tuffacton · April 28, 2020 13:33
diff --git a/academic-keyword-tool.ipynb b/academic-keyword-tool.ipynb
 {
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "academic-keyword-tool",
      "provenance": [],
      "collapsed_sections": [],
      "authorship_tag": "ABX9TyM3kg96Lcg5ANcGanphA6M2",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/gist/tuffacton/8624f66ab209a18980d62b739f191937/academic-keyword-tool.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "KW-Hr9yE2PT_",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 187
        },
        "outputId": "d3d30095-aa33-4fce-b932-969795d0999e"
      },
      "source": [
        "# Clone the entire repo.\n",
        "!git clone -l -s https://github.com/Pold87/academic-keyword-occurrence.git cloned-repo\n",
        "%cd cloned-repo\n",
        "!ls"
      ],
      "execution_count": 1,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Cloning into 'cloned-repo'...\n",
            "warning: --local is ignored\n",
            "remote: Enumerating objects: 9, done.\u001b[K\n",
            "remote: Counting objects: 100% (9/9), done.\u001b[K\n",
            "remote: Compressing objects: 100% (9/9), done.\u001b[K\n",
            "remote: Total 146 (delta 1), reused 3 (delta 0), pack-reused 137\u001b[K\n",
            "Receiving objects: 100% (146/146), 40.99 KiB | 224.00 KiB/s, done.\n",
            "Resolving deltas: 100% (57/57), done.\n",
            "/content/cloned-repo\n",
            "bitcoin_chart.png  extract_occurrences.py  out.csv  README.md\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "lZ0QfxyR2ryQ",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "outputId": "4563c54f-342d-47da-b7de-a78ea066a3a2"
      },
      "source": [
        "!pwd"
      ],
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/content/cloned-repo\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "HjRMgC5C264B",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 221
        },
        "outputId": "069626cd-f452-441b-96c7-7e248a8fc426"
      },
      "source": [
        "!python3 /content/cloned-repo/extract_occurrences.py 'gdelt' 2010 2020"
      ],
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "year,results\n",
            "2010,3\n",
            "2011,1\n",
            "2012,2\n",
            "2013,37\n",
