diff --git a/material/Analise.ipynb b/material/Analise.ipynb new file mode 100644 index 0000000..11223b0 --- /dev/null +++ b/material/Analise.ipynb @@ -0,0 +1,3998 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 51, + "metadata": {}, + "outputs": [], + "source": [ + "import pandas as pd\n", + "import matplotlib.pyplot as plt\n", + "import seaborn as sns" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "df_1991 = pd.read_csv('IDH_1991.csv', encoding=\"latin1\", sep = ';')\n", + "df_2000 = pd.read_csv('IDH_2000.csv', encoding=\"latin1\", sep = ';')" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "RangeIndex: 126 entries, 0 to 125\n", + "Data columns (total 10 columns):\n", + " # Column Non-Null Count Dtype \n", + "--- ------ -------------- ----- \n", + " 0 Ordem segundo o IDH 126 non-null int64 \n", + " 1 Bairro ou grupo de bairros 126 non-null object\n", + " 2 Esperança de vida ao nascer (em anos) 126 non-null object\n", + " 3 Taxa de alfabetização de adultos (%) 126 non-null object\n", + " 4 Taxa bruta de frequência escolar (%) 126 non-null object\n", + " 5 Renda per capita (em R$ de 2000) 126 non-null object\n", + " 6 Índice de Longevidade (IDH-L) 126 non-null object\n", + " 7 Índice de Educação (IDH-E) 126 non-null object\n", + " 8 Índice de Renda (IDH-R) 126 non-null object\n", + " 9 Índice de Desenvolvimento Humano Municipal (IDH) 126 non-null object\n", + "dtypes: int64(1), object(9)\n", + "memory usage: 10.0+ KB\n" + ] + } + ], + "source": [ + "df_1991.info()" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "RangeIndex: 126 entries, 0 to 125\n", + "Data columns (total 10 columns):\n", + " # Column Non-Null Count Dtype \n", + "--- ------ -------------- ----- \n", + " 0 Ordem segundo o IDH 126 non-null int64 \n", + " 1 Bairro ou grupo de bairros 126 non-null object\n", + " 2 Esperança de vida ao nascer (em anos) 126 non-null object\n", + " 3 Taxa de alfabetização de adultos (%) 126 non-null object\n", + " 4 Taxa bruta de frequência escolar (%) 126 non-null object\n", + " 5 Renda per capita (em R$ de 2000) 126 non-null object\n", + " 6 Índice de Longevidade (IDH-L) 126 non-null object\n", + " 7 Índice de Educação (IDH-E) 126 non-null object\n", + " 8 Índice de Renda (IDH-R) 126 non-null object\n", + " 9 Índice de Desenvolvimento Humano Municipal (IDH) 126 non-null object\n", + "dtypes: int64(1), object(9)\n", + "memory usage: 10.0+ KB\n" + ] + } + ], + "source": [ + "df_2000.info()" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Ordem segundo o IDH 0\n", + "Bairro ou grupo de bairros 0\n", + "Esperança de vida ao nascer (em anos) 0\n", + "Taxa de alfabetização de adultos (%) 0\n", + "Taxa bruta de frequência escolar (%) 0\n", + "Renda per capita (em R$ de 2000) 0\n", + "Índice de Longevidade (IDH-L) 0\n", + "Índice de Educação (IDH-E) 0\n", + "Índice de Renda (IDH-R) 0\n", + "Índice de Desenvolvimento Humano Municipal (IDH) 0\n", + "dtype: int64" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df_1991.isnull().sum()" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Ordem segundo o IDH 