enem_colaboratory.ipynb

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    "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": "3.8.11"
    },
    "colab": {
      "name": "07_csvp_altair.ipynb",
      "provenance": [],
      "include_colab_link": true
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/pauloneves/educacao/blob/master/enem_colaboratory.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "7b1593f4-b288-49fe-9a5d-99727a03e70c"
      },
      "source": [
        "import altair as alt\n",
        "import pandas as pd\n",
        "from pathlib import Path"
      ],
      "id": "7b1593f4-b288-49fe-9a5d-99727a03e70c",
      "execution_count": 42,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "24b5a8c7-518a-4594-84bc-a454664bad7c"
      },
      "source": [
        "\n",
        "CO_MUN = 3304557  # Rio de Janeiro\n",
        "CO_UF_RIO = 33  # RJ\n",
        "\n",
        "MIN_ALUNOS = 30  # Mínimo de alunos fazendo Enem para considerar na análise\n",
        "NUM_MELHORES = 60\n",
        "ANO_ULT = 2019  # último ano a processar"
      ],
      "id": "24b5a8c7-518a-4594-84bc-a454664bad7c",
      "execution_count": 43,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 17
        },
        "id": "LQ6Gq0HAsUoi",
        "outputId": "85421afe-8b6b-4909-d590-b744b9327757"
      },
      "source": [
        "%%html\n",
        "<style>\n",
        "@import url('https://fonts.googleapis.com/css?family=Lato');\n",
        "</style>"
      ],
      "id": "LQ6Gq0HAsUoi",
      "execution_count": 44,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "<style>\n",
              "@import url('https://fonts.googleapis.com/css?family=Lato');\n",
              "</style>"
            ],
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "_I8MfzkaspCx",
        "outputId": "f08f12f9-e87e-47d6-c0ba-f0e5dd0fc191"
      },
      "source": [
        "def urban_theme():\n",
        "    markColor = \"#1696d2\"\n",
        "    axisColor = \"#000000\"\n",
        "    backgroundColor = \"#FFFFFF\"\n",
        "    font = \"Lato\"\n",
        "    labelFont = \"Lato\"\n",
        "    sourceFont = \"Lato\"\n",
        "    gridColor = \"#DEDDDD\"\n",
        "    main_palette = [\"#1696d2\", \n",
        "                    \"#d2d2d2\",\n",
        "                    \"#000000\", \n",
        "                    \"#fdbf11\", \n",
        "                    \"#ec008b\", \n",
        "                    \"#55b748\", \n",
        "                    \"#5c5859\", \n",
        "                    \"#db2b27\", \n",
        "                   ]\n",
        "    sequential_palette = [\"#cfe8f3\", \n",
        "                          \"#a2d4ec\", \n",
        "                          \"#73bfe2\", \n",
        "                          \"#46abdb\", \n",
        "                          \"#1696d2\", \n",
        "                          \"#12719e\", \n",
        "                         ]\n",
        "    return {\n",
        "        \"width\": 685,\n",
        "        \"height\": 380,   \n",
        "#        \"autosize\": \"fit\",\n",
        "        \"config\": {\n",
        "            \"title\": {\n",
        "                \"anchor\": \"start\",\n",
        "                \"fontSize\": 18,\n",
        "                \"font\": font,\n",
        "                \"fontColor\": \"#000000\"\n",
        "            },\n",
        "            \"axisX\": {\n",
        "               \"domain\": True,\n",
        "               \"domainColor\": axisColor,\n",
        "               \"domainWidth\": 1,\n",
        "               \"grid\": False,\n",
        "               \"labelFontSize\": 12,\n",
        "               \"labelFont\": labelFont,\n",
        "               \"labelAngle\": 0,\n",
        "               \"tickColor\": axisColor,\n",
        "               \"tickSize\": 5,\n",