            "2014,107\n",
            "2015,131\n",
            "2016,193\n",
            "2017,233\n",
            "2018,240\n",
            "2019,314\n",
            "2020,63\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ZJljk13B3wQm",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "outputId": "706a81db-df18-44e8-9da6-a902d061c1e8"
      },
      "source": [
        "!ls"
      ],
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "bitcoin_chart.png  extract_occurrences.py  out.csv  __pycache__  README.md\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "IK6A3v8g35Xk",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 295
        },
        "outputId": "4b6bb2b8-14d0-432a-99e8-cf0a3f57f868"
      },
      "source": [
        "%matplotlib inline\n",
        "import matplotlib.pyplot as plt\n",
        "import csv\n",
        "\n",
        "x=[]\n",
        "y=[]\n",
        "\n",
        "with open('out.csv','r') as csvfile:\n",
        "  plots = csv.reader(csvfile, delimiter=',')\n",
        "  next(plots)\n",
        "\n",
        "  for row in plots:\n",
        "    x.append(int(row[0]))\n",
        "    y.append(int(row[1]))\n",
        "\n",
        "plt.bar(x,y)\n",
        "plt.xlabel('Year')\n",
        "plt.ylabel('Occurences')\n",
        "plt.title('Occurences of \"GDELT\" in Google Scholar')\n",
        "plt.show()"
      ],
      "execution_count": 23,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "B5rvhXMo5aOf",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        ""
      ],
      "execution_count": 0,
      "outputs": []
    }
  ]
 }
	{
	"nbformat": 4,
	"nbformat_minor": 0,
	"metadata": {
	"colab": {
	"name": "academic-keyword-tool",
	"provenance": [],
	"collapsed_sections": [],
	"authorship_tag": "ABX9TyM3kg96Lcg5ANcGanphA6M2",
	"include_colab_link": true
	},
	"kernelspec": {
	"name": "python3",
	"display_name": "Python 3"
	}
	},
	"cells": [
	{
	"cell_type": "markdown",
	"metadata": {
	"id": "view-in-github",
	"colab_type": "text"
	},
	"source": [
	"<a href=\"https://colab.research.google.com/gist/tuffacton/8624f66ab209a18980d62b739f191937/academic-keyword-tool.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
	]
	},
	{
	"cell_type": "code",
	"metadata": {
	"id": "KW-Hr9yE2PT_",
	"colab_type": "code",