0\n", + "Bairro ou grupo de bairros 0\n", + "Esperança de vida ao nascer (em anos) 0\n", + "Taxa de alfabetização de adultos (%) 0\n", + "Taxa bruta de frequência escolar (%) 0\n", + "Renda per capita (em R$ de 2000) 0\n", + "Índice de Longevidade (IDH-L) 0\n", + "Índice de Educação (IDH-E) 0\n", + "Índice de Renda (IDH-R) 0\n", + "Índice de Desenvolvimento Humano Municipal (IDH) 0\n", + "dtype: int64" + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df_2000.isnull().sum()" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [], + "source": [ + "df_1991 = df_1991.replace(',','.', regex=True)\n", + "df_2000 = df_2000.replace(',','.', regex=True)" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Ordem segundo o IDH int64\n", + "Bairro ou grupo de bairros object\n", + "Esperança de vida ao nascer (em anos) float64\n", + "Taxa de alfabetização de adultos (%) float64\n", + "Taxa bruta de frequência escolar (%) float64\n", + "Renda per capita (em R$ de 2000) float64\n", + "Índice de Longevidade (IDH-L) float64\n", + "Índice de Educação (IDH-E) float64\n", + "Índice de Renda (IDH-R) float64\n", + "Índice de Desenvolvimento Humano Municipal (IDH) float64\n", + "dtype: object\n" + ] + } + ], + "source": [ + "coluna_object = df_1991.select_dtypes(include=['object']).columns\n", + "coluna_object = coluna_object.drop(['Bairro ou grupo de bairros'])\n", + "for coluna in coluna_object:\n", + " df_1991[coluna] = pd.to_numeric(df_1991[coluna], errors='coerce')\n", + "print(df_1991.dtypes)" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Ordem segundo o IDH int64\n", + "Bairro ou grupo de bairros object\n", + "Esperança de vida ao nascer (em anos) float64\n", + "Taxa de alfabetização de adultos (%) float64\n", + "Taxa bruta de frequência escolar (%) float64\n", + "Renda per capita (em R$ de 2000) float64\n", + "Índice de Longevidade (IDH-L) float64\n", + "Índice de Educação (IDH-E) float64\n", + "Índice de Renda (IDH-R) float64\n", + "Índice de Desenvolvimento Humano Municipal (IDH) float64\n", + "dtype: object\n" + ] + } + ], + "source": [ + "coluna_object = df_2000.select_dtypes(include=['object']).columns\n", + "coluna_object = coluna_object.drop(['Bairro ou grupo de bairros'])\n", + "for coluna in coluna_object:\n", + " df_2000[coluna] = pd.to_numeric(df_2000[coluna], errors='coerce')\n", + "print(df_2000.dtypes)" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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Ordem segundo o IDHBairro ou grupo de bairrosEsperança de vida ao nascer (em anos)Taxa de alfabetização de adultos (%)Taxa bruta de frequência escolar (%)Renda per capita (em R$ de 2000)Índice de Longevidade (IDH-L)Índice de Educação (IDH-E)Índice de Renda (IDH-R)Índice de Desenvolvimento Humano Municipal (IDH)
01Gávea75.1197.25100.641796.100.8350.9821.0000.939
12Jardim Botânico73.6797.8195.241620.820.8110.9701.0000.927
23Ipanema74.0096.9893.951606.880.8170.9601.0000.925
34Leblon73.6797.4992.231589.110.8110.9571.0000.923
45Humaitá72.8097.93102.671422.010.7970.9860.9850.923
.................................
