2V_2021_vs_Plebiscito_1988.ipynb

2v_2021_vs_plebiscito_1988.ipynb

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        "import numpy as np\n",
        "import pandas as pd\n",
        "import matplotlib.pyplot as plt\n",
        "plt.rcParams.update({'xtick.labelsize' : 15,\n",
        "                     'ytick.labelsize' : 15})"
      ]
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    {
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      "source": [
        "df_raw = pd.read_csv(\"https://raw.githubusercontent.com/alonsosilvaallende/COVID-19/master/data/Eleccion_presidencial_2021_por_comuna.csv\", header=1, thousands=\".\")\n",
        "df_raw.head(3)"
      ],
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              "  Unnamed: 0   Unnamed: 1 Unnamed: 2  ...      No  Nulos y en blanco  Notas\n",
              "0          5    Algarrobo       5602  ...  1172.0               80.0    NaN\n",
              "1         13        Alhué      13502  ...  1079.0               67.0    NaN\n",
              "2          8  Alto Biobío       8314  ...     NaN                NaN    NaN\n",
              "\n",
              "[3 rows x 48 columns]"
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      "source": [
        "df_RM = df_raw[df_raw['Unnamed: 0'] == '13']\n",
        "df_RM.head(3)"
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              "      <td>481</td>\n",
              "      <td>132</td>\n",
              "      <td>40116</td>\n",
              "      <td>253</td>\n",
              "      <td>253</td>\n",
              "      <td>26268</td>\n",
              "      <td>20392</td>\n",
              "      <td>46660</td>\n",
              "      <td>358</td>\n",
              "      <td>105</td>\n",
              "      <td>47123</td>\n",
              "      <td>85</td>\n",
              "      <td>85</td>\n",
              "      <td>75070</td>\n",
              "      <td>7412</td>\n",
              "      <td>2181</td>\n",
              "      <td>664</td>\n",
              "      <td>3900</td>\n",
              "      <td>667</td>\n",
              "      <td>9787</td>\n",
              "      <td>6230</td>\n",
              "      <td>3557</td>\n",
              "      <td>17199</td>\n",
              "      <td>275</td>\n",
              "      <td>22</td>\n",
              "      <td>17496</td>\n",
              "      <td>33238</td>\n",
              "      <td>7166</td>\n",
              "      <td>124</td>\n",
              "      <td>59</td>\n",
              "      <td>14148.0</td>\n",
              "      <td>12753.0</td>\n",
              "      <td>643.0</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23</th>\n",
              "      <td>13</td>\n",
              "      <td>Calera de Tango</td>\n",
              "      <td>13403</td>\n",
              "      <td>67</td>\n",
              "      <td>67</td>\n",
              "      <td>22524</td>\n",
              "      <td>2586</td>\n",
              "      <td>3596</td>\n",
              "      <td>1067</td>\n",
              "      <td>1693</td>\n",
              "      <td>115</td>\n",
              "      <td>693</td>\n",
              "      <td>754</td>\n",
              "      <td>10504</td>\n",
              "      <td>59</td>\n",
              "      <td>40</td>\n",
              "      <td>10603</td>\n",
              "      <td>67</td>\n",
              "      <td>67</td>\n",
              "      <td>7141</td>\n",
              "      <td>7135</td>\n",
              "      <td>14276</td>\n",
              "      <td>107</td>\n",
              "      <td>45</td>\n",
              "      <td>14428</td>\n",
              "      <td>34</td>\n",
              "      <td>34</td>\n",
              "      <td>22134</td>\n",
              "      <td>3090</td>\n",
              "      <td>939</td>\n",
              "      <td>370</td>\n",
              "      <td>1572</td>\n",
              "      <td>209</td>\n",
              "      <td>2902</td>\n",
              "      <td>2026</td>\n",
              "      <td>876</td>\n",
              "      <td>5992</td>\n",
              "      <td>88</td>\n",
              "      <td>13</td>\n",
              "      <td>6093</td>\n",
              "      <td>9352</td>\n",
              "      <td>3340</td>\n",
              "      <td>41</td>\n",
              "      <td>17</td>\n",
              "      <td>3431.0</td>\n",
              "      <td>2709.0</td>\n",
              "      <td>113.0</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-658958e7-f17e-4a31-a5f0-19aa32fc6226')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-658958e7-f17e-4a31-a5f0-19aa32fc6226 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-658958e7-f17e-4a31-a5f0-19aa32fc6226');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ],
            "text/plain": [
