 70 to 95 on the y-axis.\n",
    "\n",
    "\n",
    "***Hint***\n",
    "You must attach .axis([-0.5, 6.5, 70, 95]) to plt.\n",
    "\n",
    "\n",
    "**5.**\n",
    "Create an ax object using plt.subplot(). Use ax to set the x-axis ticks to be range(len(years)) and the x-axis labels to be the years list.\n",
    "\n",
    "\n",
    "***Hint***\n",
    "You can use ax.set_xticks to set the x-axis ticks to range(len(years)).\n",
    "\n",
    "You can use ax.set_xticklabels to set x-axis labels to years.\n",
    "\n",
    "\n",
    "**6.**\n",
    "Add the title \"Final Exam Averages\", x-axis label \"Year\", and y-axis label \"Test average\".\n",
    "\n",
    "\n",
    "**7.**\n",
    "Save your figure to a file called my_bar_chart.png."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 1000x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from matplotlib import pyplot as plt\n",
    "\n",
    "past_years_averages = [82, 84, 83, 86, 74, 84, 90]\n",
    "years = [2000, 2001, 2002, 2003, 2004, 2005, 2006]\n",
    "error = [1.5, 2.1, 1.2, 3.2, 2.3, 1.7, 2.4]\n",
    "\n",
    "# Make your chart here\n",
    "plt.figure(figsize=(10,8))\n",
    "plt.bar(range(len(years)), past_years_averages, yerr=error, capsize=5)\n",
    "\n",
    "plt.axis([-.5, 6.5, 70, 95])\n",
    "\n",
    "ax = plt.subplot()\n",
    "ax.set_xticks(range(len(years)))\n",
    "ax.set_xticklabels(years)\n",
    "\n",
    "plt.title('Final Exam Averages')\n",
    "plt.xlabel('Year')\n",
    "plt.ylabel('Test Average')\n",
    "\n",
    "plt.savefig('my_bar_chart.png')\n",
    "\n",
    "plt.show()\n",
    "# plt.clf()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# without ax object\n",
    "plt.figure(figsize=(10,8))\n",
    "plt.bar(years, past_years_averages, yerr=error, capsize=5)\n",
    "plt.axis([1999.5, 2006.5, 70, 95])    # differ in this line\n",
    "\n",
    "plt.title('Final Exam Averages')\n",
    "plt.xlabel('Year')\n",
    "plt.ylabel('Test Average')\n",
    "plt.show()\n",
    "# plt.clf()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "myenv",
   "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": "3.1.0"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}