	"colab": {
	"base_uri": "https://localhost:8080/",
	"height": 187
	},
	"outputId": "d3d30095-aa33-4fce-b932-969795d0999e"
	},
	"source": [
	"# Clone the entire repo.\n",
	"!git clone -l -s https://github.com/Pold87/academic-keyword-occurrence.git cloned-repo\n",
	"%cd cloned-repo\n",
	"!ls"
	],
	"execution_count": 1,
	"outputs": [
	{
	"output_type": "stream",
	"text": [
	"Cloning into 'cloned-repo'...\n",
	"warning: --local is ignored\n",
	"remote: Enumerating objects: 9, done.\u001b[K\n",
	"remote: Counting objects: 100% (9/9), done.\u001b[K\n",
	"remote: Compressing objects: 100% (9/9), done.\u001b[K\n",
	"remote: Total 146 (delta 1), reused 3 (delta 0), pack-reused 137\u001b[K\n",
	"Receiving objects: 100% (146/146), 40.99 KiB \| 224.00 KiB/s, done.\n",
	"Resolving deltas: 100% (57/57), done.\n",
	"/content/cloned-repo\n",
	"bitcoin_chart.png extract_occurrences.py out.csv README.md\n"
	],
	"name": "stdout"
	}
	]
	},
	{
	"cell_type": "code",
	"metadata": {
	"id": "lZ0QfxyR2ryQ",
	"colab_type": "code",
	"colab": {
	"base_uri": "https://localhost:8080/",
	"height": 34
	},
	"outputId": "4563c54f-342d-47da-b7de-a78ea066a3a2"
	},
	"source": [
	"!pwd"
	],
	"execution_count": 10,
	"outputs": [
	{
	"output_type": "stream",
	"text": [
	"/content/cloned-repo\n"
	],
	"name": "stdout"
	}
	]
	},
	{
	"cell_type": "code",
	"metadata": {
	"id": "HjRMgC5C264B",
	"colab_type": "code",
	"colab": {
	"base_uri": "https://localhost:8080/",
	"height": 221
	},
	"outputId": "069626cd-f452-441b-96c7-7e248a8fc426"
	},
	"source": [
	"!python3 /content/cloned-repo/extract_occurrences.py 'gdelt' 2010 2020"
	],
	"execution_count": 11,
	"outputs": [
	{
	"output_type": "stream",
	"text": [
	"year,results\n",
	"2010,3\n",
	"2011,1\n",
	"2012,2\n",
	"2013,37\n",
	"2014,107\n",
	"2015,131\n",
	"2016,193\n",
	"2017,233\n",
	"2018,240\n",
	"2019,314\n",
	"2020,63\n"
	],
	"name": "stdout"
	}
	]
	},
	{
	"cell_type": "code",
	"metadata": {
	"id": "ZJljk13B3wQm",
	"colab_type": "code",
	"colab": {
	"base_uri": "https://localhost:8080/",
	"height": 34
	},
	"outputId": "706a81db-df18-44e8-9da6-a902d061c1e8"
	},
	"source": [
	"!ls"
	],
	"execution_count": 12,
	"outputs": [
	{
	"output_type": "stream",
	"text": [
	"bitcoin_chart.png extract_occurrences.py out.csv __pycache__ README.md\n"
	],
	"name": "stdout"
	}
	]