121122Rocinha65.1581.4954.47170.570.6690.7250.6310.675
122123Manguinhos62.3285.9262.98157.260.6220.7830.6170.674
123124Maré62.7183.3160.57156.260.6280.7570.6160.667
124125Complexo do Alemão62.3683.6056.52144.010.6230.7460.6020.657
125126Acari. Parque Colúmbia60.2986.2160.57147.170.5880.7770.6060.657
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" + ], + "text/plain": [ + " Ordem segundo o IDH Bairro ou grupo de bairros \\\n", + "0 1 Gávea \n", + "1 2 Jardim Botânico \n", + "2 3 Ipanema \n", + "3 4 Leblon \n", + "4 5 Humaitá \n", + ".. ... ... \n", + "121 122 Rocinha \n", + "122 123 Manguinhos \n", + "123 124 Maré \n", + "124 125 Complexo do Alemão \n", + "125 126 Acari. Parque Colúmbia \n", + "\n", + " Esperança de vida ao nascer (em anos) \\\n", + "0 75.11 \n", + "1 73.67 \n", + "2 74.00 \n", + "3 73.67 \n", + "4 72.80 \n", + ".. ... \n", + "121 65.15 \n", + "122 62.32 \n", + "123 62.71 \n", + "124 62.36 \n", + "125 60.29 \n", + "\n", + " Taxa de alfabetização de adultos (%) \\\n", + "0 97.25 \n", + "1 97.81 \n", + "2 96.98 \n", + "3 97.49 \n", + "4 97.93 \n", + ".. ... \n", + "121 81.49 \n", + "122 85.92 \n", + "123 83.31 \n", + "124 83.60 \n", + "125 86.21 \n", + "\n", + " Taxa bruta de frequência escolar (%) Renda per capita (em R$ de 2000) \\\n", + "0 100.64 1796.10 \n", + "1 95.24 1620.82 \n", + "2 93.95 1606.88 \n", + "3 92.23 1589.11 \n", + "4 102.67 1422.01 \n", + ".. ... ... \n", + "121 54.47 170.57 \n", + "122 62.98 157.26 \n", + "123 60.57 156.26 \n", + "124 56.52 144.01 \n", + "125 60.57 147.17 \n", + "\n", + " Índice de Longevidade (IDH-L) Índice de Educação (IDH-E) \\\n", + "0 0.835 0.982 \n", + "1 0.811 0.970 \n", + "2 0.817 0.960 \n", + "3 0.811 0.957 \n", + "4 0.797 0.986 \n", + ".. ... ... \n", + "121 0.669 0.725 \n", + "122 0.622 0.783 \n", + "123 0.628 0.757 \n", + "124 0.623 0.746 \n", + "125 0.588 0.777 \n", + "\n", + " Índice de Renda (IDH-R) Índice de Desenvolvimento Humano Municipal (IDH) \n", + "0 1.000 0.939 \n", + "1 1.000 0.927 \n", + "2 1.000 0.925 \n", + "3 1.000 0.923 \n", + "4 0.985 0.923 \n", + ".. ... ... \n", + "121 0.631 0.675 \n", + "122 0.617 0.674 \n", + "123 0.616 0.667 \n", + "124 0.602 0.657 \n", + "125 0.606 0.657 \n", + "\n", + "[126 rows x 10 columns]" + ] + }, + "execution_count": 10, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df_1991" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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Ordem segundo o IDHBairro ou grupo de bairrosEsperança de vida ao nascer (em anos)Taxa de alfabetização de adultos (%)Taxa bruta de frequência escolar (%)Renda per capita (em R$ de 2000)Índice de Longevidade (IDH-L)Índice de Educação (IDH-E)Índice de Renda (IDH-R)Índice de Desenvolvimento Humano Municipal (IDH)
01Gávea80.4598.08118.132139.560.9240.9871.0000.970
12Leblon79.4799.01105.182441.280.9080.9931.0000.967
23Jardim Guanabara80.4798.92111.151316.860.9240.9930.9720.963
34Ipanema78.6898.78107.982465.450.8950.9921.0000.962
45Lagoa77.9199.46115.262955.290.8820.9961.0000.959
.................................