              "   Unnamed: 0       Unnamed: 1 Unnamed: 2  ...       No  Nulos y en blanco  Notas\n",
              "1          13            Alhué      13502  ...   1079.0               67.0    NaN\n",
              "14         13             Buin      13402  ...  12753.0              643.0    NaN\n",
              "23         13  Calera de Tango      13403  ...   2709.0              113.0    NaN\n",
              "\n",
              "[3 rows x 48 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 3
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import seaborn as sns\n",
        "\n",
        "sns.set_style('white')\n",
        "sns.set_style('ticks')"
      ],
      "metadata": {
        "id": "selut1H8nMuu"
      },
      "execution_count": 4,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df_RM = df_RM.rename(columns={\"Unnamed: 1\":\"comunas\"})\n",
        "df_RM = df_RM.set_index(\"comunas\")\n",
        "df_RM = df_RM.fillna(0)"
      ],
      "metadata": {
        "id": "uvC3eShwqiaC"
      },
      "execution_count": 5,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df_RM[\"% Sí\"] = 100*df_RM[\"Sí\"]/(df_RM[\"Sí\"]+df_RM[\"No\"])\n",
        "df_RM[\"% Kast\"] = 100*df_RM[\"Kast.1\"]/(df_RM[\"Kast.1\"]+df_RM[\"Boric.1\"])"
      ],
      "metadata": {
        "id": "jwESfmHcqaAD"
      },
      "execution_count": 6,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "!pip install -q adjustText"
      ],
      "metadata": {
        "id": "e7DI9uKWt0dD"
      },
      "execution_count": 7,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "from adjustText import adjust_text"
      ],
      "metadata": {
        "id": "lqOK4OD4t3Vr"
      },
      "execution_count": 8,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# Web scrapping\n",
        "import requests\n",
        "from bs4 import BeautifulSoup\n",
        "import lxml.html as lh"
      ],
      "metadata": {
        "id": "3-zpex1awexW"
      },
      "execution_count": 9,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "url = \"https://es.wikipedia.org/wiki/Anexo:Comunas_de_Santiago_de_Chile#Conurbaci%C3%B3n_de_Santiago\""
      ],
      "metadata": {
        "id": "6RI32UKDwpYN"
      },
      "execution_count": 10,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "res = requests.get(url).text\n",
        "soup = BeautifulSoup(res,'lxml')\n",
        "soup.prettify()\n",
        "table = soup.findAll('table',{'class':'wikitable sortable'})[2].find_all('tr')[1:]"
      ],
      "metadata": {
        "id": "Zrr7T8ChwvT-"
      },
      "execution_count": 11,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df_aux = pd.DataFrame()\n",
        "df_aux[\"comunas\"] = [items.find_all(['th','td'])[0].text for items in table]\n",
        "df_aux[\"sector\"] = [items.find_all(['th','td'])[1].text for items in table]\n",
        "df_aux[\"poblacion\"] = [items.find_all(['th','td'])[2].text for items in table]\n",
        "df_aux[\"poblacion\"] = df_aux[\"poblacion\"].astype(int)\n",
        "df_aux = df_aux.set_index(\"comunas\")\n",
        "df_aux[\"% Sí\"] = df_RM[\"% Sí\"]\n",
        "df_aux[\"% Kast\"] = df_RM[\"% Kast\"]\n",
        "df_aux = df_aux.dropna()"
      ],
      "metadata": {
        "id": "Y4m3WXf6J9aT"
      },
      "execution_count": 12,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "fig, (ax1,ax2) = plt.subplots(2,1,sharex=True,figsize=(10,10), gridspec_kw={'height_ratios': [1, 5]})\n",
        "for i, sector in enumerate(sorted(df_aux[\"sector\"].unique())):\n",
        "  data_aux = df_aux[df_aux[\"sector\"]==sector]\n",
        "  ax2.scatter(data_aux[\"% Sí\"], data_aux[\"% Kast\"], color=f\"C{i}\", s=86017/1500, label=f\"{sector}\")\n",
        "  ax1.scatter(data_aux[\"% Sí\"], data_aux[\"% Kast\"], color=f\"C{i}\", s=data_aux[\"poblacion\"]/1500)\n",
        "  ax2.scatter(data_aux[\"% Sí\"], data_aux[\"% Kast\"], color=f\"C{i}\", s=data_aux[\"poblacion\"]/1500)\n",
        "ax1.axvline(50, color=\"gray\", linestyle=\"dashed\")\n",
        "ax2.axvline(50, color=\"gray\", linestyle=\"dashed\")\n",
        "ax2.axhline(50, color=\"gray\", linestyle=\"dashed\")\n",
        "ax1.plot(np.arange(30,66), np.arange(30,66), color=\"gray\", linestyle=\"dashed\")\n",
        "ax2.plot(np.arange(30,66), np.arange(30,66), color=\"gray\", linestyle=\"dashed\")\n",
        "\n",
        "ax1.set_ylim(72,85)\n",
        "ax2.set_ylim(25,52)\n",
        "texts1 = [ax1.annotate(txt, (df_aux[\"% Sí\"].iloc[i], df_aux[\"% Kast\"].iloc[i]), textcoords=\"offset points\", xytext=(-1,1), fontsize=\"large\") for i, txt in enumerate(df_aux.index)]\n",
        "texts2 = [ax2.annotate(txt, (df_aux[\"% Sí\"].iloc[i], df_aux[\"% Kast\"].iloc[i]), textcoords=\"offset points\", xytext=(-1,1), fontsize=\"large\") for i, txt in enumerate(df_aux.index)]\n",
        "adjust_text(texts1+texts2)\n",
        "# ticks\n",
        "ax1.set_yticks([10*i for i in np.arange(8,9)])\n",