	},
	{
	"cell_type": "code",
	"metadata": {
	"id": "IK6A3v8g35Xk",
	"colab_type": "code",
	"colab": {
	"base_uri": "https://localhost:8080/",
	"height": 295
	},
	"outputId": "4b6bb2b8-14d0-432a-99e8-cf0a3f57f868"
	},
	"source": [
	"%matplotlib inline\n",
	"import matplotlib.pyplot as plt\n",
	"import csv\n",
	"\n",
	"x=[]\n",
	"y=[]\n",
	"\n",
	"with open('out.csv','r') as csvfile:\n",
	" plots = csv.reader(csvfile, delimiter=',')\n",
	" next(plots)\n",
	"\n",
	" for row in plots:\n",
	" x.append(int(row[0]))\n",
	" y.append(int(row[1]))\n",
	"\n",
	"plt.bar(x,y)\n",
	"plt.xlabel('Year')\n",
	"plt.ylabel('Occurences')\n",
	"plt.title('Occurences of \"GDELT\" in Google Scholar')\n",
	"plt.show()"
	],
	"execution_count": 23,
	"outputs": [
	{
	"output_type": "display_data",
	"data": {
	"image/png": "iVBORw0KGgoAAAANSUhEUgAAAYUAAAEWCAYAAACJ0YulAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4yLjEsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy+j8jraAAAeAUlEQVR4nO3debgdVZnv8e/PDMwQQmIMSeCgxgF8moBhcroIqBDQ4LVFUCEgGu0LNrQ4RPrajQ9iRxvB60SLgkRABhElDTQGIjyKSiBBpgSQAMEkBHKABBKQMe/9Y61TFJt9ztnn5NTeZ/h9nmc/u2pV1drv2kO9VatqVykiMDMzA3hNqwMwM7P+w0nBzMwKTgpmZlZwUjAzs4KTgpmZFZwUzMys4KRgA46kcZJ+L2mdpO+0Op5mkPQJSfNaHUdPSWqTFJKGN/E1T5F0QS+XPU/SN/o6poHESaEFJB0t6U5Jz0h6RNJZkka1Oq4BZCbwGLB1RJxUOzH/sI/Oj/NK5SMl/ZukeyU9LWmlpP+R9P7SPMsk/T0nnLWS/iTpc5JeU1P/85LWlx6352mvWAlKendpnqfztPJyO0i6QdK+eWV2Sr0GR8SFEfH+etMaIWmypIsltUt6StJ9kr4vaWJv66yapFGSzs2/kXWS/ippVqvjGuycFJpM0knAt4AvAdsAewM7AtdKGtmkGJq21VaRHYEl0fN/Xl4GTAeOArYFdgL+H3BwzXwfjIit8uvMBr4CnFMzz7cjYsvSY9d6LxgRf+iYB9glF48qLfe3HrahxyS9EVgAPAzsFhFbA+8E7gfeVfXrb4QzgS2Bt5J+Kx8ClrY0ok4oGRTr00HRiIFC0tbA14HPR8Q1EfFCRCwDDgPagE/m+YZJOlnS/XkLaZGkSXnaLpKulfSEpEclnZzLX7Hbm7c8V5TGl0n6iqQ7gKclDZe0d94SXivpdkn7lua/QdKpkv6YY5gnaUxp+rtKyy6XdHQu30TS6ZL+luP7L0mb5WljJF2Zl3lC0h86+yFJeoekWyQ9mZ/f0dFOYAbw5bylfUCD7/0BwPuA6RGxICKez49rIuKEestExJMRMRf4GDBD0tsaea0q5L2eG0vjkfdg7svv5w8lqZPFTwH+GBFfiIgVABGxOiK+GxEXl+r8jKSl+bOZK2n70rS6n0eetpNe7s67LsdSt/tG0jaSzpG0SmlP7RuShnUS9x7ALyJiTURsiIh7IuKyUl11fwvZSEk/zzEtljS1tNxb8/d7bZ72oU5i3TZ/X9slrcnDE0vTb5B0mqQ/As8Ar++kHQNLRPjRpAdwIPAiMLzOtDnARXn4S8CdwJsBAbsC2wFbAauAk4BN8/heeZnzgG+U6tsXWFEaXwbcBkwCNgMmAI8D00gbB+/L42Pz/DeQtiTflOe/AZidp+0IrAOOAEbk2KbkaWcCc4HROb7/Bv4jT/sP4L/yMiOAdwOq816MBtYARwLD8+usAbar19YG3/vZwA0NzLcMOKBO+d+Af+ru