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analise_dados_saresp.ipynb
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"authorship_tag": "ABX9TyN5XXb4TkpQN0P/pWe86O3H",
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"<a href=\"https://colab.research.google.com/gist/royopa/8193f44b3d3c9a1ad1ca56a8c261b3b6/analise_dados_saresp.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
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{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "pk1QGHX7k7bD"
},
"outputs": [],
"source": [
"# importa bilbiotecas\n",
"import pandas as pd\n",
"import ssl\n",
"ssl._create_default_https_context = ssl._create_unverified_context"
]
},
{
"cell_type": "code",
"source": [
"# baixa apenas o arquivo de 2022 e coloca num dataframe pandas\n",
"file_path = 'https://dados.educacao.sp.gov.br/sites/default/files/MICRODADOS_SARESP_2022.csv'\n",
"df = pd.read_csv(file_path, sep=\";\")\n",
"df.head()"
],
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" CD_ALUNO NOMEDEP NomeDepBol \\\n",
"0 26191083 ESTADUAL-SE Rede Estadual \n",
"1 26191084 ESTADUAL-SE Rede Estadual \n",
"2 26191092 ESTADUAL-SE Rede Estadual \n",
"3 26191096 ESTADUAL-SE Rede Estadual \n",
"4 26191097 ESTADUAL-SE Rede Estadual \n",
"\n",
" RegiaoMetropolitana CDREDE DE \\\n",
"0 Região Metropolitana de Ribeirão Preto 20512 SERTAOZINHO \n",
"1 Região Metropolitana de São Paulo 10703 ITAPEVI \n",
"2 Região Metropolitana de São Paulo 10602 MAUA \n",
"3 Região Metropolitana do Vale do Paraíba e Lito... 20206 TAUBATE \n",
"4 Região Metropolitana do Vale do Paraíba e Lito... 20206 TAUBATE \n",
"\n",
" CODMUN MUN CODESC TIPOCLASSE ... profic_lp \\\n",
"0 543 PITANGUEIRAS 22640 0 ... 284,5 \n",
"1 206 BARUERI 290075 0 ... 234,2 \n",
"2 442 MAUA 7791 0 ... 302,2 \n",
"3 688 TAUBATE 49220 0 ... NaN \n",
"4 648 SAO LUIZ DO PARAITINGA 37874 0 ... NaN \n",
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" profic_mat profic_cie nivel_profic_lp nivel_profic_mat \\\n",
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"1 222 220,9 Abaixo do Básico Abaixo do Básico \n",
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"4 NaN 289,8 NaN NaN \n",
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" <td>10602</td>\n",
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" <td>Região Metropolitana do Vale do Paraíba e Lito...</td>\n",
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" <td>TAUBATE</td>\n",
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"metadata": {},
"execution_count": 12
}
]
},
{
"cell_type": "code",
"source": [
"# exibe as colunas do dataframe\n",
"df.columns"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "CJkwV1fwlme8",
"outputId": "4eefcafa-4e85-4905-d959-55b61c8887ff"
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"execution_count": null,
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{
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"data": {
"text/plain": [
"Index(['CD_ALUNO', 'NOMEDEP', 'NomeDepBol', 'RegiaoMetropolitana', 'CDREDE',\n",
" 'DE', 'CODMUN', 'MUN', 'CODESC', 'TIPOCLASSE', 'SERIE_ANO', 'TURMA',\n",
