d1_data_visualization.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# DATA VISUALIZATION"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "sample_data = pd.read_csv(\n",
    "    \"https://raw.githubusercontent.com/davidbrandon16/binusMachineLearning/master/sample.csv\",\n",
    "    sep=\";\",\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "data_1 = sample_data.drop_duplicates().dropna().reset_index(\n",
    "    drop=True\n",
    ").rename(\n",
    "    columns={\n",
    "        \"Industry_aggregation_NZSIOC\": \"level\",\n",
    "        \"Industry_code_NZSIOC\": \"code\",\n",
    "        \"Industry_name_NZSIOC\": \"name\",\n",
    "    }\n",
    ").drop(columns=\"Year\")\n",
    "data_1.loc[(data_1.Units == \"Dollars (millions)\"), \"Value\"] = data_1.Value * 1000\n",
    "data_1 = data_1[[\"level\", \"name\", \"Value\"]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "data_2 = sample_data.drop_duplicates().fillna(\n",
    "    0,\n",
    ").reset_index(\n",
    "    drop=True,\n",
    ").rename(\n",
    "    columns={\n",
    "        \"Industry_aggregation_NZSIOC\": \"level\",\n",
    "        \"Industry_code_NZSIOC\": \"code\",\n",
    "        \"Industry_name_NZSIOC\": \"name\",\n",
    "    }\n",
    ").drop(columns=\"Year\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>level</th>\n",
       "      <th>name</th>\n",
       "      <th>Value</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Level 3</td>\n",
       "      <td>Horticulture and Fruit Growing</td>\n",
       "      <td>4432000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Level 3</td>\n",
       "      <td>Horticulture and Fruit Growing</td>\n",
       "      <td>4119000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Level 3</td>\n",
       "      <td>Horticulture and Fruit Growing</td>\n",
       "      <td>211000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Level 3</td>\n",
       "      <td>Horticulture and Fruit Growing</td>\n",
       "      <td>3579000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Level 3</td>\n",
       "      <td>Horticulture and Fruit Growing</td>\n",
       "      <td>180000.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     level                            name      Value\n",
       "0  Level 3  Horticulture and Fruit Growing  4432000.0\n",
