lkluft/pyramid-pie.ipynb

## pyramid-pie.ipynb
{
  "cells": [
    {
      "metadata": {
        "ExecuteTime": {
          "start_time": "2019-03-04T10:06:54.230765Z",
          "end_time": "2019-03-04T10:06:54.621474Z"
        },
        "trusted": true
      },
      "cell_type": "code",
      "source": "%matplotlib inline\nimport matplotlib.pyplot as plt\n\n\ndata = {\n    'Sky': 75,\n    'Sunny side of pyramid': 19,\n    'Shady side of pyramid': 6,\n}\n\nfig, ax = plt.subplots()\nax.set_prop_cycle(color=['#1e88e5', '#ffd54f', '#6d4c41'])\nax.pie(data.values(), startangle=-40)\nax.legend(data.keys(), loc='center', bbox_to_anchor=(1., -0.25, 0.5, 1))\nax.set_aspect('equal')",
      "execution_count": 1,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": "<Figure size 432x288 with 1 Axes>",
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    }
  ],
  "metadata": {
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3",
      "language": "python"
    },
    "language_info": {
      "name": "python",
      "version": "3.6.5",
      "mimetype": "text/x-python",
      "codemirror_mode": {
        "name": "ipython",
        "version": 3
      },
      "pygments_lexer": "ipython3",
      "nbconvert_exporter": "python",
      "file_extension": ".py"
    },
    "toc": {
      "toc_threshold": 6,
      "toc_number_sections": true,
      "toc_cell": false,
      "toc_window_display": false
    },
    "gist": {
      "id": "",
      "data": {
        "description": "",
        "public": true
      }
    }
  },
  "nbformat": 4,
  "nbformat_minor": 2
}
	{
	"cells": [
	{
	"metadata": {
	"ExecuteTime": {
	"start_time": "2019-03-04T10:06:54.230765Z",
	"end_time": "2019-03-04T10:06:54.621474Z"
	},
	"trusted": true
	},
	"cell_type": "code",
