matplotlib.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "e5e0683d646d599f",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "## Line Plot\n",
    "\n",
    "#### Notes\n",
    "\n",
    "`plt.clf()` to clear\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "dd6b3f3593f20982",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-09-06T12:27:33.061589281Z",
     "start_time": "2023-09-06T12:27:32.586049015Z"
    },
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import pandas as pd\n",
    "\n",
    "year = [2000, 2010, 2020, 2030, 2040]\n",
    "pop = [2000, 4000, 1000, 3000, 5000]\n",
    "\n",
    "# Make a line plot: year on the x-axis, pop on the y-axis\n",
    "plt.plot(year, pop, \"-o\")\n",
    "\n",
    "# Customization\n",
    "# ---------------------------------------------\n",
    "\n",
    "plt.xlabel(\"Year\")\n",
    "plt.ylabel(\"Population\")\n",
    "plt.title(\"World Population Projections\")\n",
    "plt.yticks(\n",
    "    [0, 1000, 2000, 3000, 4000, 5000, 6000], [0, \"1k\", \"2k\", \"3k\", \"4k\", \"5k\", \"6k\"]\n",
    ")\n",
    "plt.text(2010, 500, \"Text\")\n",
    "plt.grid(True)\n",
    "plt.xlim(2000, None)\n",
    "# ---------------------------------------------\n",
    "\n",
    "# Display the plot with plt.show()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f388cadb",
   "metadata": {},
   "source": [
    "## Scatter Plot\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "143606bb",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "#### Note\n",
    "\n",
    "Use log scale\n",
    "\n",
    "`plt.xscale('log')`\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "1021a25c",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-09-06T12:27:33.210316274Z",
     "start_time": "2023-09-06T12:27:33.078370011Z"
    },