        "               \"titleFontSize\": 12,\n",
        "               \"titlePadding\": 10,\n",
        "               \"titleFont\": font,\n",
        "               \"title\": \"\",\n",
        "           },\n",
        "           \"axisY\": {\n",
        "               \"domain\": False,\n",
        "               \"grid\": True,\n",
        "               \"gridColor\": gridColor,\n",
        "               \"gridWidth\": 1,\n",
        "               \"labelFontSize\": 12,\n",
        "               \"labelFont\": labelFont,\n",
        "               \"labelPadding\": 8,\n",
        "               \"ticks\": False,\n",
        "               \"titleFontSize\": 12,\n",
        "               \"titlePadding\": 10,\n",
        "               \"titleFont\": font,\n",
        "               \"titleAngle\": 0,\n",
        "               \"titleY\": -10,\n",
        "               \"titleX\": 18,\n",
        "           },\n",
        "           \"background\": backgroundColor,\n",
        "           \"legend\": {\n",
        "               \"labelFontSize\": 12,\n",
        "               \"labelFont\": labelFont,\n",
        "               \"symbolSize\": 100,\n",
        "               \"symbolType\": \"square\",\n",
        "               \"titleFontSize\": 12,\n",
        "               \"titlePadding\": 10,\n",
        "               \"titleFont\": font,\n",
        "               \"title\": \"\",\n",
        "               \"orient\": \"top-left\",\n",
        "               \"offset\": 0,\n",
        "           },\n",
        "           \"view\": {\n",
        "               \"stroke\": \"transparent\",\n",
        "           },\n",
        "           \"range\": {\n",
        "               \"category\": main_palette,\n",
        "               \"diverging\": sequential_palette,\n",
        "           },\n",
        "           \"area\": {\n",
        "               \"fill\": markColor,\n",
        "           },\n",
        "           \"line\": {\n",
        "               \"color\": markColor,\n",
        "               \"stroke\": markColor,\n",
        "               \"strokewidth\": 5,\n",
        "           },\n",
        "           \"trail\": {\n",
        "               \"color\": markColor,\n",
        "               \"stroke\": markColor,\n",
        "               \"strokeWidth\": 0,\n",
        "               \"size\": 1,\n",
        "           },\n",
        "           \"path\": {\n",
        "               \"stroke\": markColor,\n",
        "               \"strokeWidth\": 0.5,\n",
        "           },\n",
        "           \"point\": {\n",
        "               \"filled\": True,\n",
        "           },\n",
        "           \"text\": {\n",
        "               \"font\": sourceFont,\n",
        "               \"color\": markColor,\n",
        "               \"fontSize\": 11,\n",
        "               \"align\": \"right\",\n",
        "               \"fontWeight\": 400,\n",
        "               \"size\": 11,\n",
        "           }, \n",
        "           \"bar\": {\n",
        "                \"size\": 40,\n",
        "                \"binSpacing\": 1,\n",
        "                \"continuousBandSize\": 30,\n",
        "                \"discreteBandSize\": 30,\n",
        "                \"fill\": markColor,\n",
        "                \"stroke\": False,\n",
        "            }, \n",
        "       },\n",
        "    }\n",
        "    \n",
        "    \n",
        "import altair as alt\n",
        "alt.themes.register(\"my_custom_theme\", urban_theme)\n",
        "alt.themes.enable(\"my_custom_theme\")"
      ],
      "id": "_I8MfzkaspCx",
      "execution_count": 45,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "ThemeRegistry.enable('my_custom_theme')"
            ]
          },
          "metadata": {},