121122Manguinhos66.3091.4869.64188.860.6880.8420.6480.726
122123Maré66.5889.4668.76187.250.6930.8260.6460.722
123124Acari. Parque Colúmbia63.9391.6879.44174.120.6490.8760.6340.720
124125Costa Barros63.9391.3474.09175.000.6490.8560.6350.713
125126Complexo do Alemão64.7989.0772.04177.310.6630.8340.6370.711
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countmeanstdmin25%50%75%max
Ordem segundo o IDH126.063.50000036.5171191.00032.2500063.500094.75000126.000
Esperança de vida ao nascer (em anos)126.067.8592063.59743557.04065.2250067.740070.5525075.390
Taxa de alfabetização de adultos (%)126.093.5956353.72815181.49091.9275094.405096.1175098.250
Taxa bruta de frequência escolar (%)126.079.33761910.57241954.47072.8675079.020086.18750103.500
Renda per capita (em R$ de 2000)126.0466.831587401.692442144.010233.12250327.9700497.227502277.530
Índice de Longevidade (IDH-L)126.00.7143020.0599210.5340.670250.71200.759500.840
Índice de Educação (IDH-E)126.00.8881980.0577110.7250.858250.89550.921750.988
Índice de Renda (IDH-R)126.00.7573730.1047110.6020.683000.73950.809001.000
Índice de Desenvolvimento Humano Municipal (IDH)126.00.7865950.0686750.6570.742250.78400.823000.939
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" + ], + "text/plain": [ + " count mean \\\n", + "Ordem segundo o IDH 126.0 63.500000 \n", + "Esperança de vida ao nascer (em anos) 126.0 67.859206 \n", + "Taxa de alfabetização de adultos (%) 126.0 93.595635 \n", + "Taxa bruta de frequência escolar (%) 126.0 79.337619 \n", + "Renda per capita (em R$ de 2000) 126.0 466.831587 \n", + "Índice de Longevidade (IDH-L) 126.0 0.714302 \n", + "Índice de Educação (IDH-E) 126.0 0.888198 \n", + "Índice de Renda (IDH-R) 126.0 0.757373 \n", + "Índice de Desenvolvimento Humano Municipal (IDH) 126.0 0.786595 \n", + "\n", + " std min \\\n", + "Ordem segundo o IDH 36.517119 1.000 \n", + "Esperança de vida ao nascer (em anos) 3.597435 57.040 \n", + "Taxa de alfabetização de adultos (%) 3.728151 81.490 \n", + "Taxa bruta de frequência escolar (%) 10.572419 54.470 \n", + "Renda per capita (em R$ de 2000) 401.692442 144.010 \n", + "Índice de Longevidade (IDH-L) 0.059921 0.534 \n", + "Índice de Educação (IDH-E) 0.057711 0.725 \n", + "Índice de Renda (IDH-R) 0.104711 0.602 \n", + "Índice de Desenvolvimento Humano Municipal (IDH) 0.068675 0.657 \n", + "\n", + " 25% 50% \\\n", + "Ordem segundo o IDH 32.25000 63.5000 \n", + "Esperança de vida ao nascer (em anos) 65.22500 67.7400 \n", + "Taxa de alfabetização de adultos (%) 91.92750 94.4050 \n", + "Taxa bruta de frequência escolar (%) 72.86750 79.0200 \n", + "Renda per capita (em R$ de 2000) 233.12250 327.9700 \n", + "Índice de Longevidade (IDH-L) 0.67025 0.7120 \n", + "Índice de Educação (IDH-E) 0.85825 0.8955 \n", + "Índice de Renda (IDH-R) 0.68300 0.7395 \n", + "Índice de Desenvolvimento Humano Municipal (IDH) 0.74225 0.7840 \n", + "\n", + " 75% max \n", + "Ordem segundo o IDH 94.75000 126.000 \n", + "Esperança de vida ao nascer (em anos) 70.55250 75.390 \n", + "Taxa de alfabetização de adultos (%) 96.11750 98.250 \n", + "Taxa bruta de frequência escolar (%) 86.18750 103.500 \n", + "Renda per capita (em R$ de 2000) 497.22750 2277.530 \n", + "Índice de Longevidade (IDH-L) 0.75950 0.840 \n", + "Índice de Educação (IDH-E) 0.92175 0.988 \n", + "Índice de Renda (IDH-R) 0.80900 1.000 \n", + "Índice de Desenvolvimento Humano Municipal (IDH) 0.82300 0.939 " + ] + }, + "execution_count": 12, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df_1991.describe().T" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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countmeanstdmin25%50%75%max
Ordem segundo o IDH126.063.50000036.5171191.00032.2500063.500094.75000126.000
Esperança de vida ao nascer (em anos)126.072.0576194.05798562.81069.4175072.320075.0275080.470
Taxa de alfabetização de adultos (%)126.095.9287302.38127587.90094.7850096.300097.5550099.460