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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2DxSXqLo66cgRaf9+KSfnXACprPQ/3r/f315X156jBACEoFXh49ixY7r//vv1u9/9Tr169Qqs93g8euONN/Rf//VfuuWWWzRs2DAtWrRImzdv1pYtW8I2aFxCMjKkkhIpK+tcANm8+VzwyMryt2dktO84AQAt1qrwUVhYqDvuuEO5ublB68vLy3Xq1Kmg9YMGDVJmZqbKysqa3ZbP55PX6w1agCBud3AAGT06OHi43e09QgBACEIOH8uXL9cXX3yh4uLiJm01NTWKjY1Vz549g9anpqaqpqam2e0VFxfL5XIFFjcfJGiO2y0tWRK8bskSggcARKGQwkdlZaV+9atfaenSperevXtYBlBUVCSPxxNYKs+fVAhI/jkekycHr5s8uekkVABAhxdS+CgvL9eRI0d0/fXXKyYmRjExMSotLdXLL7+smJgYpaam6uTJkzp69GjQ82pra5WWltbsNuPi4uR0OoMWIEjjyaVZWdKmTcFzQAggABBVQgof48aN086dO7V9+/bAcsMNN+j+++8P/NytWzdt2LAh8JyKigodOnRI2dnZYR88LgFVVU0nl44a1XQS6oXuAwIA6HBiQumcmJioIUOGBK277LLLlJycHFj/8MMPa9asWUpKSpLT6dT06dOVnZ2tkSNHhm/UuHQkJkopKf6fG08ubZiEmpPjb09MbKcBAgBCFVL4aIl58+apS5cumjhxonw+n/Ly8jR//vxwvwwuFS6XtHat/z4e519O63ZLpaX+4OFytc/4AAAhcxhjTHsPojGv1yuXyyWPx8P8DwAAokQon998twsAALCK8AEAAKwifAAAAKsIHwAAwCrCBwAAsIrwAQAArCJ8AAAAqwgfAADAKsIHAACwivABAACsInwAAACrCB8AAMAqwgcAALCK8AEAAKwifAAAAKsIHwAAwCrCBwAAsIrwAQAArCJ8AAAAqwgfAADAKsIHAACwivABAACsInwAAACrCB8AAMAqwgcAALCK8AEAAKwifAAAAKsIHwAAwCrCBwAAsIrwAQAArCJ8AAAAq0IKHwsWLNDQoUPldDrldDqVnZ2tDz/8MNCek5Mjh8MRtEydOjXsgwYAANErJpTOGRkZmjt3rgYMGCBjjN566y2NHz9e27Zt0zXXXCNJeuSRR/TMM88EnhMfHx/eEQMAgKgWUvi48847gx4/99xzWrBggbZs2RIIH/Hx8UpLSwvfCAEAQKfS6jkfZ86c0fLly1VfX6/s7OzA+qVLl6p3794aMmSIioqKdPz48Ytux+fzyev1Bi0AAKDzCunIhyTt3LlT2dnZOnHihBISErRq1SpdffXVkqT77rtP/fr1U3p6unbs2KHZs2eroqJCK1euvOD2iouL9fTTT7e+AgAAEFUcxhgTyhNOnjypQ4cOyePx6I9//KN+//vfq7S0NBBAGtu4caPGjRunvXv3qn///s1uz+fzyefzBR57vV653W55PB45nc4QywEAAO3B6/XK5XK16PM75PBxvtzcXPXv318LFy5s0lZfX6+EhAStXbtWeXl5LdpeKIMHAAAdQyif322+z8fZs2eDjlw0tn37dklS37592/oyAACgkwhpzkdRUZEKCgqUmZmpuro6LVu2TCUlJVq3bp327dunZcuW6fbbb1dycrJ27NihmTNnasyYMRo6dGikxg8AAKJMSOHjyJEjevDBB1VdXS2Xy6WhQ4dq3bp1uvXWW1VZWan169frxRdfVH19vdxutyZOnKinnnoqUmMHAABRqM1zPsKNOR8AAEQfq3M+AAAAQkH4AAAAVhE+AACAVYQPAABgFeEDAABYRfgAAABWET4AAIBVhA8AAGAV4QMAAFhF+AAAAFYRPgAAgFWEDwAAYBXhAwAAWEX4AAAAVhE+AACAVYQPAABgFeEDAABYRfgAAABWET4AAIBVhA8AAGAV4QMAAFhF+AAAAFYRPgAAgFWEDwAAYBXhAwAAWEX4AAAAVhE+AACAVYQPAABgFeEDAABYRfgAAABWET4AABfn8UhVVc23VVX524EQhBQ+FixYoKFDh8rpdMrpdCo7O1sffvhhoP3EiRMqLCxUcnKyEhISNHHiRNXW1oZ90AAASzweKT9fGjtWqqwMbqus9K/PzyeAICQhhY+MjAzNnTtX5eXl2rp1q2655RaNHz9ef/nLXyRJM2fO1Pvvv68VK1aotLRUhw8f1j333BORgQMALKirk44ckfbvl3JyzgWQykr/4/37/e11de05SkQZhzHGtGUDSUlJeuGFF3TvvfeqT58+WrZsme69915J0tdff63BgwerrKxMI0eObNH2vF6vXC6XPB6PnE5nW4YGAAiHxkEjK0taskSaPPnc45ISye1u71GinYXy+d3qOR9nzpzR8uXLVV9fr+zsbJWXl+vUqVPKzc0N9Bk0aJAyMzNVVlZ2we34fD55vd6gBQDQgbjd/oCRleUPHKNHEzzQJiGHj507dyohIUFxcXGaOnWqVq1apauvvlo1NTWKjY1Vz549g/qnpqaqpqbmgtsrLi6Wy+UKLG7+EwNAx+N2+494NLZkCcEDrRJy+Bg4cKC2b9+uzz77TI8++qgeeughffXVV60eQFFRkTweT2CpPH9CEwCg/VVW+k+1NDZ5ctNJqEALhBw+YmNjdeWVV2rYsGEqLi7Wtddeq5deeklpaWk6efKkjh49GtS/trZWaWlpF9xeXFxc4OqZhgUA0IGcP+dj06Zzp2AaT0IFWqjN9/k4e/asfD6fhg0bpm7dumnDhg2BtoqKCh06dEjZ2dltfRkAQHuoqgoOHiUl0qhRwXNAcnIufB8QoBkxoXQuKipSQUGBMjMzVVdXp2XLlqmkpETr1q2Ty+XSww8/rFmzZikpKUlOp1PTp09XdnZ2i690AQB0MImJUkqK/+fGk0sbJqHm5PjbExPbaYCIRiGFjyNHjujBBx9UdXW1XC6Xhg4dqnXr1unWW2+VJM2bN09dunTRxIkT5fP5lJeXp/nz50dk4AAAC1wuae1a/308MjKC29xuqbTUHzxcrvYZH6JSm+/zEW7c5wMAgOhj5T4fAAAArUH4AAAAVhE+AACAVYQPAABgFeEDAABYRfgAAABWET4AAIBVhA8AAGAV4QMAAFhF+AAAAFYRPgAAgFWEDwAAYBXhAwAAWEX4AAAAVhE+AACAVYQPAABgFeEDAABYRfgAAABWET4AAIBVhA8AAGAV4QMAAFhF+AAAAFYRPgAAgFWEDwAAYBXhAwAAWEX4AAAAVhE+AACAVYQPAABgFeEDAABYRfgAAABWET4AAIBVIYWP4uJiDR8+XImJiUpJSdGECRNUUVER1CcnJ0cOhyNomTp1algHDQAAoldI4aO0tFSFhYXasmWLPvroI506dUq33Xab6uvrg/o98sgjqq6uDizPP/98WAcNAACiV0wondeuXRv0ePHixUpJSVF5ebnGjBkTWB8fH6+0tLTwjBAAAHQqbZrz4fF4JElJSUlB65cuXarevXtryJAhKioq0vHjxy+4DZ/PJ6/XG7QAAIDOK6QjH42dPXtWM2bM0OjRozVkyJDA+vvuu0/9+vVTenq6duzYodmzZ6uiokIrV65sdjvFxcV6+umnWzsMAAAQZRzGGNOaJz766KP68MMP9emnnyojI+OC/TZu3Khx48Zp79696t+/f5N2n88nn88XeOz1euV2u+XxeOR0OlszNAAAYJnX65XL5WrR53erjnxMmzZNa9as0SeffHLR4CFJI0aMkKQLho+4uDjFxcW1ZhgAACAKhRQ+jDGaPn26Vq1apZKSEl1xxRU/+Jzt27dLkvr27duqAQIAgM4lpPBRWFioZcuW6U9/+pMSExNVU1MjSXK5XOrRo4f27dunZcuW6fbbb1dycrJ27NihmTNnasyYMRo6dGhECgAAANElpDkfDoej2fWLFi3SlClTVFlZqQceeEC7du1SfX293G637r77bj311FMtnr8RyjkjAADQMURszscP5RS3263S0tJQNgkAAC4xfLcLAACwivABAACsInwAAACrCB8AAMAqwgcAALCK8AEAAKwifAAAAKsIHwAAwCrCBwAAsIrwAQAArCJ8AAAAqwgfAADAKsIHAACwivABAACsInwAAACrCB8AAMAqwgcAALCK8AEAAKwifAAAAKsIHwAAwCrCBwAAsIrwAQAArCJ8AAAAqwgfAADAKsIHAACwivABAACsInwAAACrCB8AAMAqwgcAALCK8AEAAKzq/OHD45Gqqppvq6rytwMAAGtCCh/FxcUaPny4EhMTlZKSogkTJqiioiKoz4kTJ1RYWKjk5GQlJCRo4sSJqq2tDeugW8zjkfLzpbFjpcrK4LbKSv/6/HwCCAAAFoUUPkpLS1VYWKgtW7boo48+0qlTp3Tbbbepvr4+0GfmzJl6//33tWLFCpWWlurw4cO65557wj7wFqmrk44ckfbvl3JyzgWQykr/4/37/e11de0zPgAALkEOY4xp7ZO/+eYbpaSkqLS0VGPGjJHH41GfPn20bNky3XvvvZKkr7/+WoMHD1ZZWZlGjhz5g9v0er1yuVzyeDxyOp2tHdo5jYNGVpa0ZIk0efK5xyUlktvd9tcBAOASFsrnd5vmfHj+/3RFUlKSJKm8vFynTp1Sbm5uoM+gQYOUmZmpsrKyZrfh8/nk9XqDlrByu/0BIyvLHzhGjyZ4AADQjlodPs6ePasZM2Zo9OjRGjJkiCSppqZGsbGx6tmzZ1Df1NRU1dTUNLud4uJiuVyuwOKORBhwu/1HPBpbsoTgAQBAO2h1+CgsLNSuXbu0fPnyNg2gqKhIHo8nsFSePzE0HCor/adaGps8uekkVAAAEHGtCh/Tpk3TmjVr9PHHHysjIyOwPi0tTSdPntTRo0eD+tfW1iotLa3ZbcXFxcnpdAYtYXX+nI9Nm86dgmk8CRUAAFgRUvgwxmjatGlatWqVNm7cqCuuuCKofdiwYerWrZs2bNgQWFdRUaFDhw4pOzs7PCMORVVVcPAoKZFGjQqeA5KTc+H7gAAAgLCLCaVzYWGhli1bpj/96U9KTEwMzONwuVzq0aOHXC6XHn74Yc2aNUtJSUlyOp2aPn26srOzW3SlS9glJkopKf6fG08ubZiEmpPjb09MtD82AAAuUSFdautwOJpdv2jRIk2ZMkWS/yZjjz32mN555x35fD7l5eVp/vz5Fzztcr6wX2rr8fjv49Ho9FBAVZU/eLhcbX8dAAAuYaF8frfpPh+REPbwAQAAIs7afT4AAABCRfgAAABWET4AAIBVhA8AAGAV4QMAAFhF+AAAAFYRPgAAgFWEDwAAYBXhAwAAWEX4AAAAVhE+AACAVYQPAABgFeEDAABYRfgAAABWET4AAIBVhA8AAGAV4QMAAFhF+AAAAFYRPgAAgFWEDwAAYBXhAwAAWEX4AAAAVhE+AACAVYQPAABgFeEDAABYRfgAAABWET4AAIBVhA8AAGAV4QMAAFhF+AAAAFYRPgAAgFUhh49PPvlEd955p9LT0+VwOLR69eqg9ilTpsjhcAQt+fn54RovAACIciGHj/r6el177bV67bXXLtgnPz9f1dXVgeWdd95p0yABAEDnERPqEwoKClRQUHDRPnFxcUpLS2v1oAAAQOcVkTkfJSUlSklJ0cCBA/Xoo4/q22+/vWBfn88nr9cbtAAAgM4r7OEjPz9fb7/9tjZs2KDf/OY3Ki0tVUFBgc6cOdNs/+LiYrlcrsDidrvDPSQAANCBOIwxptVPdji0atUqTZgw4YJ99u/fr/79+2v9+vUaN25ck3afzyefzxd47PV65Xa75fF45HQ6Wzs0AABgkdfrlcvlatHnd8Qvtc3KylLv3r21d+/eZtvj4uLkdDqDFgAA0HlFPHxUVVXp22+/Vd++fSP9UgAAIAqEfLXLsWPHgo5iHDhwQNu3b1dSUpKSkpL09NNPa+LEiUpLS9O+ffv05JNP6sorr1ReXl5YBw4AAKJTyOFj69atuvnmmwOPZ82aJUl66KGHtGDBAu3YsUNvvfWWjh49qvT0dN1222169tlnFRcXF75RAwCAqNWmCaeREMqEFQAA0DF0qAmnAAAAjRE+AACAVYQPAABgFeEDAABYRfgAAABWET4AAIBVhA8AAGAV4QMAAFhF+AAAAFYRPgAAgFWEDwAAYBXhAwAAWEX4AAAAVhE+AACAVYQPAABgFeEDAABYRfgAAABWET4AAIBVhA8AAGAV4QMAAFhF+AAAAFYRPgAAgFWEDwAAYBXhAwAAWEX4AAAAVhE+AACAVYQPAABgFeEDAABYRfgAAABWET4AAIBVhA8AkeXxSFVVzbdVVfnbAVxSQg4fn3zyie68806lp6fL4XBo9erVQe3GGP3bv/2b+vbtqx49eig3N1d79uwJ13gBRBOPR8rPl8aOlSorg9sqK/3r8/MJIMAlJuTwUV9fr2uvvVavvfZas+3PP/+8Xn75Zb3