9UnJPTr5jDud1kBcRwM3lsYDuBIYBewAtAMHdrLsI8DR3dS/H6lLbndgE+D7wO8b/Dz+DJwOjCTteTwFXFCvzcCvgR8DWwCvBW4GPttJTD8FFgPHAJNrpnX1WzgFeJb03R6Wv3c35WkjSHsbJ+d49yN9l99c+9mSvtcfATbP9f8S+E0phhvy92KX/L6MaPU6pi8e3lNorjHAYxHxYp1pq/J0gE8D/zci7o3k9oh4HDgEeCQivhMRz0bEuohY0IPX/15ELI+Iv5P2Sq6OiKsjbYVdCywk/ZA6/Cwi/prnvxSYkss/DlwXERdF2tt5PCJuy1uqM4F/iYgnImId8E3g8LzcC8B4YMe83B8i/7pqHAzcFxHnR8SLEXERcA/wwR60tdYY0soRAEmj85bik5KebWD5h0krxw5fzMt3POZsRGy9NTsi1kbqgrqelz+fWrVtPz7HvF7ST3LxJ4BzI+LWiHgO+Cqwj6Q2uvg8JO1A2qL/t0h7XjeSNgpeRdI40vfrxIh4OiJWkzYiDq83P/B54ELgeGBJ3os5KE/r7rdwY/5uvwScT9qwgtRdu2V+756PiN+RkusRtS+ev9e/iohn8nf5NOB/1cx2XkQszu/LC520Y0BxUmiux4Axqt+nPz5Ph7Q1f3+deTorb9Ty0vCOwEfLKzbSVt740jyPlIafIf2YuopjLGmralGpzmtyOcB/krbS5kl6QJ0fNNweeKim7CHS3k1vPU6pbTlpjQLeTtoy7s4E4InS+OkRMar0mLERsfVWZ59Prdq2/yC3/bukLWeoec8jYn1ebkLttOyh0rQnIuKZ0rTl1Ldjfr1Vpe/Hj0l7DK8SEX+PiG9GxNtJW+2XAr+UNJrufwu1782m+Xe3PbA8IjbUacsrSNpc0o8lPSTpKeD3wKia7q7O2jpgOSk015+B54D/XS6UtCVwEDA/Fy0H3lBn+eV03m/5NGmF3OF1deYpb5UvB86vWbFtERGzu29Gp/E9Bvwd2KVU5zaRDrKSt+ZOiojXkw4afkHS/nXqeZi0AinbAVjZQGydmQ/soV6cbSNpD9JK48bu5u2n5lPznavjFe+5pC1IK+KVtdOyjs9jFTBaUvm7N6mT11hO+v6PKX0/to6IXTqZvxART5H2OrcgnSDQ1W+hKw8Dk2qOZXX23TqJ1IW7V6SD8+/J5eVjN4PuMtNOCk0UEU+SDjR/X9KBkkbk3fNLgRWk3VxIfamnKp1GKEn/IGk70m7ueEknKh3Q3UrSXnmZ24BpuVvkdcCJ3YRzAWn3/wNKB7Y3VTo43chK80LgAEmHKR2w3k7SlLz19RPgTEmvBZA0QdIH8vAhkt6Yu5meBF4CNtSp/2rgTZI+nuv/GLBzbn+vRMQ8UhfLbyTtpXR66ghSd0JdkraWdAhwMamP/M4evOQm+T3teLTyt3YK8G5JZ0iaAOmgP+msng4XAcdImiJpE9IKeEGkEyE6/Twi4iFSt+Mp+T3dh066+SJiFTAP+E5+b18j6Q2SartkyDF+TdIeud5NgROAtcC9dP1b6MoC0p7Dl/Pvb98c78V15t2KtJGzNu+d/HsD9Q94TgpNFhHfJh3kOp10QG4Baatn/9yXC3AGKVHMy/OcA2yW+zXfR/oSPwLcB7w3L3M+cDvpQOk84JJu4lhOOj3zZNJByuWkA9zdfidyH/Y00pbUE6SE1NFn+xVSF9FNeZf7OtLWFsDkPL6etNf0o4i4vk79HcdPTiJ1YXwZOCQiHqudt4c+TFqZXEBauTxI6kv/QM18/y1pHek9+VfS53FMzTwdZz91PGpjW09aoXQ89tvI2HstIv4K7AVMBG7Pbfsjaav5a3me6/Lwr0hb/28g9/U38Hl8AtgnT/sG6bvX8V2udRTpAO8S0sHqy3hll+UrQgd+RtoDfZj03T84ItZ381vo6r14Pi9zUK73R8BREXFPndm/SzrJ4jHgJlJX6KCn+sf5zMx6R9IlwD0RMSS2rAcb7ymY2UbJXTxvyN1BB5L2QH/T6risdwb6P1vNrPVeB1xOOjC9gvR/jr+0NiTrLXcfmZlZwd1HZmZWGNDdR2PGjIm2trZWh2FmNqAsWrTosYgYW2/agE4KbW1tLFy4sNVhmJkNKJJq/6FecPeRmZkVnBTMzKzgpGBmZgUnBTMzKzgpmJlZwUnBzMwKTgpmZlZwUjAzs4KTgpmZFQb0P5rNzHqibdZVldW9bPbBldXdTN5TMDOzgpOCmZkVnBTMzKzgpGBmZgUnBTMzK1SWFCRtKulmSbdLWizp67l8J0kLJC2VdImkkbl8kzy+NE9vqyo2MzOrr8o9heeA/SJiV2AKcKCkvYFvAWdGxBuBNcCxef5jgTW5/Mw8n5mZNVFlSSGS9Xl0RH4EsB9wWS6fAxyah6fncfL0/SWpqvjMzOzVKj2mIGmYpNuA1cC1wP3A2oh4Mc+yApiQhycAywHy9CeB7erUOVPSQkkL29vbqwzfzGzIqTQpRMRLETEFmAjsCbylD+o8OyKmRsTUsWPr3nfazMx6qSlnH0XEWuB6YB9glKSOy2tMBFbm4ZXAJIA8fRvg8WbEZ2ZmSZVnH42VNCoPbwa8D7iblBz+Mc82A7giD8/N4+Tpv4uIqCo+MzN7tSoviDcemCNpGCn5XBoRV0paAlws6RvAX4Bz8vznAOdLWgo8ARxeYWxmZlZHZUkhIu4AdqtT/gDp+EJt+bPAR6uKx8zMuud/NJuZWcFJwczMCk4KZmZWcFIwM7OCk4KZmRWcFMzMrOCkYGZmBScFMzMrOCmYmVnBScHMzApOCmZmVnBSMDOzgpOCmZkVnBTMzKzgpGBmZgUnBTMzKzgpmJlZwUnBzMwKTgpmZlZwUjAzs4KTgpmZFZwUzMys4KRgZmYFJwUzMytUlhQkTZJ0vaQlkhZLOiGXnyJppaTb8mNaaZmvSloq6V5JH6gqNjMzq294hXW/CJwUEbdK2gpYJOnaPO3MiDi9PLOknYHDgV2A7YHrJL0pIl6qMEYzMyupbE8hIlZFxK15eB1wNzChi0WmAxdHxHMR8SCwFNizqvjMzOzVmnJMQVIbsBuwIBcdL+kOSedK2jaXTQCWlxZbQZ0kImmmpIWSFra3t1cYtZnZ0FN5UpC0JfAr4MSIeAo4C3gDMAVYBXynJ/VFxNkRMTUipo4dO7bP4zUzG8oqTQqSRpASwoURcTlARDwaES9FxAbgJ7zcRbQSmFRafGIuMzOzJqny7CMB5wB3R8QZpfLxpdk+DNyVh+cCh0vaRNJOwGTg5qriMzOzV6vy7KN3AkcCd0q6LZedDBwhaQoQwDLgswARsVjSpcAS0plLx/nMIzOz5qosKUTEjYDqTLq6i2VOA06rKiYzM+ua/9FsZmaFKruPzMy61DbrqkrqXTb74ErqHQq8p2BmZgUnBTMzKzgpmJlZwccUzKzgPn7znoKZmRWcFMzMrOCkYGZmBScFMzMrOCmYmVnBScHMzApOCmZmVnBSMDOzgpOCmZkVnBTMzKzgpGBmZgUnBTMzKzgpmJlZwUnBzMwKTgpmZlZwUjAzs4KTgpmZFZwUzMys0FBSkHSCpK2VnCPpVknv72aZSZKul7RE0mJJJ+Ty0ZKulXRfft42l0vS9yQtlXSHpN03vnlmZtYTje4pfCoingLeD2wLHAnM7maZF4GTImJnYG/gOEk7A7OA+RExGZifxwEOAibnx0zgrJ40xMzMNl6jSUH5eRpwfkQsLpXVFRGrIuLWPLwOuBuYAEwH5uTZ5gCH5uHpwM8juQkYJWl8wy0xM7ON1mhSWCRpHikp/FbSVsCGRl9EUhuwG7AAGBcRq/KkR4BxeXgCsLy02IpcVlvXTEkLJS1sb29vNAQzM2tAo0nhWFI3zx4R8QwwEjimkQUlbQn8Cjgxd0EVIiKAaDxciIizI2JqREwdO3ZsTxY1M7NuNJoUAtgZ+Oc8vgWwaXcLSRpBSggXRsTlufjRjm6h/Lw6l68EJpUWn5jLzMysSRpNCj8C9gGOyOPrgB92tYAkAecAd0fEGaVJc4EZeXgGcEWp/Kh8FtLewJOlbiYzM2uC4Q3Ot1dE7C7pLwARsUbSyG6WeSfpLKU7Jd2Wy04mnbV0qaRjgYeAw/K0q0nHLJYCz9Bg95SZmfWdRpPCC5KGkfv/JY2lmwPNEXEjnZ+htH+d+QM4rsF4zIaEtllXVVLvstkHV1KvDXyNdh99D/g18FpJpwE3At+sLCozM2uJhvYUIuJCSYtIW/gCDo2IuyuNzMzMmq6hpJAP/C6OiB/m8a0l7RURCyqNzszMmqrR7qOzgPWl8fX4MhRmZoNOw5e5yAeCAYiIDTR+kNrMzAaIRpPCA5L+WdKI/DgBeKDKwMzMrPkaTQqfA95B+ofxCmAv0pVMzcxsEGn07KPVwOEVx2JmZi3W6NlHY4HPAG3lZSLiU9WEZWZmrdDoweIrgD8A1wEvVReOmZm1UqNJYfOI+EqlkZiZWcs1eqD5SknTKo3EzMxartGkcAIpMTwr6SlJ6yQ91e1SZmY2oDR69tFWVQdiZmat19CeQr7xzSclfS2PT5K0Z7WhmZlZs/X0zmsfz+Pr6ebOa2ZmNvBUeec1MzMbYBrdU+jxndfMzGzg8Z3XzMys0G33kaTXAA8CX