Taxa bruta de frequência escolar (%)126.090.65222211.94570467.66082.3000088.595096.80250122.200
Renda per capita (em R$ de 2000)126.0621.834762539.892572174.120302.82500432.5450681.040002955.290
Índice de Longevidade (IDH-L)126.00.7843100.0676660.6300.740000.78850.833750.924
Índice de Educação (IDH-E)126.00.9353810.0442910.8180.905250.93850.974750.996
Índice de Renda (IDH-R)126.00.8006830.1012680.6340.726250.78600.862001.000
Índice de Desenvolvimento Humano Municipal (IDH)126.00.8400560.0673500.7110.798500.83400.891000.970
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" + ], + "text/plain": [ + " count mean \\\n", + "Ordem segundo o IDH 126.0 63.500000 \n", + "Esperança de vida ao nascer (em anos) 126.0 72.057619 \n", + "Taxa de alfabetização de adultos (%) 126.0 95.928730 \n", + "Taxa bruta de frequência escolar (%) 126.0 90.652222 \n", + "Renda per capita (em R$ de 2000) 126.0 621.834762 \n", + "Índice de Longevidade (IDH-L) 126.0 0.784310 \n", + "Índice de Educação (IDH-E) 126.0 0.935381 \n", + "Índice de Renda (IDH-R) 126.0 0.800683 \n", + "Índice de Desenvolvimento Humano Municipal (IDH) 126.0 0.840056 \n", + "\n", + " std min \\\n", + "Ordem segundo o IDH 36.517119 1.000 \n", + "Esperança de vida ao nascer (em anos) 4.057985 62.810 \n", + "Taxa de alfabetização de adultos (%) 2.381275 87.900 \n", + "Taxa bruta de frequência escolar (%) 11.945704 67.660 \n", + "Renda per capita (em R$ de 2000) 539.892572 174.120 \n", + "Índice de Longevidade (IDH-L) 0.067666 0.630 \n", + "Índice de Educação (IDH-E) 0.044291 0.818 \n", + "Índice de Renda (IDH-R) 0.101268 0.634 \n", + "Índice de Desenvolvimento Humano Municipal (IDH) 0.067350 0.711 \n", + "\n", + " 25% 50% \\\n", + "Ordem segundo o IDH 32.25000 63.5000 \n", + "Esperança de vida ao nascer (em anos) 69.41750 72.3200 \n", + "Taxa de alfabetização de adultos (%) 94.78500 96.3000 \n", + "Taxa bruta de frequência escolar (%) 82.30000 88.5950 \n", + "Renda per capita (em R$ de 2000) 302.82500 432.5450 \n", + "Índice de Longevidade (IDH-L) 0.74000 0.7885 \n", + "Índice de Educação (IDH-E) 0.90525 0.9385 \n", + "Índice de Renda (IDH-R) 0.72625 0.7860 \n", + "Índice de Desenvolvimento Humano Municipal (IDH) 0.79850 0.8340 \n", + "\n", + " 75% max \n", + "Ordem segundo o IDH 94.75000 126.000 \n", + "Esperança de vida ao nascer (em anos) 75.02750 80.470 \n", + "Taxa de alfabetização de adultos (%) 97.55500 99.460 \n", + "Taxa bruta de frequência escolar (%) 96.80250 122.200 \n", + "Renda per capita (em R$ de 2000) 681.04000 2955.290 \n", + "Índice de Longevidade (IDH-L) 0.83375 0.924 \n", + "Índice de Educação (IDH-E) 0.97475 0.996 \n", + "Índice de Renda (IDH-R) 0.86200 1.000 \n", + "Índice de Desenvolvimento Humano Municipal (IDH) 0.89100 0.970 " + ] + }, + "execution_count": 13, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df_2000.describe().T" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [], + "source": [ + "df_1991['Ano'] = 1991\n", + "df_2000['Ano'] = 2000" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": {}, + "outputs": [], + "source": [ + "df_idh = pd.concat([df_1991, df_2000])" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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Ordem segundo o IDHBairro ou grupo de bairrosEsperança de vida ao nascer (em anos)Taxa de alfabetização de adultos (%)Taxa bruta de frequência escolar (%)Renda per capita (em R$ de 2000)Índice de Longevidade (IDH-L)Índice de Educação (IDH-E)Índice de Renda (IDH-R)Índice de Desenvolvimento Humano Municipal (IDH)Ano
01Gávea75.1197.25100.641796.100.8350.9821.0000.9391991
12Jardim Botânico73.6797.8195.241620.820.8110.9701.0000.9271991
23Ipanema74.0096.9893.951606.880.8170.9601.0000.9251991
34Leblon73.6797.4992.231589.110.8110.9571.0000.9231991
45Humaitá72.8097.93102.671422.010.7970.9860.9850.9231991
....................................