++uv67LPPdNlllykvL08nTpxo82ABRJm6OunIEWn/fikn51wAqaz0P96/399eV9eeowRgmcMYY1r9ZIdDq1at0oQJEyT5j3qkp6frscce0+OPPy5J8ng8Sk1N1eLFi/XTn/70B7fp9Xrlcrnk8XjkdDpbOzQAHUXjoJGVJS1ZIk2efO5xSYnkdrf3KAG0USif32Gd83HgwAHV1NQoNzc3sM7lcmnEiBEqKytr9jk+n09erzdoAdCJuN3+gJGV5Q8co0cTPIBLXFjDR01NjSQpNTU1aH1qamqg7XzFxcVyuVyBxc0vIqDzcbv9RzwaW7KE4AFcotr9apeioiJ5PJ7AUnn+pDQA0a+y0n+qpbHJk5tOQgVwSQhr+EhLS5Mk1dbWBq2vra0NtJ0vLi5OTqczaAHQiZw/52PTpnOnYBpPQgVwyQhr+LjiiiuUlpamDRs2BNZ5vV599tlnys7ODudLAYgGVVXBwaOkRBo1KngOSE7Ohe8DAqBTign1CceOHdPevXsDjw8cOKDt27crKSlJmZmZmjFjhv7jP/5DAwYM0BVXXKFf//rXSk9PD1wRA+ASkpgopaT4f248ubRhEmpOjr89MbGdBgigPYR8qW1JSYluvvnmJusfeughLV68WMYYzZkzR//93/+to0eP6qabbtL8+fN11VVXtWj7XGoLdDIej/8+HhkZTduqqvzBw+WyPy4AYRXK53eb7vMRCYQPAACiT7vd5wMAAOCHED4AAIBVhA8AAGAV4QMAAFhF+AAAAFYRPgAAgFWEDwAAYBXhAwAAWEX4AAAAVoX83S6R1nDDVa/X284jAQAALdXwud2SG6d3uPBRV1cnSXI3fAEVAACIGnV1dXL9wPc1dbjvdjl79qwOHz6sxMREORyOsG7b6/XK7XarsrKyU35vTGevT+r8NVJf9OvsNVJf9ItUjcYY1dXVKT09XV26XHxWR4c78tGlSxdlNPftl2HkdDo77X8qqfPXJ3X+Gqkv+nX2Gqkv+kWixh864tGACacAAMAqwgcAALDqkgofcXFxmjNnjuLi4tp7KBHR2euTOn+N1Bf9OnuN1Bf9OkKNHW7CKQAA6NwuqSMfAACg/RE+AACAVYQPAABgFeEDAABYFVXho7i4WMOHD1diYqJSUlI0YcIEVVRUBPU5ceKECgsLlZycrISEBE2cOFG1tbVBfQ4dOqQ77rhD8fHxSklJ0RNPPKHTp08H9SkpKdH111+vuLg4XXnllVq8eHGky5Nkr8aSkhI5HI4mS01NTVTU98tf/lLDhg1TXFycrrvuumZfa8eOHfrRj36k7t27y+126/nnn49UWQG26jt48GCz+2/Lli2RLE9SeGr88ssvNWnSJLndbvXo0UODBw/WSy+91OS12uN9aKu+9noPhqvGb7/9Vvn5+UpPT1dcXJzcbremTZvW5Hu5onUftqS+aP892rjWjIwMORwOHT16NKgtYvvPRJG8vDyzaNEis2vXLrN9+3Zz++23m8zMTHPs2LFAn6lTpxq32202bNhgtm7dakaOHGlGjRoVaD99+rQZMmSIyc3NNdu2bTMffPCB6d27tykqKgr02b9/v4mPjzezZs0yX331lXnllVdM165dzdq1aztNjR9//LGRZCoqKkx1dXVgOXPmTIevzxhjpk+fbl599VUzefJkc+211zZ5HY/HY1JTU839999vdu3aZd555x3To0cPs3Dhwk5R34EDB4wks379+qD9d/LkyYjWZ0x4anzjjTfML3/5S1NSUmL27dtnlixZYnr06GFeeeWVQJ/2eh/aqq+93oPhqvFvf/ubmT9/vvn888/NwYMHzfr1683AgQPNpEmTAn2ieR+2pL5o/z3aYPz48aagoMBIMt99911gfST3X1SFj/MdOXLESDKlpaXGGGOOHj1qunXrZlasWBHos3v3biPJlJWVGWOM+eCDD0yXLl1MTU1NoM+CBQuM0+k0Pp/PGGPMk08+aa655pqg1/rJT35i8vLyIl1SE5GqseFN0/g/WntoTX2NzZkzp9kP5/nz55tevXoF6jXGmNmzZ5uBAweGv4iLiFR9DeFj27ZtkRp6i7W1xga/+MUvzM033