          "execution_count": 45
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "QGJ0UPRrkVP3"
      },
      "source": [
        "COLABORATORY = True\n",
        "\n",
        "if COLABORATORY and 'dados_dir' not in vars(): \n",
        "  from google.colab import drive\n",
        "  drive.mount('/drive')\n",
        "\n",
        "if COLABORATORY:\n",
        "  dados_dir = Path('/drive/MyDrive/Colab Notebooks/educacao/')\n",
        "else:\n",
        "  dados_dir = Path('./dados')"
      ],
      "id": "QGJ0UPRrkVP3",
      "execution_count": 46,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "1f7ae5b4-7c12-416a-bf80-2a01830d4c92"
      },
      "source": [
        "df_turmas_rio = pd.read_feather(dados_dir / \"turmas_rio.feather\")"
      ],
      "id": "1f7ae5b4-7c12-416a-bf80-2a01830d4c92",
      "execution_count": 47,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "2f404ff5-da70-4005-9e53-5dccfbfbcfe2"
      },
      "source": [
        "ANO_ULT = df_turmas_rio.ano.max()"
      ],
      "id": "2f404ff5-da70-4005-9e53-5dccfbfbcfe2",
      "execution_count": 48,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "a8f590f0-3816-4e7b-a75e-b0dc81f615ce"
      },
      "source": [
        "em_etapas = tuple(range(25, 39))  # escolas normais devem ter só 25-27\n",
        "\n"
      ],
      "id": "a8f590f0-3816-4e7b-a75e-b0dc81f615ce",
      "execution_count": 49,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "88de82f3-7c21-45b7-a31d-9f7283f76370"
      },
      "source": [
        "df_enem = pd.read_feather(dados_dir / \"enem_anos.feather\")"
      ],
      "id": "88de82f3-7c21-45b7-a31d-9f7283f76370",
      "execution_count": 55,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "PcNFNo1-uCzA"
      },
      "source": [
        "df_medio_alunos = (df_turmas_rio.loc[df_turmas_rio.id_etapa.isin(em_etapas), \n",
        "                                     [\"ano\", \"id_escola\", \"id_etapa\", \"num_matriculas\"]]\n",
        "                   .groupby([ \"id_escola\", \"ano\", \"id_etapa\"])\n",
        "                   .aggregate(num_matriculas=(\"num_matriculas\", sum), num_turmas=(\"num_matriculas\", \"count\"))\n",
        "                   .rename({25:'1º', 26: '2º', 27: '3º'})\n",
        "                   .reset_index()\n",
        "                   .rename(columns={'id_etapa': 'Série'})\n",
        "                   )#.unstack()['num_matriculas'].rename(columns={25:'1º ano', 26: '2º ano', 27: '3º ano'}).reset_index()\n"
      ],
      "id": "PcNFNo1-uCzA",
      "execution_count": 76,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "_Xmr9JvntHLp"
      },
      "source": [
        "df_medio = df_turmas_rio[df_turmas_rio.id_etapa.isin(em_etapas)]\n"
      ],
      "id": "_Xmr9JvntHLp",
      "execution_count": 77,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "FKyBgNsF2Ipp"
      },
      "source": [
        "num_escolas = NUM_MELHORES"
      ],
      "id": "FKyBgNsF2Ipp",
      "execution_count": 78,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "N2F6lCeZxiqE"
      },
      "source": [
        "df_enem2 = df_enem[:num_escolas].rename(columns={'CO_ESCOLA': 'id_escola'})\n",
        "df_notas = df_enem.loc[df_enem.CO_ESCOLA.isin(df_enem2.id_escola), :].rename(columns={'CO_ESCOLA': 'id_escola'})\n",
        "df_notas_melt= (df_notas.set_index(['id_escola', 'Ano' ]) # primeiro cria chave com null in valores inexistentes\n",
        "                .reindex(pd.MultiIndex.from_product([df_notas.id_escola.unique(), df_notas.Ano.unique()], names=['id_escola', 'Ano']))\n",
        "                .reset_index()\n",
        "                .melt(\n",
        "                  id_vars=[\"Ano\", 'id_escola'],\n",
        "                  value_vars=[c for c in df_enem.columns if c.startswith(\"nota_\") and not c.endswith('80')],\n",
        "                  var_name=\"Matéria\",\n",