       "1  Level 3  Horticulture and Fruit Growing  4119000.0\n",
       "2  Level 3  Horticulture and Fruit Growing   211000.0\n",
       "3  Level 3  Horticulture and Fruit Growing  3579000.0\n",
       "4  Level 3  Horticulture and Fruit Growing   180000.0"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_1.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "data_level_3 = data_1[data_1.level==\"Level 3\"]\n",
    "data_level_4 = data_1[data_1.level==\"Level 4\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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IAAYAADARAQwAAGAiAhgAAMBEBDAAAICJCGAAAAATEcAAAAAmIoABAABMRAADAACYiAAGAAAwEQEMAABgIgIYAADARAQwAACAiQhgAAAAExHAAAAAJjJXAKuqh1fVR6rqY1V13EYXCgAAYCtaNYBV1UFJ/jrJjye5e5InVtXdN7pgAAAAW808PWD3S/Kx7v5Ed38zyauTPHpjiwUAALD1zBPAviPJFTOvPzWOAwAAYA22rdeMqurYJMeOL6+qqo+s17zZbxye5PObXYjrq/qjzS4BG8z+cR3YP7Y8+8d1YP/Y8uwf19F+vI/ccamR8wSwTyf5zpnXtx/H7aW7T0xy4j4VjeuFqtrV3Ts3uxywP7J/wPLsH7A8+8eBZ55LED+c5C5VdaequmGSJyR588YWCwAAYOtZtQesu79VVb+e5O1JDkry0u6+aMNLBgAAsMXMdQ9Yd/9jkn/c4LKw/3OJKSzP/gHLs3/A8uwfB5jq7s0uAwAAwAFhnnvAAAAAWAcHdACrqqsWvT6mqp6/xnkcVVU/NPP6yVX1i/tYntOqauc4/N/3ZR5TGL/zqcuM/1JVnTv+vWsf5v2B8d8dVfWzK0x3l6o6tao+XlVnVdV7q+pBa13eKmW5XVWdsp7znEJV/XZVXVRV54+/ww+M4y+vqsM3qUwnVdVlY3kurar/7zrMa3tVnVlV51TVDy967+CqOqGq/qWqzq6qM6rqx1eZ39Or6iYzr//7ovevuvanNs5yv1NV3bSqXjhu82eP2/2v7cP8/7GqbrGG6Y+vqk/P7NcnrHWZG1GuA0FVXT2u84uq6ryq+o2qWrHeXo/jVlV9z/h7LOxHr62q264w/V7H66o6sqoeMfN6TXXretQlcy7nd6vqoRsx7/3JzHZ0YVW9bvZ4t8b5nFRVjx2Hn76v81lh3peN2/lHq+rlVXX79Zr/elppe66qnxzr3kuq6oKq+slFn7vdzOt1rZOXqquuyznpMsvY65x3jZ/dUVUXzjHN12b2/XNreADgulrv9bIvDugAdl1V1bYkRyW5ZmPs7r/p7pevw+zXHMDG8my207v7yPHvWhXbamXs7oV1uSPJkgGsqg5J8tYkJ3b3nbv7vkmekuS71rq8Vcryme5+7L5+fjNU1f2TPDLJfbr7nkkemr3/I/XN9KzuPjLJkUl+qarutI/z+dEkF3T3vbv79EXv/V6SI5Lco7vvk+Qnk9xslfk9PcnsicT+2vjx4iRfSHKX8bs9PMmtFk80xz72iO7+4hqX/byZ/fq4eT+0lv1vH8u11X1tXOffm+THkvx4khUbL5Y7bs37W8wcX1/Y3Qvb2guSbF/hYzuy9/H6yCSPWHrSua1Ylyxnjdvcc7p7Q8LdfmZhO7pHkm8mefI6zHPxcfMaVXXQPs7zWd19ryR3TXJOkvesx8n3VOdGVXWvJH+a5NHd/R+TPCrJn1bVPcdJjklyu2U+vtZlzfsMh/U6J11wVGbOeTfIx2f2/SO7+5vzfGiN+/56r5c1E8CWMabw94wtGe+uqjuM40+qqr+pqjOTvDbDgewZY0r/4bG1+JnjtN9dVe8aW3TOrqo716Leo6p6flUds2jZJyS58TjPVy5uNaiqZ1bV8ePwaVX1F1W1K8nTaugdeH1VfXj8e8Ay3+30sUxnL7RmjGU7rapOqaGX4pVVVeN7Dx/HnZ3kp9a4LmfX2R/PrqPx/