xx43FHeh5Gqr6O8B40JX40vvfSSycjICDzubPvw/Po6yj5sS33z5883Y8eONRs2bGhSSyT3X1Sddjmfx+ORJCUlJUmSysvLderUKeXm5gb6DBo0SJmZmSorK5MklZWV6e/+7u+Umpoa6JOXlyev16u//OUvgT6Nt9HQp2EbNkWqxgbXXXed+vbtq1tvvVWbNm2KdDlNtKa+ligrK9OYMWMUGxsbWJeXl6eKigp99913YRr9D4tUfQ3uuusupaSk6KabbtJ7770XnkGHKFw1ejyewDakjvM+jFR9Ddr7PSiFp8bDhw9r5cqVGjt2bGBdZ9qHzdXXoL33YWvr++qrr/TMM8/o7bffbvaL4CK5/6I2fJw9e1YzZszQ6NGjNWTIEElSTU2NYmNj1bNnz6C+qampgXNwNTU1QR/KDe0NbRfr4/V69f3330einGZFssa+ffvq9ddf17vvvqt3331XbrdbOTk5+uKLLyJc1Tmtra8lWvJvEGmRrC8hIUH/+Z//qRUrVujPf/6zbrrpJk2YMMF6AAlXjZs3b9Yf/vAH/fznPw+s6wjvw0jW1xHeg1Lba5w0aZLi4+N1+eWXy+l06ve//32grTPsw4vV1xH2YWvr8/l8mjRpkl544QVlZmY2u+1I7r8O9622LVVYWKhdu3bp008/be+hREwkaxw4cKAGDhwYeDxq1Cjt27dP8+bN05IlS8L+es3p7PswkvX17t1bs2bNCjwePny4Dh8+rBdeeEF33XVX2F/vQsJR465duzR+/HjNmTNHt912WxhH13aRrK8jvAelttc4b948zZkzR3/9619VVFSkWbNmaf78+WEeZetFsr6OsA9bW19RUZEGDx6sBx54IEIju7ioPPIxbdo0rVmzRh9//LEyMjIC69PS0nTy5Mkms3Vra2uVlpYW6HP+jN+Gxz/Ux+l0qkePHuEup1mRrrE5N954o/bu3RumCi6uLfW1RGv/DcIl0vU1Z8SIEdb2nxSeGr/66iuNGzdOP//5z/XUU08FtbX3+zDS9TXH5ntQCk+NaWlpGjRokO666y4tXLhQCxYsUHV1daAt2vfhxeprTrT8Ht24caNWrFihmJgYxcTEaNy4cZL8f9jMmTMnsJ2I7b82zxqx6OzZs6awsNCkp6ebv/71r03aGybZ/PGPfwys+/rrr5udjFlbWxvos3DhQuN0Os2JEyeMMf5JNkOGDAna9qRJk6xMkrJVY3Nyc3PN3XffHcZqmgpHfY390ITTxld/FBUVRXzCqa36mvPP//zP5u///u9bPfaWCleNu3btMikpKeaJJ55o9nXa631oq77m2HgPGhP+/6cNSktLjSRz4MABY0z078PznV9fc6Ll9+jevXvNzp07A8ubb75pJJnNmzcHPjsiuf+iKnw8+uijxuVymZKSkqDLmo4fPx7oM3XqVJOZmWk2btxotm7darKzs012dnagveEy1Ntuu81s377drF271vTp06fZS22feOIJs3v3bvPaa69Zu9TWVo3z5s0zq1evNnv27DE7d+40v/rVr0yXLl3M+vXrO3x9xhizZ88es23bNvMv//Iv5qqrrjLbtm0z27ZtC1zdcvToUZOammomT55sdu3aZZYvX27i4+MjfqmtrfoWL15sli1bZnbv3m12795tnnvuOdOlSxfz5ptvRrS+cNW4c+dO06dPH/PAAw8EbePIkSOBPu31PrRVX3u9B8NV45///Gfz5ptvmp07d5oDBw6YNWvWmMGDB5vRo0cH+kTzPmxJfdH+e7Sx5q7cieT+i6rwIanZZdGiRYE+33//vfnFL35hevXqZeLj483dd99tqqurg7Zz8OBBU1BQYHr06GF69+5tHnvsMXPq1KmgPh9//LG57rrrTGxsrMnKygp6jUiyVeNvfvMb079/f9O9e3eTlJRkcnJyzMaNG6OmvrFjxza7ncZ/kXz55ZfmpptuMnFxcebyyy83c+fO7TT1LV682AwePNjEx8cbp9NpbrzxxqDL6jp6jXPmzGl2G/369Qt6rfZ4H9qqr73eg+GqcePGjSY7O9u4XC7TvXt3M2DAADN79uwml51G6z5sSX3R/nu0sQtdNhyp/ef4/0IAAACsiMoJpwAAIHoRPgAAgFWEDwAAYBXhAwAAWEX4AAAAVhE+AACAVYQPAABgFeEDAABYRfgAAABWET4AAIBVhA8AAGAV4QMAAFj1f3VFwMLxbWYKAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "year = [2000, 2010, 2020, 2030, 2040]\n",