" 'CLASSE', 'TP_SEXO', 'DT_NASCIMENTO', 'PERIODO', 'NEC_ESP_1',\n",
" 'NEC_ESP_2', 'NEC_ESP_3', 'NEC_ESP_4', 'NEC_ESP_5', 'Tip_PROVA',\n",
" 'Tem_Nec', 'cad_prova_lp', 'cad_prova_mat', 'cad_prova_cie',\n",
" 'particip_lp', 'particip_mat', 'particip_cie', 'TOTAL_PONTO_LP',\n",
" 'TOTAL_PONTO_MAT', 'TOTAL_PONTO_CIE', 'porc_ACERT_lp', 'porc_ACERT_MAT',\n",
" 'porc_ACERT_CIE', 'profic_lp', 'profic_mat', 'profic_cie',\n",
" 'nivel_profic_lp', 'nivel_profic_mat', 'nivel_profic_cie',\n",
" 'classific_lp', 'classific_mat', 'classific_cie', 'validade'],\n",
" dtype='object')"
]
},
"metadata": {},
"execution_count": 13
}
]
},
{
"cell_type": "code",
"source": [
"# únicas séries disponíveis no arquivo de 2022\n",
"df['SERIE_ANO'].unique()"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 394
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"id": "GEhvHTssnAY6",
"outputId": "ed4a98b9-acff-4314-e09e-a3f6fd6e035e"
},
"execution_count": null,
"outputs": [
{
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"data": {
"text/plain": [
" CD_ALUNO CDREDE CODMUN CODESC TIPOCLASSE \\\n",
"count 1.020231e+06 1.020231e+06 1.020231e+06 1.020231e+06 1.020231e+06 \n",
"mean 2.920044e+07 1.603643e+04 3.694749e+02 2.765600e+05 4.317659e-01 \n",
"std 3.815891e+06 4.994657e+03 2.075620e+02 3.487569e+05 2.874535e+00 \n",
"min 5.442500e+04 1.010100e+04 1.000000e+02 1.200000e+01 0.000000e+00 \n",
"25% 2.623462e+07 1.040200e+04 1.820000e+02 1.921500e+04 0.000000e+00 \n",
"50% 2.896814e+07 2.020500e+04 3.450000e+02 4.866500e+04 0.000000e+00 \n",
"75% 3.252829e+07 2.041300e+04 5.670000e+02 4.364460e+05 0.000000e+00 \n",
"max 3.893356e+07 2.110200e+04 7.940000e+02 9.261030e+05 3.400000e+01 \n",
"\n",
" CLASSE NEC_ESP_1 NEC_ESP_2 NEC_ESP_3 NEC_ESP_4 ... \\\n",
"count 1.020231e+06 21608.000000 1692.000000 1083.000000 63.000000 ... \n",
"mean 2.613592e+08 11.938958 11.497045 10.489381 18.666667 ... \n",
"std 1.100771e+06 5.838648 7.082641 1.336474 4.004030 ... \n",
"min 2.600007e+08 1.000000 2.000000 4.000000 7.000000 ... \n",
"25% 2.606420e+08 10.000000 7.000000 11.000000 20.000000 ... \n",
"50% 2.610896e+08 11.000000 9.000000 11.000000 20.000000 ... \n",
"75% 2.614188e+08 11.000000 20.000000 11.000000 20.000000 ... \n",
"max 2.661986e+08 30.000000 30.000000 11.000000 23.000000 ... \n",
"\n",
" cad_prova_lp cad_prova_mat cad_prova_cie particip_lp particip_mat \\\n",
"count 1.020231e+06 1.020231e+06 808031.000000 1.020231e+06 1.020231e+06 \n",
"mean 1.552707e+01 1.552707e+01 13.487474 8.604698e-01 8.604698e-01 \n",
"std 9.502602e+00 9.502602e+00 7.508109 3.464991e-01 3.464991e-01 \n",
"min 1.000000e+00 1.000000e+00 1.000000 0.000000e+00 0.000000e+00 \n",
"25% 8.000000e+00 8.000000e+00 7.000000 1.000000e+00 1.000000e+00 \n",
"50% 1.500000e+01 1.500000e+01 13.000000 1.000000e+00 1.000000e+00 \n",
"75% 2.200000e+01 2.200000e+01 20.000000 1.000000e+00 1.000000e+00 \n",
"max 4.400000e+01 4.400000e+01 27.000000 1.000000e+00 1.000000e+00 \n",
"\n",
" particip_cie TOTAL_PONTO_LP TOTAL_PONTO_MAT TOTAL_PONTO_CIE \\\n",
"count 1.020231e+06 877878.000000 877878.000000 669012.000000 \n",