8Z3XjMzG9S6TQoRsUHSDyNiN+CeJsRkZmYt0mj30XxJH5GkSqMxM7OWajQpfBb4JfCc/9FsZjZ4+R/NZmZWaPQfze+p9+hmmXMlrZZ0V6nsFEkrJd2WH9NK074qaamkeyV9oPdNMjOz3mr0z2tfKg1vCuwJLAL262KZ84AfAD+vKT8zIk4vF0jamXRnt12A7YHrJL0pInzvBjOzJmq0++iD5XFJk4DvdrPM7yW1NRjHdODiiHgOeFDSUlLi+XODy5uZWR9o9EBzrRXAW3u57PGS7sjdS9vmsgnA8pr6J9RbWNJMSQslLWxvb+9lCGZmVk+j92j+PvkSF6REMgW4tRevdxZwaq7rVOA7QI/u8xwRZwNnA0ydOjW6md3MzHqg0WMKC0vDLwIXRcQfe/piEfFox7CknwBX5tGVwKTSrBNzmZmZNVGjSeEy4NmOA7+ShknaPCKe6cmLSRofEavy6IeBjjOT5gK/kHQG6UDzZODmntRtZmYbr9GkMB84gHQfBYDNgHnAOzpbQNJFwL7AGEkrgH8H9pU0hdR9tIz0pzgiYrGkS4ElpD2R43zmkZlZ8zWaFDaNiI6EQESsl7R5VwtExBF1is/pYv7TgNMajMfMzCrQ6NlHT0vavWNE0tuBv1cTkpmZtUqjewonAr+U9DDp0tmvAz5WWVRmZtYSjf557RZJbwHenIvujYgXqgvLzMxaodFrHx0HbBERd0XEXcCWkv5PtaGZmVmzNXpM4TMRsbZjJCLWAJ+pJiQzM2uVRpPCsPINdiQNA0ZWE5KZmbVKoweafwtcIunHefxzwDXVhGTWP7XNuqqyupfNPriyus16otGk8DVSd1HHcYTf0sV/DszMbGDqMilIGg58EziGl69iugPwAKnryf86NjMbRLo7pvCfwGjg9RGxe0TsDuwEbAOc3uWSZmY24HSXFA4hnXm0rqMgD/8TMK3TpczMbEDqLilERLzqngX5YnW+l4GZ2SDTXVJYIumo2kJJnwTuqSYkMzNrle7OPjoOuFzSp4BFuWwq6dLZH64yMDMza74uk0JErAT2krQfsEsuvjoi5lcemZmZNV2jF8T7HfC7imMxM7MWa/QyF2ZmNgQ4KZiZWcFJwczMCk4KZmZWcFIwM7OCk4KZmRUavXS2Wb/j+xuY9T3vKZiZWaGypCDpXEmrJd1VKhst6VpJ9+XnbXO5JH1P0lJJd0javaq4zMysc1XuKZwHHFhTNguYHxGTgfl5HOAgYHJ+zATOqjAuMzPrRGVJISJ+DzxRUzwdmJOH5wCHlsp/HslNwChJ46uKzczM6mv2MYVxEbEqDz8CjMvDE3j5dp8AK3LZq0iaKWmhpIXt7e3VRWpmNgS17EBzvnlPj2/UExFnR8TUiJg6duzYCiIzMxu6mp0UHu3oFsrPq3P5SmBSab6JuczMzJqo2UlhLjAjD88AriiVH5XPQtobeLLUzWRmZk1S2Z/XJF0E7AuMkbQC+HdgNnCppGOBh4DD8uxXA9OApcAzwDFVxWVmZp2rLClExBGdTNq/zrxBuvWnmZm1kP/RbGZmBScFMzMrOCmYmVnBScHMzApOCmZmVnBSMDOzgpOCmZkVnBTMzKzgpGBmZgUnBTMzKzgpmJlZwUnBzMwKTgpmZlZwUjAzs4KTgpmZFZwUzMys4KRgZmYFJwUzMytUdjtOM7Ohrm3WVZXVvWz2wZXU6z0FMzMrOCmYmVnBScHMzApOCmZmVnBSMDOzQkvOPpK0DFgHvAS8GBFTJY0GLgHagGXAYRGxphXxmZkNVa3cU3hvREyJiKl5fBYwPyImA/PzuJmZNVF/6j6aDszJw3OAQ1sYi5nZkNSqpBDAPEmLJM3MZeMiYlUefgQYV29BSTMlLZS0sL29vRmxmpkNGa36R/O7ImKlpNcC10q6pzwxIkJS1FswIs4GzgaYOnVq3XnMzKx3WrKnEBEr8/Nq4NfAnsCjksYD5OfVrYjNzGwoa3pSkLSFpK06hoH3A3cBc4EZebYZwBXNjs3MbKhrRffROODXkjpe/xcRcY2kW4BLJR0LPAQc1oLYzMyGtKYnhYh4ANi1TvnjwP7NjsfMzF7Wn05JNTOzFnNSMDOzgm+yY31mIN5QxMxeyXsKZmZWcFIwM7OCk4KZmRWcFMzMrOCkYGZmBScFMzMrOCmYmVnBScHMzApOCmZmVnBSMDOzgpOCmZkVnBTMzKzgpGBmZgUnBTMzKzgpmJlZwUnBzMwKTgpmZlZwUjAzs4KTgpmZFZwUzMys4KRgZmaFfpcUJB0o6V5JSyXNanU8ZmZDyfBWB1AmaRjwQ+B9wArgFklzI2JJX79W26yr+rrKwrLZB1dWd09U1cb+0j4z63v9KikAewJLI+IBAEkXA9OBPk8KreCVtJn1d4qIVsdQkPSPwIER8ek8fiSwV0QcX5pnJjAzj74ZuLdJ4Y0BHmvSa7WC2zfwDfY2Dvb2QfPauGNEjK03ob/tKXQrIs4Gzm7260paGBFTm/26zeL2DXyDvY2DvX3QP9rY3w40rwQmlcYn5jIzM2uC/pYUbgEmS9pJ0kjgcGBui2MyMxsy+lX3UUS8KOl44LfAMODciFjc4rA6NL3LqsncvoFvsLdxsLcP+kEb+9WBZjMza63+1n1kZmYt5KRgZmaFIZsUJE2SdL2kJZIWSzohl4+WdK2k+/Lztrn8LZL+LOk5SV+sqavfXZqjr9rXWT39QV9+hnn6MEl/kXRls9tSTx9/R0dJukzSPZLulrRPK9pUE1Nftu9fch13SbpI0qataFOtXrTxE5LukHSnpD9J2rVUV3PWMxExJB/AeGD3PLwV8FdgZ+DbwKxcPgv4Vh5+LbAHcBrwxVI9w4D7gdcDI4HbgZ0HUfvq1tPq9vVlG0v1fQH4BXBlq9vW1+0D5gCfzsMjgVGDpX3ABOBBYLM8filwdKvb18s2vgPYNg8fBCzIw01bzwzZPYWIWBURt+bhdcDdpC/XdNIPiPx8aJ5ndUTcArxQU1VxaY6IeB7ouDRHS/VV+7qop+X68DNE0kTgYOCnTQi9IX3VPknbAO8BzsnzPR8Ra5vSiC705edHOpNyM0nDgc2BhysOvyG9aOOfImJNLr+J9F8taOJ6ZsgmhTJJbcBuwAJgXESsypMeAcZ1s/gEYHlpfAX9ZKXZYSPb11k9/UoftPG7wJeBDVXEt7E2sn07Ae3Az3L32E8lbVFVrL2xMe2LiJXA6cDfgFXAkxExr7Jge6kXbTwW+J883LT1zJBPCpK2BH4FnBgRT5WnRdpvG9Dn7PZV+7qqp9U2to2SDgFWR8Si6qLsvT74DIcDuwNnRcRuwNOkLot+oQ8+v21JW807AdsDW0j6ZEXh9kpP2yjpvaSk8JWmBZkN6aQgaQTpg7owIi7PxY9KGp+njwdWd1NNv700Rx+1r7N6+oU+auM7gQ9JWkbaLd9P0gUVhdwjfdS+FcCKiOjYw7uMlCRaro/adwDwYES0R8QLwOWkvvl+oadtlPQPpG7M6RHxeC5u2npmyCYFSSL1sd4dEWeUJs0FZuThGcAV3VTVLy/N0Vft66KeluurNkbEVyNiYkS0kT6/30VEy7c0+7B9jwDLJb05F+1PP7gcfR/+Bv8G7C1p81zn/qS++5braRsl7UBKakdGxF9L8zdvPVPF0euB8ADeRdpluwO4LT+mAdsB84H7gOuA0Xn+15G2uJ4C1ubhrfO0aaSzCu4H/rXVbevL9nVWT6vb19efYanOfek/Zx/15Xd0CrAw1/Ub8hkug6h9XwfuAe4Czgc2aXX7etnGnwJrSvMuLNXVlPWML3NhZmaFIdt9ZGZmr+akYGZmBScFMzMrOCmYmVnBScHMzApOCmY9oORGSQeVyj4q6ZpWxmXWV3xKqlkPSXob8EvSdWyGA38BDoyI+3tR1/CIeLGPQzTrNScFs16Q9G3SNYS2yM87Am8DRgCnRMQV+QJo5+d5AI6PiD9J2hc4lfQnpbdExJuaG71Z55wUzHohX2X0VuB54EpgcURcIGkUcDNpLyKADRHxrKTJwEURMTUnhauAt0XEg61pgVl9w1sdgNlAFBFPS7oEWA8cBnywdDewTYEdSNf0/4GkKcBLQHmP4GYnBOuPnBTMem9Dfgj4SETcW54o6RTgUWBX0kkdz5YmP92kGM16xGcfmW283wKfz1fERNJuuXwbYFVEbACOJN1S0axfc1Iw23inkg4w3yFpcR4H+BEwQ9LtwFvw3oENAD7QbGZmBe8pmJlZwUnBzMwKTgpmZlZwUjAzs4KTgpmZFZwUzMys4KRgZmaF/w/Hf+xhzpMjuAAAAABJRU5ErkJggg==\n",
	"text/plain": [
	"<Figure size 432x288 with 1 Axes>"
	]
	},
	"metadata": {
	"tags": [],
	"needs_background": "light"
	}
	}
	]
	},
	{
	"cell_type": "code",
	"metadata": {
	"id": "B5rvhXMo5aOf",
	"colab_type": "code",
	"colab": {}
	},
	"source": [
	""
	],
	"execution_count": 0,
	"outputs": []
	}
	]
	}