    "pop = [20, 40, 10, 30, 50]\n",
    "\n",
    "# Make a line plot: year on the x-axis, pop on the y-axis\n",
    "plt.scatter(year, pop, color=\"red\", marker=\"x\", label=\"Population\")\n",
    "plt.legend()\n",
    "\n",
    "# Display the plot with plt.show()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "af11eda4",
   "metadata": {},
   "source": [
    "## Histogram\n",
    "\n",
    "`plt.hist(list,bins)`\n",
    "\n",
    "bins = 10 by default\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "9a583958",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-09-06T12:27:33.331024470Z",
     "start_time": "2023-09-06T12:27:33.237055878Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "x = [\n",
    "    43.828,\n",
    "    76.423,\n",
    "    72.301,\n",
    "    42.731,\n",
    "    75.32,\n",
    "    81.235,\n",
    "    79.829,\n",
    "    75.635,\n",
    "    64.062,\n",
    "    79.441,\n",
    "    56.728,\n",
    "    65.554,\n",
    "    74.852,\n",
    "    50.728,\n",
    "    72.39,\n",
    "    73.005,\n",
    "    52.295,\n",
    "    49.58,\n",
    "    59.723,\n",
    "    50.43,\n",
    "    80.653,\n",
    "    50.651,\n",
    "    78.553,\n",
    "    72.961,\n",
    "    72.889,\n",
    "    65.152,\n",
    "    46.462,\n",
    "]\n",
    "plt.hist(x, bins=6, color=\"red\", edgecolor=\"black\", linewidth=2)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c814ed21",
   "metadata": {},
   "source": [
    "## Box Plot\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "696a9e78",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "x = [\n",
    "    43.828,\n",
    "    76.423,\n",
    "    72.301,\n",
    "    42.731,\n",
    "    75.32,\n",
    "    81.235,\n",
    "    79.829,\n",
    "    75.635,\n",
    "    64.062,\n",
    "    79.441,\n",
    "    56.728,\n",
    "    65.554,\n",