"mean 6.557456e-01 12.788988 11.027290 11.146081 \n",
"std 4.751247e-01 5.174653 4.837222 4.258847 \n",
"min 0.000000e+00 0.000000 0.000000 0.000000 \n",
"25% 0.000000e+00 9.000000 7.000000 8.000000 \n",
"50% 1.000000e+00 13.000000 11.000000 11.000000 \n",
"75% 1.000000e+00 17.000000 14.000000 14.000000 \n",
"max 1.000000e+00 24.000000 24.000000 24.000000 \n",
"\n",
" validade \n",
"count 1.020231e+06 \n",
"mean 9.823246e-01 \n",
"std 1.317688e-01 \n",
"min 0.000000e+00 \n",
"25% 1.000000e+00 \n",
"50% 1.000000e+00 \n",
"75% 1.000000e+00 \n",
"max 1.000000e+00 \n",
"\n",
"[8 rows x 22 columns]"
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" <td>1083.000000</td>\n",
" <td>63.000000</td>\n",
" <td>...</td>\n",
" <td>1.020231e+06</td>\n",
" <td>1.020231e+06</td>\n",
" <td>808031.000000</td>\n",
" <td>1.020231e+06</td>\n",
" <td>1.020231e+06</td>\n",
" <td>1.020231e+06</td>\n",
" <td>877878.000000</td>\n",
" <td>877878.000000</td>\n",
" <td>669012.000000</td>\n",
" <td>1.020231e+06</td>\n",
" </tr>\n",
" <tr>\n",
" <th>mean</th>\n",
" <td>2.920044e+07</td>\n",
" <td>1.603643e+04</td>\n",
" <td>3.694749e+02</td>\n",
" <td>2.765600e+05</td>\n",
" <td>4.317659e-01</td>\n",
" <td>2.613592e+08</td>\n",
" <td>11.938958</td>\n",
" <td>11.497045</td>\n",
" <td>10.489381</td>\n",
" <td>18.666667</td>\n",
" <td>...</td>\n",
" <td>1.552707e+01</td>\n",
" <td>1.552707e+01</td>\n",
" <td>13.487474</td>\n",
" <td>8.604698e-01</td>\n",
" <td>8.604698e-01</td>\n",
" <td>6.557456e-01</td>\n",
" <td>12.788988</td>\n",
" <td>11.027290</td>\n",
" <td>11.146081</td>\n",
" <td>9.823246e-01</td>\n",
" </tr>\n",
" <tr>\n",
" <th>std</th>\n",
" <td>3.815891e+06</td>\n",
" <td>4.994657e+03</td>\n",
" <td>2.075620e+02</td>\n",
" <td>3.487569e+05</td>\n",
" <td>2.874535e+00</td>\n",
" <td>1.100771e+06</td>\n",
" <td>5.838648</td>\n",
" <td>7.082641</td>\n",
" <td>1.336474</td>\n",
" <td>4.004030</td>\n",
" <td>...</td>\n",
" <td>9.502602e+00</td>\n",
" <td>9.502602e+00</td>\n",
" <td>7.508109</td>\n",
" <td>3.464991e-01</td>\n",
" <td>3.464991e-01</td>\n",
" <td>4.751247e-01</td>\n",
" <td>5.174653</td>\n",
" <td>4.837222</td>\n",
" <td>4.258847</td>\n",
" <td>1.317688e-01</td>\n",
" </tr>\n",
" <tr>\n",
" <th>min</th>\n",
" <td>5.442500e+04</td>\n",
" <td>1.010100e+04</td>\n",
" <td>1.000000e+02</td>\n",
" <td>1.200000e+01</td>\n",
" <td>0.000000e+00</td>\n",
" <td>2.600007e+08</td>\n",
" <td>1.000000</td>\n",
" <td>2.000000</td>\n",
" <td>4.000000</td>\n",
" <td>7.000000</td>\n",
" <td>...</td>\n",
" <td>1.000000e+00</td>\n",
" <td>1.000000e+00</td>\n",
" <td>1.000000</td>\n",
" <td>0.000000e+00</td>\n",
" <td>0.000000e+00</td>\n",
" <td>0.000000e+00</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000e+00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>25%</th>\n",
" <td>2.623462e+07</td>\n",
" <td>1.040200e+04</td>\n",
" <td>1.820000e+02</td>\n",
" <td>1.921500e+04</td>\n",
" <td>0.000000e+00</td>\n",
" <td>2.606420e+08</td>\n",
" <td>10.000000</td>\n",
" <td>7.000000</td>\n",
" <td>11.000000</td>\n",
" <td>20.000000</td>\n",
" <td>...</td>\n",
" <td>8.000000e+00</td>\n",