        "ax1.set_yticklabels([f\"{10*i}%\" for i in np.arange(8,9)])\n",
        "ax2.set_xticks([5*i for i in np.arange(6,14)])\n",
        "ax2.set_xticklabels([f\"{5*i}%\" for i in np.arange(6,14)])\n",
        "ax2.set_yticks([10*i for i in np.arange(3,6)])\n",
        "ax2.set_yticklabels([f\"{10*i}%\" for i in np.arange(3,6)])\n",
        "\n",
        "# hide the spines between ax and ax2\n",
        "ax1.spines['bottom'].set_visible(False)\n",
        "ax2.spines['top'].set_visible(False)\n",
        "ax1.xaxis.tick_top()\n",
        "ax1.tick_params(labeltop='off')  # don't put tick labels at the top\n",
        "ax2.xaxis.tick_bottom()\n",
        "\n",
        "d = .015  # how big to make the diagonal lines in axes coordinates\n",
        "# arguments to pass to plot, just so we don't keep repeating them\n",
        "kwargs = dict(transform=ax1.transAxes, color='k', clip_on=False)\n",
        "ax1.plot((-d, +d), (-d, +d), **kwargs)        # top-left diagonal\n",
        "ax1.plot((1 - d, 1 + d), (-d, +d), **kwargs)  # top-right diagonal\n",
        "\n",
        "kwargs.update(transform=ax2.transAxes)  # switch to the bottom axes\n",
        "ax2.plot((-d, +d), (1 - d, 1 + d), **kwargs)  # bottom-left diagonal\n",
        "ax2.plot((1 - d, 1 + d), (1 - d, 1 + d), **kwargs)  # bottom-right diagonal\n",
        "ax2.legend()\n",
        "ax2.set_xlabel(\"Sí (Plebiscito 1988)\", fontsize=15)\n",
        "ax2.set_ylabel(\"Kast 2V (2021)\", fontsize=15)\n",
        "plt.annotate('Fuente: SERVEL\\nAutor: @alonsosilva', (0,0), (-60,-30), xycoords='axes fraction', textcoords='offset points', va='top', fontsize=15)\n",
        "plt.savefig('servel.svg', bbox_inches='tight', format='svg')\n",
        "# plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 659
        },
        "id": "sG0M0Irvprw_",
        "outputId": "20070407-3c20-40f0-aa0c-3541ff155c92"
      },
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x720 with 2 Axes>"
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from google.colab import files\n",
        "files.download(f\"servel.svg\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 17
        },
        "id": "bu3Eh9aJlf7N",
        "outputId": "0b5be3b6-481d-416e-c9a1-7122780dea3d"
      },
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "application/javascript": [
              "\n",
              "    async function download(id, filename, size) {\n",
              "      if (!google.colab.kernel.accessAllowed) {\n",
              "        return;\n",
              "      }\n",
              "      const div = document.createElement('div');\n",
              "      const label = document.createElement('label');\n",
              "      label.textContent = `Downloading \"${filename}\": `;\n",
              "      div.appendChild(label);\n",
              "      const progress = document.createElement('progress');\n",
              "      progress.max = size;\n",
              "      div.appendChild(progress);\n",
              "      document.body.appendChild(div);\n",
              "\n",
              "      const buffers = [];\n",
              "      let downloaded = 0;\n",
              "\n",
              "      const channel = await google.colab.kernel.comms.open(id);\n",
              "      // Send a message to notify the kernel that we're ready.\n",
              "      channel.send({})\n",
              "\n",
              "      for await (const message of channel.messages) {\n",
              "        // Send a message to notify the kernel that we're ready.\n",
              "        channel.send({})\n",
              "        if (message.buffers) {\n",
              "          for (const buffer of message.buffers) {\n",
              "            buffers.push(buffer);\n",
              "            downloaded += buffer.byteLength;\n",
              "            progress.value = downloaded;\n",
              "          }\n",
              "        }\n",
              "      }\n",
              "      const blob = new Blob(buffers, {type: 'application/binary'});\n",
              "      const a = document.createElement('a');\n",
              "      a.href = window.URL.createObjectURL(blob);\n",
              "      a.download = filename;\n",
              "      div.appendChild(a);\n",
              "      a.click();\n",
              "      div.remove();\n",
              "    }\n",
              "  "
            ],
            "text/plain": [
              "<IPython.core.display.Javascript object>"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "application/javascript": [
              "download(\"download_6f310843-9bd7-48d1-9304-06a0003beb7f\", \"servel.svg\", 128577)"
            ],
            "text/plain": [
              "<IPython.core.display.Javascript object>"
            ]
          },
          "metadata": {}
        }
      ]
    }
  ]
}