    "    74.852,\n",
    "    50.728,\n",
    "    72.39,\n",
    "    73.005,\n",
    "    52.295,\n",
    "    49.58,\n",
    "    59.723,\n",
    "    50.43,\n",
    "    80.653,\n",
    "    50.651,\n",
    "    78.553,\n",
    "    72.961,\n",
    "    72.889,\n",
    "    65.152,\n",
    "    46.462,\n",
    "]\n",
    "\n",
    "plt.boxplot(x)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4a9de81b",
   "metadata": {},
   "source": [
    "## Display image from array\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "884f44ab",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 1. 1. 1. 1. 0. 0. 0. 1. 0. 0. 0. 0. 1. 0.\n",
      " 0. 1. 0. 0. 0. 0. 1. 0. 0. 1. 0. 0. 0. 0. 1. 0. 0. 1. 0. 0. 0. 0. 1. 0.\n",
      " 0. 0. 1. 1. 1. 1. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      " 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      " 0. 0. 0. 0. 0. 0. 0. 0.]\n",
      "[[0. 0. 0. 0. 0. 0. 0. 0.]\n",
      " [0. 0. 1. 1. 1. 1. 0. 0.]\n",
      " [0. 1. 0. 0. 0. 0. 1. 0.]\n",
      " [0. 1. 0. 0. 0. 0. 1. 0.]\n",
      " [0. 1. 0. 0. 0. 0. 1. 0.]\n",
      " [0. 1. 0. 0. 0. 0. 1. 0.]\n",
      " [0. 0. 1. 1. 1. 1. 0. 0.]\n",
      " [0. 0. 0. 0. 0. 0. 0. 0.]\n",
      " [0. 0. 0. 0. 0. 0. 0. 0.]\n",
      " [0. 0. 0. 0. 0. 0. 0. 0.]\n",
      " [0. 0. 0. 0. 0. 0. 0. 0.]\n",
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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "samples = pd.read_csv(\"datasets/lcd-digits.csv\").values\n",
    "\n",
    "# Select the 0th row: digit\n",
    "digit = samples[0, :]\n",
    "\n",
    "# Print digit\n",
    "print(digit)\n",
    "\n",
    "# Reshape digit to a 13x8 array: bitmap\n",
    "bitmap = digit.reshape((13, 8))\n",
    "\n",
    "# Print bitmap\n",
    "print(bitmap)\n",
    "\n",
    "# Use plt.imshow to display bitmap\n",
    "plt.imshow(bitmap, cmap=\"gray\", interpolation=\"nearest\")\n",
    "plt.colorbar()\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "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": "3.11.0"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}