" <td>8.000000e+00</td>\n",
" <td>7.000000</td>\n",
" <td>1.000000e+00</td>\n",
" <td>1.000000e+00</td>\n",
" <td>0.000000e+00</td>\n",
" <td>9.000000</td>\n",
" <td>7.000000</td>\n",
" <td>8.000000</td>\n",
" <td>1.000000e+00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>50%</th>\n",
" <td>2.896814e+07</td>\n",
" <td>2.020500e+04</td>\n",
" <td>3.450000e+02</td>\n",
" <td>4.866500e+04</td>\n",
" <td>0.000000e+00</td>\n",
" <td>2.610896e+08</td>\n",
" <td>11.000000</td>\n",
" <td>9.000000</td>\n",
" <td>11.000000</td>\n",
" <td>20.000000</td>\n",
" <td>...</td>\n",
" <td>1.500000e+01</td>\n",
" <td>1.500000e+01</td>\n",
" <td>13.000000</td>\n",
" <td>1.000000e+00</td>\n",
" <td>1.000000e+00</td>\n",
" <td>1.000000e+00</td>\n",
" <td>13.000000</td>\n",
" <td>11.000000</td>\n",
" <td>11.000000</td>\n",
" <td>1.000000e+00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>75%</th>\n",
" <td>3.252829e+07</td>\n",
" <td>2.041300e+04</td>\n",
" <td>5.670000e+02</td>\n",
" <td>4.364460e+05</td>\n",
" <td>0.000000e+00</td>\n",
" <td>2.614188e+08</td>\n",
" <td>11.000000</td>\n",
" <td>20.000000</td>\n",
" <td>11.000000</td>\n",
" <td>20.000000</td>\n",
" <td>...</td>\n",
" <td>2.200000e+01</td>\n",
" <td>2.200000e+01</td>\n",
" <td>20.000000</td>\n",
" <td>1.000000e+00</td>\n",
" <td>1.000000e+00</td>\n",
" <td>1.000000e+00</td>\n",
" <td>17.000000</td>\n",
" <td>14.000000</td>\n",
" <td>14.000000</td>\n",
" <td>1.000000e+00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>max</th>\n",
" <td>3.893356e+07</td>\n",
" <td>2.110200e+04</td>\n",
" <td>7.940000e+02</td>\n",
" <td>9.261030e+05</td>\n",
" <td>3.400000e+01</td>\n",
" <td>2.661986e+08</td>\n",
" <td>30.000000</td>\n",
" <td>30.000000</td>\n",
" <td>11.000000</td>\n",
" <td>23.000000</td>\n",
" <td>...</td>\n",
" <td>4.400000e+01</td>\n",
" <td>4.400000e+01</td>\n",
" <td>27.000000</td>\n",
" <td>1.000000e+00</td>\n",
" <td>1.000000e+00</td>\n",
" <td>1.000000e+00</td>\n",
" <td>24.000000</td>\n",
" <td>24.000000</td>\n",
" <td>24.000000</td>\n",
" <td>1.000000e+00</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>8 rows × 22 columns</p>\n",
"</div>\n",
" <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-ac3c7185-5a2e-4564-9f6d-5ef535db83ee')\"\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-ac3c7185-5a2e-4564-9f6d-5ef535db83ee 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-ac3c7185-5a2e-4564-9f6d-5ef535db83ee');\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",
" "
]
},
"metadata": {},
"execution_count": 15
}
]
},
{
"cell_type": "code",
"source": [],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "kFztpf8InCkD",
"outputId": "14472ad8-a770-4fa5-813d-0d92bbaca40f"
},
"execution_count": null,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"array(['EM-3ª série', '9º Ano EF', '5º Ano EF', '2º Ano EF', '3º Ano EF'],\n",
" dtype=object)"
]
},
"metadata": {},
"execution_count": 18
}
]
},
{
"cell_type": "code",
"source": [],
"metadata": {
"id": "00NJfhmRnmZA"
},
"execution_count": null,
"outputs": []
}
]
}
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