        "                  value_name=\"Nota\",\n",
        "              ))\n"
      ],
      "id": "N2F6lCeZxiqE",
      "execution_count": 79,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "TeEnFwcVb0BN"
      },
      "source": [
        "num_anos = 5\n",
        "df_medio_alunos2 = df_medio_alunos[df_medio_alunos.id_escola.isin(df_enem2.id_escola) & (df_medio_alunos.ano > (df_medio_alunos.ano.max() - num_anos))].copy()\n",
        "df_medio_alunos2[\"Período\"] = (\n",
        "    df_medio_alunos2[\"ano\"].astype(str) + \"–\" + (df_medio_alunos2[\"ano\"] + 2).astype(str)\n",
        ")\n",
        "alunos_index_names = ['id_escola', 'Período', 'Série']\n",
        "new_alunos2_index = pd.MultiIndex.from_product([df_medio_alunos2.id_escola.unique(), \n",
        "                                                df_medio_alunos2.Período.unique(), \n",
        "                                                ['1º', '2º', '3º']], \n",
        "                                               names=alunos_index_names)\n",
        "\n",
        "df_medio_alunos2 = df_medio_alunos2.set_index(alunos_index_names).reindex(new_alunos2_index).reset_index()\n",
        "\n"
      ],
      "id": "TeEnFwcVb0BN",
      "execution_count": 80,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "bmpSCE0_CpbJ"
      },
      "source": [
        "def enem_ajusta_cols(df):\n",
        "    return df.rename(\n",
        "        columns={\n",
        "            \"NU_ANO\": \"Ano\",\n",
        "            \"NU_NOTA_CN\": \"nota_ciências\",\n",
        "            \"NU_NOTA_CH\": \"nota_humanas\",\n",
        "            \"NU_NOTA_LC\": \"nota_português\",\n",
        "            \"NU_NOTA_MT\": \"nota_matemática\",\n",
        "            \"NU_NOTA_REDACAO\": \"nota_redação\",\n",
        "            'CO_ESCOLA': 'id_escola'\n",
        "        }\n",
        "    )\n"
      ],
      "id": "bmpSCE0_CpbJ",
      "execution_count": 82,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "iDzDRI7L03Dq"
      },
      "source": [
        "df_enem_bins = enem_ajusta_cols(pd.read_feather(dados_dir / 'enem_rio_bins.feather'))"
      ],
      "id": "iDzDRI7L03Dq",
      "execution_count": 83,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "s-5IQjzI2uzC",
        "outputId": "41a5ebbc-7613-49d0-ef11-87ca1c959280"
      },
      "source": [
        "df_enem_bins2 = df_enem_bins.loc[df_enem_bins.id_escola.isin(df_enem2.id_escola), :]\n",
        "df_enem_bins2.columns"
      ],
      "id": "s-5IQjzI2uzC",
      "execution_count": 84,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Index(['id_escola', 'nota_ciências', 'nota_humanas', 'nota_português',\n",
              "       'nota_matemática', 'nota_redação', 'nota_final', 'bins', 'bin_label'],\n",
              "      dtype='object')"
            ]
          },
          "metadata": {},
          "execution_count": 84
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ccjgAvAEVI4c"
      },
      "source": [
        "## Visualização"
      ],
      "id": "ccjgAvAEVI4c"
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "BxI-rbsN8HvD"
      },
      "source": [
        "brush = alt.selection_single(fields=['id_escola'], \n",
        "                             nearest=True, \n",
        "                             init={'id_escola': CO_SAO_VICENTE})"
      ],
      "id": "BxI-rbsN8HvD",
      "execution_count": 85,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 611
        },
        "id": "h6uQSFRtJvIg",
        "outputId": "4ec4bb66-18fc-421b-c98d-fdc04a00c30e"
      },
      "source": [
        "\n",
        "base = alt.Chart(df_enem2, title=alt.TitleParams(\"Medianas da nota final (clique para selecionar uma escola)\", subtitle=[\"Redação tem peso 2\", \"Área cinza mostra o 80º percentil\"]))\n",
        "\n",
        "median = (base.mark_bar(size=30, color='cornflowerblue')\n",