Qurasc4vNCCc0KSHx7XwTMWzfLnkpzR3df8dwjdfWF3nzTO4/iqekVVvT/JK6rqkKp62dgadU5VPXic7q0LB8Zx/HPG4d+tql+bXe9jy9UbquptNbQK//FM+Z9UQ4vdh6rqb2uNvajr7Igkn+/ubyRJd3++uz8z8/5Txt/8gqq6W5JU1aFV9dKx/OdU1aPH8QdV1Z+M29H5VfWfxvFHVdX7xvX3kfG3Xcux5JDx36+O87tvVf1TDT06b6+qI8bxdx7X91nj9nq3qjoyyR8nefS4bdx4YaY1tMb+WpKnzHz/z3X3a8f3X1hVu2roTXjuOO6pGSrE99bQi7rXvre44FX1rJn18dylvtxSyxnHX15Vz11i/d+6qt4xTv/iJLXEPO+c5H5Jfqe7vz1+t93d/Ufj+0eN6+jNSS4ex71pXHcXVdWxi8px+Lh9XzJusxeNZbjx4mUvp6qeM66LC6vqxJljxeJj0knjOvlgVX1iLOtLx2WftJZyVdX3156e3T+pVVpTt5LuvjLJsUl+vQbLHccXH7feXFXvSfLuGnoVZlvkX7mwv8/42QzH17fMLPu07r5wuWVm7+P1s5P8bpLHj68fPzvzmqOOWk5V/UTt6f1+V429cnXtY/4x4/b/znG7+vWq+m/j5z5YVbcaPzfbo7Pc/rl9nM9FVfXiqvpkbdKVBOvk9CTfnSTjOrlw/Hv6OG7Z842ZcXsdN8dxV1XVn1XVeUl+u6reNDP9j1XVG+ctYA+el+R/Z2h0SFU9rIYrGs6uoRfvpuP45eqPvY5Di8p/v3Fe51TVB6rqruP4ler5X66xnk+y3Db7zCT/o7svG7/HZUn+MMmzxu1sZ5JX1t5111rq5L3253nW5bhvPLOG+vNDM+N3VNUFq6zDp1bVxTUcc19dw3na4nPe5c6Vb1tVb6zh/Pe8WtRrVlXfNX6375/ze6z0m80e444av8s/1FDfnFBVPzeuywtqqEuvWS/j8GlV9UfjNB+t8cqaqrpJDb3/F4/f5cwar1JbF919wP4luTrJuTN//3+S54/vvSXJL43Dv5LkTePwSUlOTXLQ+Pr4JM+cmec1r5OcmeQx4/AhGVqLjkpy6sz0z09yzDh8WpKd4/BVM9PsSHLhzOtnJjl+5jMvmHnv5CQPHIfvkOSSJb73TZIcMg7fJcmucfioJF/K8J9t3yDJGUkeOJb9inHayhA8T11ivgufX1ifvz3nOrswyY7Z7714PS1azp8nedoKv+vxSc5KcuPx9W9k+O8TkuRu4+98SJLjkvzXJIdl+P/u3j5O894MLXDXrPcMLVefGKc9JMknM/wH5bdLcnmGnoiDM1Ruz9/Ebfqm47r/aIZW6x+Zee/yDOEkSf5LkhePw/8jyc+Pw7cYP3tohpO93xnH3yjJriR3Gn+br2focTwoyTuTPHaVcp2U5LKxbFdlqKQyrrMPJNk+vn78zG/17gy9PUnyA0neM/NbXGsdJ7lnknNWKMOtxn8PyrDf3HNmvRw+M91Viz63sE0+LMOTqirD/nFqkgetcTlLrf+/SvKccfjoJD1bnnH8o5K8cYXvdlSGQHunJcpx4wz72K1nv2+G7ftbSY4cx792YTtYYn/6dPbs1//P7PzH4Vck+Ylx+LTsfUw6Kcmrx/X26CRfTvJ94zo8a2b5q5Zr/B73H4dPyMxxcSv+Ld4Wx3FfTHLbLH8c35G9j1ufmtkWfiR76rLDMuyT2xbNf9nj6wrLPCp712vHZGYfnX2d+eqoo7J0XXLL5JqHh/1qkj+b2UZnj/nHJPlYht7v7eO8njy+97wkT5/ZNh+7yv75/CS/NQ4/PEvsn/v7X/Ycw7Yl+Yck/znJfZNckOFYf9MkFyW5d1Y+31i8vmaPm53kZ8bhSnJp9hzXT854fFihjNfMe2bcXyR5dobjwvuSHDqOf3aS52Tl+uO0zByHFs335hm3+wxXibx+ZrtZqp4/IsN5w/YkN0zy/ixdB52d5F6Lxt0rydkzZdo5895y29xydfIxmdmfl/udF407PnvOSc/NWEeM6/B3VlmHn0lyo4VyLJ7f+Hq5c+XXZM9+dtC4TndkOIYv9HDea4ny7kjytezZ9/96jt9s9hh3VIZj5BEZzls+neS543tPS/IXS6yX07LnWPKIJO+a2fZfNA7fI0O9tHNxmff1b3+4ZG0zfa2HS6KSDEk6QwtFktw/e3p6XpGh1X3B67r76pVmXFU3S/Id3f3GJOnur4/j16fke3vNzPBDk9x9Zjk3r6qbdvfstcEHJ3l+Db0JVyf5npn3PtTdnxrLem6GneGqJJd197+M4/8+w8n5Uk7v7kcuMX7Vdbavxpa1uyT5aHcv/GZv7u6vjcMPTPI/k6S7L62qT2b4zqcneWqGk5C3JvmxGnpR7tTdHxlbe2a9u7u/NC7z4iR3zFAx/FN3/9s4/nXZe31Oqruvqqr7JvnhJA9O8pqqOq7H3sEkbxj/PSt7tu+HJXlU7emVPCTDidHDktxzbLlLhgPoXTJcwvKh7v5EklTVqzKs49XuO3lWd58ytly+e2wR+3KGA9s7x232oCSfHaf5oSSvm9mWb7SmlXFtP1NDT9C2DAfnuyc5fw2ff9j4d874+qYZ1sf71rCcpdb/gxaGu/utVfWF1QpSVb+d5HFJbtPdC5e0fKjHltfRU6vqMePwd45l/ddFs7qsu8+dKdOOZRb5vO7+00XjHlxVv5nhpPxWGU7gFnpNXrNo2rd0d48trp/r7oWW14vGZZ67aPprlauG+8Nu1t1njONPznC57YFqpeP4rHcuHJ+6+5+q6gVVtT3JT2c4ifnWBixzJfPUUcnSdcntMxzTjshwIjy7vc8e85Pkvd39lSRfqaovZc+2eUGGxpqlLLV/PjDJY5Kku982z/65H7rxWJ8nQ733kgwh7I3dvXAlwhsy1BtvXnoWq7o6yeuToQerql6R5Oer6mUZzqf25X6bhY3kBzMcR98/bjc3zNBAfNcsUX/MfH7xcWjBYUn+rqrukiE4Hjzz3nL1/GndvXsc/5qsXz2/ljo5mdmf98FrMwSsE8Z/H5+V1+H5GXrs3pTkTdea22C5c+WHZPzNx3O/L1XVLTOE2H9I8lPdffEy8/z47Ln5aKXfbPE6+XB3fzZJqurjSd4xjr8gw3nRUmZ/hx3j8AOT/OX4HS6sqrWcL6zqQA9g++qr1+Gz38rel34estyEa/jMbHlukOQHFwLfMp6R5HMZWmZukKE3Y8E3ZoavzvptI7Nl3Jd1MOuiDCetSZLufszYLTx7gjjPb/ThDIH7Exl6cQ7PcAnbWctMv1HrZl2NB7vTkpw2nvD+UobWxWTPd5gtfyX56e7+yOx8ajgaP6W7375o/FEZDoB7LXYN5buqqk7LcHD7X0ku6u77L1rGzZN8cYmD8Eo+luQOVXXz7v7yovndKUNr1vd39xdquPRtrdtdJfnD7n7RshOsvpyl1v88Lk5yr6q6QXd/u7v/IMkf1N43XV+zzY+/0UMz9Bb9+7i+l/q+i7fpuS5BrOE+oRdkaA28ooZLlGbnv3j/W1jOtxct89tZej3sU7m2uqr6rgzr48oM94Itdxyftfi3eHmSn0/yhCS/vMT0F2XoKVvKSnXHvOapo5bzP5P8eXe/edzGj595b7ltLtl7u1tum5v9zH57fN9HX1t8LF2hMXhf6+evL2pkfVmG0Pv1DA2wawn6C+6d4UqIynCS/cTZN6vq+7JE/TFjufOA38sQ0B8zNrSeNvPedannL87Qs3jezLj7ZtinlrOWOvkHct3OP1+ToVHzDRly8r+ssg6PznCu9RMZLiv9vuuw7AVfytCb+MCMl8vPaaXf7Hq577sHbHkfyFBBJcM9R4tv9l/wlSxxk//Y8vapGq+3r6objb0rn8zQ+nejsUX3R5eZ7/+pqoWE/7kkt6nhXpEbZeVW33dkeCBFxuUudQJ7WJLP9nAvyS9kaPFYyaUZWqDvPL5+4koTz+HyJPcZy3efDJe1Lbbkeh2dnOQBVfWomXErPY3p9Ay/YarqezK0JH2khxs7r8jQk3DGON0zc+0ejZV8OMmPVNUta7gB9KfX8Nl1V1V3HVuIFhyZYZtbydszXIe+cA/PvWfG/+eF7bCGJ6MdOr53v6q6Uw33fj0+yT+P07y8qu63Shm3Zbik8ONJPpJkew0PD0kNTzH83jFAXVZVjxvHVw03OC+ru/89Q8vuX9Z443YN9288LsPlC1/N0Ap324z3FYwWb2uz+97i9fQrtefeg++oqtssmmal5SznfRkfYFDDExtvucR3+1iGS0B/v8Yb3McQtNxZ1GFJvjCGr7tlaEFeTwsnZZ8f18eGP6ymhwd0fGU8CUn2HJ8PCGOv1d9kuPSps/bj+IKTMjxAIcu0QJ+c5Ieq6uiZZT+oqu6xwjIX70MrHb/nqaOWc1iGS4qSoXm3aQwAAASMSURBVGFpCu9P8jPJcB9Sltg/r6dOT/KTNdzncmiGXr7TM//5xkq/cXq49/gzGS5ze9nC+DnriKrhPrMjkrwtyQcz1PkL964dOtblS9Yfc3z32e3omDmmPzNDPX/rsW543DLT/WmS36o997TvyPBQpz8b319xnc1Yrk6+Trr74xkCxv+bPb2DS67DsW7/zu5+b4bLFQ/LcNXH4u+w3LnyuzP0sqaG+8kPG8d/M8O29ou1wpOul7DW32w9zO77d89w6fy6EcCW95Qkvzx2Of5CFt3EOeMtSR5T4w2Ji977hQyXAZ2fYSP9D919RYZu4AvHf8/J0k5Mcn5VvbK7/0+Gm5o/lKGn5tIVyv3UJDtruCHy4iz9tKMXZHgK3XkZ7olasUVlbKk8Nslba3gIx5UrTT+H1ye5VQ2XH/16huubFzs/ydU13Ly510M4xstMHpnkyTXcZHlGhoP87y+zvBckuUENvUGvyXDP3UJrx+lJrhzneXqGS1yWC9vX0t2fznC99ocy7KyXZ2jh2Sw3zdBNf/G43d09e7cSL+X3MnTnnz/+Jr83jn9xhhaqs2u4KftF2dMy9OEM90ZckuEyoIUbrO+ZodJdyp/UcBnM+RkuBXjDGIIfm+SPxu3x3Ox5wtLPJXnSOP6iDPcPreZ3kuxOcvFY5lOTfLm7z8uwr12a4QTz/TOfOTHJ22q8mTwz+97sjLv7HeNnzxi3pVOyqDJdZTnLeW6SB43r/qcytA4u5VeT3DrJx2q4sfydSX5zmWnflmRbVV2S4XKTD85RjrmNYehvMxzH3p5he5jCk5L87bgdHZrN3demsPBAmIuSvCtDeFl4sMuajuMLuvtzGfbbly3z/sLx9Sk1PIjg4gz3p+xeYZmLj9fvzdDQeK2HcGS+Omo5x2dowT8ryefX8Lnr4rlJHjYeTx6X4cEQX5lo2Rumu8/OEMY/lCFgvLi7z1nD+cbi4+ZSXpnkiu6+ZGbcanXEeRnOCb4/yYO7+5vjpX/HJHnVWK+dkeRuq9QfK/njJH9YVedkjt6O8XK248flvj/D/rPUdOdmCCtvqapLM5wf/ubM5dQnJfmbWvQAqSUsVyev5iZV9amZv/+2xDSvydAD/tqxzMutw4OS/P1Y152T5K/G4/7ic97lzpWfluEy9QsyXFV095n19NUMx5hn1N4N6StZ02+2Tl6QIZxenOH88qKsY52zcDMrsI9qvH+hhp6dN2a4gXXuJz5d39Rw6c8zF9+fUcNlgy/p7uVaB+E6qZl7harquCRHdPdyjWMsoYYrMS7I8F9VbPUAe52NvUBXd/e3xl6CF67x0ugDVg1PBD6nu18yvlZHcL0xXm1ycHd/vYYrwN6V5K4952PxV7OVrnGGzXJ8Df+Z5yEZWqiXu1l1SxsvG1SxspGOrqrfylB3fTLTXYqyJYzHqZdkeKiK8DWfOyR57XhJ1jcz3CfMKsZeyq9meApxEnUE1zs3yfBfLRyc4XL//7Je4SvRAwYAADAZ94ABAABMRAADAACYiAAGAAAwEQEMAABgIgIYAADARAQwAACAifxfug3lJzmIRGEAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 1080x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "_ = plt.figure(figsize=(15,5))\n",
    "_ = plt.title(\"Level 3\")\n",
    "_ = plt.bar(\n",
    "    data_level_3.name,\n",
    "    data_level_3.Value,\n",
    "    width=0.8,\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [],
   "source": [
    "data_level_3_grouped = data_level_3.groupby([\"name\"]).mean()\n",
    "data_level_4_grouped = data_level_4.groupby([\"name\"]).mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "_ = plt.figure(figsize=(15,5))\n",
    "_ = plt.title(\"Grouped Data\")\n",
    "_ = plt.plot(data_level_3_grouped, label=\"Level 3\")\n",
    "_ = plt.plot(data_level_4_grouped, label=\"Level 4\")\n",
    "_ = plt.legend()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "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": "3.6.8"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}