	"source": "%matplotlib inline\nimport matplotlib.pyplot as plt\n\n\ndata = {\n 'Sky': 75,\n 'Sunny side of pyramid': 19,\n 'Shady side of pyramid': 6,\n}\n\nfig, ax = plt.subplots()\nax.set_prop_cycle(color=['#1e88e5', '#ffd54f', '#6d4c41'])\nax.pie(data.values(), startangle=-40)\nax.legend(data.keys(), loc='center', bbox_to_anchor=(1., -0.25, 0.5, 1))\nax.set_aspect('equal')",
	"execution_count": 1,
	"outputs": [
	{
	"output_type": "display_data",
	"data": {
	"text/plain": "<Figure size 432x288 with 1 Axes>",
	"image/png": 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/AChlHcIcvO1vXP5PwkeuHAd71lmac+oicY2JlHX6ZgLvG9kpQ/LmHpA01Fn6k373qpW8WI9lE0YEV75qJV8H4P9Y5zA1B2lt5Y6UtyuknN6TdZaWTEqzj+W4zj9fr0v1lcTU7Fnn7GrLrhkjFyOi/3kk5ie48m20hnUA09Lrt6W8k+8gq+vNOklrbGw4hyEDbU4bY1vyhppHhuW83ND9ZlGhMbZnZloA37AOQcRHkOWrVvI5AApY5zCVVXGf7unpcOOhj3tnbcRjtgkyKYwyTF0CXY+kY+k+iitZljbDYyfd1UZMQZDl2+gr1gFM4cXAn38d4nlcEFc2PIxUysnGjrQz2uECDnCMOLMqLur057uMtU0zWME6ABEnIZfvOgCimh070P3Esbm9f4xjnaM9Hk2wibezw0Nn/rYVB3A9r+1JScmb/yun03boemIzugDgR9YhiDhxQr4SSKHSbAIwjnUOY/BzvHbxv4PS7SWc3o11lvY6cbL+6Io11UafKVwnczy2M/qf3nU2XV2NvW0jmadW8ipjbjA3N9dDJpOtBBAOYS9+SOfpABzXarUzY2Ji7vsEKWMQqD3+CRGUr5Os+ua2gYtqJZzel3WWjngkVB7Rzbkmp7xCH2vM7dpoK/sOz/nLxT0R6eUVXfwCjLltI6gG8IWxNyqTyVZ6eXmFuru7l0kkEuGufEin6XQ6rqSkJOzKlSsrATx57/cF/S+vWslnw8Lnp0qga9iRsvC0nbQ+kHWWznh2ukN3mOAwkETf4DvwyN/dva/te+DDPBnYoFbyprjePNzd3f0mFa/4SSQSvbu7ewUMn3Lu/76Z83TEMtYBOmN9QsY+L/uKfqxzdJavtzTQh5eYZOQnB3SNOf1pVJ+z/95tiu13UIaJtiuh4rUejX/XLfas0A87AMBPAI6jlX89hOyvvX/Ym+h22ixPozCHmdMcAv6x9HYNADtjb5sDpL0ubx/Y7fa5Pb/2fSNRz0lZ/mx+r1byx8yxI4VKE9OZ96uV/AOf/F1aWioZN25cr9u3b0urq6sl8+fP1yxevJg/fvx4m59cQkxD8CvfxmE7/2Sdo72Gex35bVbgtgTWOYzJpbukR2iI7KBJ93HrTPLw7L8ck9ffLjflfh5AB+BNRvs2uhUrVrgOGzasIjs7u/Do0aMnH3vssdusMxEDwZdvo/WwoJsugp005z/r97k/x1nEJ4t2mT7RPgqASYvRtv5m9PDsl8qcqi79bsr9tOJrtZI32qV1rDk4OOhycnIcL168KJNIJHBzc7tz3P61117rsWDBAq/09HSPFStWuABAXl6eXVpamh+zwFbEIspXreQbAChZ52gLZ3ll+f9LXsJJOHRjncUUHBw454Q4uckfnCnVa/0H5c1z9rpx2JxPC24A8JYZ92dys2bNuhEcHFwzbNiw4KioqN75+fm2APDSSy95Ozs7NyxatOjKjBkzSjdt2tQdAFavXu06derUG2xTWweLKF8AUCv5LQD+yzrHg0i5Bu1/B6Wft5E0+LHOYkrjRtn1l0hQbOr9cED3uJMfhof+vtFcT5D4Sq3ki8y0L7OQy+VYunTplVOnThUsXLiw+G9/+xtfXFxss3fvXqf58+dfAwBfX18tABQXF8v27dvnNHLkyFtsU1sHiynfRq+jA88YM5dvB7y339X2dhTrHKYml3G2jw+1NcrMh4fhAHnwpR+TEvMXm/ohnVUA0k24fSZOnz5tU1NTwwFAjx496nU6Heft7V33yiuvXB0/frxfQ4PhKMSECRNKX3jhBd/Y2NjbUqmUaWZrIeg73FqiUGnWAvgj6xz3Sg//evfT/rstYmaDMeh0et3cN2+dra9HkLn2WW3TPScrellvrczeyQSbn69W8ktNsN27HD169PeIiAizDer5z3/+47x06dIetra2egBYvny5+plnnvE/fvz4yY8//tj1wIEDjhs2bLhQVVXFeXp6Rmzfvr0wISHB0ucvC8rRo0fdIiIi/O79uiWWry8MJ9/M+mj1BxntnX34w6g1URwHq1oyZOfW5azbWGPUu94epkEiL/pv1BL7SnsvHyNu9gSAKLWSrzfiNltk7vJtq6qqKi4lJSU4OzvbEsd+Clpr5Wtphx2gVvIXAfyNdY4m4c4XznwYtSbY2ooXAOJibGIdHbgj5tynVFcfNCR3rp172bF8I252ljmKV6jy8/Ntk5KSgl988cVOD88nbWdx5dvoEwD7WIdws7l5ffOjy+w4Dl1ZZ2HlmT/ay829Tw56t4QTy4KDLmYa42fgK7WSt+hb2DurT58+tbm5uYXTp09ndW21VbLI8m288eJPAGpYZZBz2rqsQekauURnzI+/Fic4QPaImytnktuOH4QDbMPUXw+IL3hvdyce0lkKYK4xcxHSVhZZvgCgVvKFYHh2OjN5abazTXVfVvsXkmenO/SA4XE7ZudV+tvAoYfnHJI21FZ14O3PqZV8idFDEdIGFlu+jd4F8MB7202y08h/7wrtqnnU3PsVqh6eUj+/nlKzr36bONaW9E89NEttX3P9cjve9oVayX9rslCEPIRFl69ayWsBTARw01z7nKLYe3Ccz0GruaSsrWb80T4EQCWr/ct0taHDDr/KuVacastt6KcAvGLqTKyVlpZKBg8eHBgXFxfSp0+f0A0bNjizyDF58mTFvV+bNWuW95YtWzp0yaBOp8PgwYMDY2JiQq5evcrkRPeMGTN8b9++zTX/2jfffNN1zpw5fFu3YfGzB9RK/oxCpXkGgMlXMTHdz55a1Oc/fTgO3MNfbV26OUs8IsJlu48e1zL7h4mD3mtA/jvO+b2mHTjPP9baUKNaAJPUSr4jhymMr2B0p6aaIWxzq5/8mobqzJ8/v0Sn06G0tJRJUW3YsEFtzO1dvHhRznGcPjc3t9OXxTU0NKAjN5WsWrXqYmf3bdEr3yZqJf8dgA9NuQ8vu7KrGxM/cOY4OJpyP5ZsylP20RwHptewcoB9n3P/7h9TuHxXKy+Zr1byZr08jpXWhuqEh4eHNr0mIiKiNwCkpaX5TZw4UZGYmBg8ZMiQAJ1Ohy1btjglJSUFDRkyJCAkJCQsOzvbft++ffZNK1mtVovIyMjeumY3Hq5du7ZbeHh4aFxcXIhKpXJvvr/9+/fbh4eHhw4ePDiwsLDQDjCsYqdPn+4bHx8fnJiYGHT27Nm7rp65ceOGdPDgwYGxsbEhf/jDH3rV1NRwf/7zn33z8vK6PP74472avzYtLc1v8uTJPfv37x88duxYPwAYNmxYwPnz5+UAsHTpUvePPvrIdc6cOfzYsWP9kpOTg3Jzc+1HjRrlHxcXFxITExNSVFRkAwBhYWGhkydP7tm7d++wd9991y0tLc0vNDQ0rGkAUVxcXEhFRYXk+vXr0gEDBgQlJSUFbdy4sXt7/n5EUb6N/grAJMcd7SR11TtTFt6QSXQ9TLF9sbCz45ySE22YT5/jAM6n5EDKoFzlPomuvrbZtzbBxP9IC0lrQ3Va8+ijj97ev3//aUdHR11OTo49AGi1Wm7nzp1nly5deunzzz93HTBgQHVRUZFdTU0Nl5mZ2TU5OfmmRPK/Gvn222+7r169+nx2dnbh66+/ftfJzAULFnivX7/+3I4dO86Ul5fLAODrr7927t69e8OhQ4dOq1Sq4vT09Lv+G/vwww/dUlNTK3JycgpDQ0Orv/jiC5cPPvjgUnx8/K2tW7eeu/fPEB0dXXXw4MHTtra2+i1btjhNmTLlxurVq10A4Mcff+w+derUMgDw9fWt27NnT1FcXFz1unXr1NnZ2YVz5sy5kpGR4Q4AN2/elC1cuPByTk7OqfT0dJ+MjIxLe/fuLVyxYoVH8/1lZGS4jRkzpmzv3r1Fnp6e7TrpLJrybbxIfjxg7JWXXr914OIjXeS1YcbdrjiNHmGbIJXgAuscANC1unhA6qFZRbZ1ZSUAjgB4uvEyRavQ0lCde1/T/Cq9uLi4KgDw8fGpu379uhQAwsPDqwDAz8+vrqkwU1NTyzdt2uS8bt06l2eeeeauRy0tXLhQ8+GHH3qMGTPGb9euXXd9SiwpKZFHRETUSiQSREZGVgHAiRMn7H766aducXFxIXPmzPGtqKi46xjA2bNnbRMSEioBICEhofLMmTMP/AckPj6+CgCio6Mri4qKbCdOnFixfft251OnTtm4urrWu7i46Br/rJWAYfX+0ksvecfExIQsXbqUv3z5shwAnJ2dtYGBgfVOTk46f3//Gm9vb62bm1tDXV3dXYccz5w5Y9u0z/j4+Had8xBN+QKAWslfguFBdUa7N/3TmC929+pyTVRD0U1JKuXkIx+3vcQ6RxN5Q3X4sJw5xQBGCeY4r5m0NFQHAGprayVarRanT5+2KSsru3Peh+O4O02s1+u5xq+h2dcAADNnzixds2aNa3FxsU1UVNRd19r36tWrbv369Rfef//94gULFng3/567u3t9fn6+rU6nw7FjxxwAIDQ0tGbUqFFl2dnZhTk5OYUbN278vfl7AgMDaw8cOOAIAAcOHHAMCgpq/knmPjk5OQ4A8NtvvzkEBQXV2tnZ6QMDA2vmzp3rPWXKlDv/UDSt1g8cOOBQUlIiz83NLZw3b56m6c/Y/M/d/H/fKzAwsLZpn02/t5XFn3C7l1rJH1CoNJNhOAHXqX9cnu21Y/8f+CMpRglmRQYl2SRs/aX2ZG0dQh/+apOrkurrn1MreUGsxu/zgBNmnZWbm2v/1FNP9Wo+VAcAxo0bdyMqKiq0T58+lc7Ozu1+KKpCoaivra2VjBgx4r474ubOncvn5OR0qaqqksyePfuu25Xfeeed4kmTJvVyc3Or79q1qxYAJk2aVLFz586u8fHxwQAwceLE0ldfffXOp9eXX375+rhx4/w3btzo4uHhUb9o0aIrarW61bsqc3JyHOPj4128vb3rnnjiiVsA8PTTT98YP3584HfffXffJL6IiIiaq1evyhMTE4NCQkLafdPW7Nmzr48aNarXd999193Ly6u+Z8+edW19r8UN1mkrhUozC8Dyjr4/0bXwxIaEjwI4zvjPK7MGR/Lr81atq45mHEMHYGxGZtYPjHPcIdTBOu01ePDgwLVr1/7u7e3N5OaalqSlpfnNmzfvSmxs7F0lmpWV5bh27VqX1atXd/oKhY4QzWCdtlIr+X8B6NCIQB/7G5p1CRnuVLwdF9lHHt3ViTP7DTD3eFlIxSsWQ4cODQgKCqoRUvG2Zu3atd1eeeUVX6VSKbihQaJd+QKAQqXhAKwGML2t73GU1tw+/Ni8YgdZXYjpklmH82pt4Qf/qgoGmFwX/UpGZtZHDPb7QGJZ+ZK2s7qVL3BnAM8MAGva8noOOt0vKW8XUPEah79CFuLlIWFx2/FfhFi8hDQn6vIFALWS18FQwJ8/7LVr4v+1x9uhLM70qazHs9MdegJo80mITtIDmJWRmfWJmfZHSIeJvnyBOyvgF2CYA9yiV4O37E3xKEgxWygr4e4m8QkKMMvQHT2A5zMysz41w74I6TSrKF/AUMBqJf8XAO/d+73BHvlHXw7+KZ5BLKvwzBT7PjDt8CMdgJkZmVlfmHAfFqe1wTrNby9uq2XLlrlnZGS4tvd9+/fvt2+6zbi5ptuaO+L8+fPy8PDw0DFjxvh1dBudZYxhQaK7zvdh1Er+dYVKcwPAIgCcv+PVC1/GferLcbBhnU2sujhKXGKj5LtyfqtPMcHmawHMyMjM2mCCbZvc7JGDOzVYJyMzS9CDdRITE6sTExON+kDO7du3Oz311FM33nrrrWud2U5Hh+oAxhkWZDUr3+bUSn4JgEldZVXXtg1cVC/h4MI6k9hNGGsXx3G4YuTNlgAYYqnFa2qtDdapqqqSPPnkk/6hoaFhy5cvdwGA5cuXuyQkJASHhYWFNn2tqKjIJiYmJmTgwIGBe/fu7QIA6enpHk3DZfLy8uzS0tL8mu9z9uzZfGRkZO9+/fqF7Ny503HLli1Ozz33nA8AfPzxx65NK9bq6moJAFy+fFk2dOjQgP79+wePGjXKX6u9++q1Q4cO2UdHR/eOiorqrVQqva5evSpdunRpj1WrVnkolUqv5q8NCwsLnTp1as8+ffqELlmyxL22tpaLiYm5c/J8xIgRvQoKCmzi4uJCnn2bKwNJAAAIb0lEQVT2WZ+BAwcGXbx4UZaYmBjcr1+/kNTU1F5arRaFhYU2kZGRvVNTU3sFBAQ88tVXX3V77LHHAoKDg8Py8vLsgAcPC2orqyxfAFAr+a83Jy0baSvV0pQyM7Cx4RyGptgUGXGTJwDEZ2RmMX+Wn1C1Nljn+vXr8jVr1qgPHjx46osvvvAAgGnTppUfOHDgdG5u7qlPP/3UEwDefvttrwULFlzevXv3maZbbGfMmFG6adOm7gCwevVq16lTp95ovs+srCznnJycU4cPHy5MSUm5M+tAq9Vi+fLlnjk5Oac+++yzixqNxhYA3nrrLa/Zs2dfO3jw4OnIyMiqtWvX3jUZbN68ed4rV678PTc399TevXu7lpeXS1999dUrzz///FWVSnXXP+YVFRWyuXPnXs3Lyzu5fv16t7q6Oi48PLxqz549DqWlpZKysjJpWFhYHQA88cQTFb/++muRu7t7w+7du08fPny40MfHpy4zM7Nr47akW7ZsOff+++9fWLZsWY+tW7eeffPNNzWrVq2669BLS8OC2spqyxcAAuI+zwYQC+Aw6yzWYMRjtokyKe6bRNUB3wFIyMjMuu92UfI/rQ3W8fX1rXVxcdE5Ozvrmq7z/+GHH7rGxsaGJCcnB6vValsAOH/+vG1iYmIlAMTGxlY2vlcLAMXFxbJ9+/Y5jRw58lbzfaanpxdPmTJFMXnyZEVxcfGdMtJoNDKe5+vs7e31np6eDb6+vrUAUFhYaJeens7HxcWFfP/9990vX758V4GVlJTIo6OjaxqH8VSeOnWq1cE6jo6ODX379q2Vy+Xw9/evuXDhgnzGjBk31qxZ47p27druo0ePvnM7dFJSUiUAXLt2Tfr4448HxMbGhuzYsaPbpUuX5AAQHBxcI5PJ0LNnz/qQkJBqqVSKnj171pWVld11nKKlYUFtZdXlCwAI23wJQDIAOlljYhIJJ0170q4zz0zTAZifkZmVlpGZdeuhr7ZyrQ3WaWlQzOLFi3v8/PPPZ3bv3n3a3t5eBwD+/v61Bw8edACA3NzcO58QJ0yYUPrCCy/4xsbG3r73mOnw4cNvbdy4UZ2cnHyraTwjAPA8r718+bJNTU0NV1JSIr148aItAAQFBdUsWrSoODs7u/DYsWOnXnvttbtuQHF3d6/Py8uz0+l0OHLkiGPv3r1bHaxTWVkpzc/Pt9Vqtfj999/tevbsWT9w4MCqgoIC+02bNrlMnz79zmCdptxffvml69ChQ2/m5OQUDh06tLzZYJ07d5+1NFyoeb57hwW1ldWdcGtR2OZqAM+hYPTPMJQwHQM2kQH9beJ/3FqTX12DPu1862UA0zMys34xRS4xam2wTktGjhxZlpSUFBweHl7VNGznjTfeuDJx4kT/9957T9d8AM+UKVPK58yZo9i+fft9T5JITU0NrKmpkdTV1XErV65UX7t2TQYAMpkMs2bNutqvX7/eAQEBNTzP1wLAO++8c3natGl+//jHP3gAWLZs2aXk5OQ7K8jFixcXz5w500+n02H48OHlISEhddu2bWvxz+Ds7KxdsmSJZ35+vuPkyZOvOzk56QBg0KBBNw8fPuzo6el53xCh4cOH33z66af9f/nll64ODg46tHMiYkvDgtpK1LcXd0jBaB8AawGkME4iWgWn6o99trpdT35eB2B2RmZWmakymYsYbi+uqqriUlJSgrOzszv9GB9jCg8PDz1+/PjJe7++YMECr5CQkJpp06bdN4XNHKzy9uIOMRyGGAJgARg9Dl3swnrL+3bvxmW34aVXAYzOyMyaKobiFYP8/HzbpKSk4BdffFFwg2pa8vrrr/fYvXu306RJk5gU74PQyvdBCkZHAvgUQH/WUcTmUnHD2WUZlX4AWrvQcgMMMxpKW/m+RRLDype0D618OyJs8xEAiQCeB0ArLyPy8ZYG+PAtDt25BsMM3iliK95GuqYTX0T8Gv+udS19j8r3YcI26xG2+XMAITBMR6OPCkYyc5pDAP53gqMewEcAQjMys75nl8rkjpeUlDhTAYufTqfjSkpKnAEcb+n7dNihvQpGJwH4JwCaBWEEK1ZX7TpxSlsBYG5GZpYxb8IQpNzcXA+ZTLYSQDho8SN2OgDHtVrtzJiYmPtuhaby7aiC0SMALATA+lE5luzX+nr9PHnED3SXGrE6VL6dUTCaAzAGQDoMKxnSNgcBLETY5q2sgxDCCpWvMRSMlgB4CsAroCsjWqMD8D2A9xG2eT/rMISwRuVrbAWj+wF4CcAEgB7ACeA2gFUAPkLYZmPMdSBEFKh8TaVgtBuAmTA8QeO+wctWIBuGO9PWImyz4C5wJ4Q1Kl9TMxwXHgBgPIBxAHqwDWRS52Ao3HUI2yz6KxcI6QwqX3MyHBtOgqGI0wB4sg1kFCcBbAOwiY7lEtJ2VL6sGIo4AsBgAINgGGvZ5uc/MVQOYAcMhbsNYZsvMs5DiEWi8hWKgtEyADEwlHE8gL4A/ACwvBNKC6AAQG7jrxwAuQjbfN9oPkJI+1D5ClnB6C4A+jT+6gsgDIaTdz6AUR/4WQbgdwDqxt/PwFC2RxtnHRNCjIzK1xIZTuJ5APCC4bixBwyHLGyb/bJp/F0KoArALRgu+7rd+L9vAbgCQI2wzaZ8rDshpAVUvoQQwgAN9iCEEAaofAkhhAEqX0IIYYDKlxBCGKDyJYQQBqh8CSGEASpfQghhgMqXEEIYoPIlhBAGqHwJIYQBKl9CCGGAypcQQhig8iWEEAaofAkhhAEqX0IIYYDKlxBCGKDyJYQQBqh8CSGEASpfQghhgMqXEEIYoPIlhBAGqHwJIYQBKl9CCGGAypcQQhig8iWEEAaofAkhhAEqX0IIYYDKlxBCGKDyJYQQBqh8CSGEASpfQghh4P8D/QUN7kxCsPoAAAAASUVORK5CYII=\n"
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