        "          .encode(x=alt.X(\"id_escola:N\", sort=alt.SortField(\"rank\"), axis=alt.Axis(labelFontSize=10)), \n",
        "                  y=alt.Y(\"nota_final:Q\", axis=alt.Axis(title=None)), \n",
        "                  tooltip=['nota_final', 'nota_final_perc80', 'rank', 'id_escola'],\n",
        "                  opacity=alt.condition(brush, alt.value(1), alt.value(.6)))\n",
        " \n",
        ").add_selection(brush)\n",
        "\n",
        "perc80 = (base.mark_bar(size=30,  color='lightgray', opacity=.8)\n",
        "          .encode(x=alt.X(\"id_escola:N\", sort=alt.SortField(\"rank\")), \n",
        "                  y=\"nota_final_perc80:Q\")\n",
        " \n",
        ")\n",
        "#alt.data_transformers.enable(max_rows=None)\n",
        "\n",
        "materias = (alt.Chart(df_notas_melt)\n",
        "           .mark_line(point=True)\n",
        "           .encode(\n",
        "                x=alt.X(\"Ano:O\", scale=alt.Scale(padding=0.05)),\n",
        "                y=alt.Y(\"Nota\", scale=alt.Scale(domain=[500, 1000]), axis=alt.Axis(title=None)),\n",
        "                color=alt.Color(\"Matéria\",legend=alt.Legend(orient='top'), scale=alt.Scale(scheme=\"tableau10\"), \n",
        "                                sort=['nota_final', 'nota_redação', 'nota_matemática', 'nota_português', 'nota_ciências','nota_humanas']),\n",
        "                tooltip=[\"Matéria\", \"Nota\",\"Ano\"]\n",
        "                )\n",
        "            #.transform_filter(alt.FieldEqualPredicate(field=\"id_escola\", equal=CO_SAO_BENTO))\n",
        "            .transform_filter(brush)\n",
        "            .properties(\n",
        "                width=500, title=\"Notas a cada ano\"\n",
        "            )\n",
        "           )\n",
        "\n",
        "nalunos = (alt.Chart(df_medio_alunos2)\n",
        "           .mark_line(point=True)\n",
        "           .encode(\n",
        "              x=alt.X(\"Série:O\", scale=alt.Scale(domain=['1º', '2º', '3º'], padding=0.05)),\n",
        "              y=alt.Y(\"num_matriculas:Q\", axis=alt.Axis(title=None), scale=alt.Scale(domain=[0,230])),\n",
        "              color=alt.Color(\"Período:O\", scale=alt.Scale(scheme='blues'), legend=alt.Legend(orient='top')), \n",
        "              tooltip=('Período', \"Série\", \"num_matriculas\")\n",
        "            ).transform_filter(brush)\n",
        "         ).properties(width=400, title=\"Nº matrículas por série\")\n",
        "\n",
        "notas_dist_width=400\n",
        "notas_dist = (\n",
        "    alt.Chart(df_enem_bins2)\n",
        "       .mark_bar(stroke='white', width=notas_dist_width//21)\n",
        "       .encode(x=\"bin_label:O\", \n",
        "               y='nota_final:Q',\n",
        "               tooltip=['nota_final', 'bins'])\n",
        "      .transform_filter(brush)\n",
        "      .properties(width=notas_dist_width, title=\"Histograma das notas\")\n",
        ")         \n",
        "\n",
        "alt.vconcat( \n",
        "    (perc80 + median).properties(width=alt.Step(45)).interactive(),\n",
        "    (materias.interactive() | nalunos.interactive() | notas_dist.interactive()).resolve_scale(color='independent')\n",
        ").configure_point(size=40)"
      ],
      "id": "h6uQSFRtJvIg",
      "execution_count": 86,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "alt.VConcatChart(...)"
            ],
            "text/html": [
              "\n",
              "<div id=\"altair-viz-8d89036cc5b145d88b41f43f73800fe9\"></div>\n",
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              "  (function(spec, embedOpt){\n",
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              "</script>"
            ]
          },
          "metadata": {},
          "execution_count": 86
        }
      ]
    }
  ]
}