121122Manguinhos66.3091.4869.64188.860.6880.8420.6480.7262000
122123Maré66.5889.4668.76187.250.6930.8260.6460.7222000
123124Acari. Parque Colúmbia63.9391.6879.44174.120.6490.8760.6340.7202000
124125Costa Barros63.9391.3474.09175.000.6490.8560.6350.7132000
125126Complexo do Alemão64.7989.0772.04177.310.6630.8340.6370.7112000
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252 rows × 11 columns

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" + ], + "text/plain": [ + " Ordem segundo o IDH Bairro ou grupo de bairros \\\n", + "0 1 Gávea \n", + "1 2 Jardim Botânico \n", + "2 3 Ipanema \n", + "3 4 Leblon \n", + "4 5 Humaitá \n", + ".. ... ... \n", + "121 122 Manguinhos \n", + "122 123 Maré \n", + "123 124 Acari. Parque Colúmbia \n", + "124 125 Costa Barros \n", + "125 126 Complexo do Alemão \n", + "\n", + " Esperança de vida ao nascer (em anos) \\\n", + "0 75.11 \n", + "1 73.67 \n", + "2 74.00 \n", + "3 73.67 \n", + "4 72.80 \n", + ".. ... \n", + "121 66.30 \n", + "122 66.58 \n", + "123 63.93 \n", + "124 63.93 \n", + "125 64.79 \n", + "\n", + " Taxa de alfabetização de adultos (%) \\\n", + "0 97.25 \n", + "1 97.81 \n", + "2 96.98 \n", + "3 97.49 \n", + "4 97.93 \n", + ".. ... \n", + "121 91.48 \n", + "122 89.46 \n", + "123 91.68 \n", + "124 91.34 \n", + "125 89.07 \n", + "\n", + " Taxa bruta de frequência escolar (%) Renda per capita (em R$ de 2000) \\\n", + "0 100.64 1796.10 \n", + "1 95.24 1620.82 \n", + "2 93.95 1606.88 \n", + "3 92.23 1589.11 \n", + "4 102.67 1422.01 \n", + ".. ... ... \n", + "121 69.64 188.86 \n", + "122 68.76 187.25 \n", + "123 79.44 174.12 \n", + "124 74.09 175.00 \n", + "125 72.04 177.31 \n", + "\n", + " Índice de Longevidade (IDH-L) Índice de Educação (IDH-E) \\\n", + "0 0.835 0.982 \n", + "1 0.811 0.970 \n", + "2 0.817 0.960 \n", + "3 0.811 0.957 \n", + "4 0.797 0.986 \n", + ".. ... ... \n", + "121 0.688 0.842 \n", + "122 0.693 0.826 \n", + "123 0.649 0.876 \n", + "124 0.649 0.856 \n", + "125 0.663 0.834 \n", + "\n", + " Índice de Renda (IDH-R) \\\n", + "0 1.000 \n", + "1 1.000 \n", + "2 1.000 \n", + "3 1.000 \n", + "4 0.985 \n", + ".. ... \n", + "121 0.648 \n", + "122 0.646 \n", + "123 0.634 \n", + "124 0.635 \n", + "125 0.637 \n", + "\n", + " Índice de Desenvolvimento Humano Municipal (IDH) Ano \n", + "0 0.939 1991 \n", + "1 0.927 1991 \n", + "2 0.925 1991 \n", + "3 0.923 1991 \n", + "4 0.923 1991 \n", + ".. ... ... \n", + "121 0.726 2000 \n", + "122 0.722 2000 \n", + "123 0.720 2000 \n", + "124 0.713 2000 \n", + "125 0.711 2000 \n", + "\n", + "[252 rows x 11 columns]" + ] + }, + "execution_count": 16, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df_idh" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": {}, + "outputs": [], + "source": [ + "df_idh.reset_index(drop=True, inplace=True)" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": {}, + "outputs": [], + "source": [ + "centro = [\"Centro\", \"Estácio\", \"Catumbi\"]\n", + "\n", + "ilha_do_governador = [\"Jardim Guanabara\", \"Moneró\", \"Portuguesa\", \"Cocotá\", \"Bancários\", \"Ribeira\", \"Cacuia\", \"Zumbi\", \"Pitangueiras\", \"Praia da Bandeira\", \"Jardim Carioca\", \"Tauá\", \"Galeão\", \"Cidade Universitária\"]\n", + "\n", + "zona_norte = [\"Maracanã\", \"Grajaú\", \"Méier\", \"Tijuca\", \"Alto da Boa Vista\", \"Todos os Santos\", \"Vila da Penha\", \"Andaraí\", \"Riachuelo\", \"Campinho\", \"Vila Valqueire\", \"Vila Isabel\", \"Cachambi\", \"Higienópolis\", \"Água Santa\", \"Encantado\", \"Vila Cosmos\", \"Cidade Nova\", \"Praça da Bandeira\", \"Bonsucesso\", \"Maria da Graça\", \"Del Castilho\", \"Lins de Vasconcelos\", \"Engenho Novo\", \"Ramos\", \"Engenho de Dentro\", \"Abolição\", \"Oswaldo Cruz\", \"Olaria\", \"Bento Ribeiro\", \"Piedade\", \"Quintino Bocaiúva\", \"Rio Comprido\", \"Praça Seca\", \"Jardim América\", \"Jacaré\", \"Rocha\", \"Sampaio\", \"Engenho da Rainha\", \"Brás de Pina\", \"São Cristóvão\", \"Vasco da Gama\", \"Cascadura\", \"Parque Anchieta\", \"Madureira\", \"Pilares\", \"Penha Circular\", \"Benfica\", \"Rocha Miranda\", \"Marechal Hermes\", \"Turiaçu\", \"Guadalupe\", \"Inhaúma\", \"Cavalcanti\", \"Engenheiro Leal\", \"Vaz Lobo\", \"Ricardo de Albuquerque\", \"Coelho Neto\", \"Penha\", \"Honório Gurgel\", \"Tomás Coelho\", \"Mangueira\", \"São Francisco Xavier\", \"Vista Alegre\", \"Irajá\", \"Cordovil\", \"Pavuna\", \"Anchieta\", \"Vicente de Carvalho\", \"Vigário Geral\", \"Colégio\", \"Barros Filho\", \"Parada de Lucas\", \"Jacarezinho\", \"Manguinhos\", \"Maré\", \"Acari\", \"Parque Colúmbia\", \"Costa Barros\", \"Complexo do Alemão\"]\n", + "\n", + "zona_oeste = [\"Joá\", \"Barra da Tijuca\", \"Anil\", \"Pechincha\", \"Freguesia (Jacarepaguá)\", \"Recreio dos Bandeirantes\", \"Grumari\", \"Taquara\", \"Deodoro\", \"Vila Militar\", \"Campo dos Afonsos\", \"Jardim Sulacap\", \"Freguesia\", \"Tanque\", \"Curicica\", \"Itanhangá\", \"Campo Grande\", \"Padre Miguel\", \"Realengo\", \"Senador Vasconcelos\", \"Magalhães Bastos\", \"Bangu\", \"Santíssimo\", \"Jacarepaguá\", \"Senador Camará\", \"Gardênia Azul\", \"Sepetiba\", \"Cosmos\", \"Paciência\", \"Cidade de Deus\", \"Inhoaíba\", \"Camorim\", \"Vargem Pequena\", \"Vargem Grande\", \"Guaratiba\", \"Barra de Guaratiba\", \"Pedra de Guaratiba\", \"Santa Cruz\"]\n", + "\n", + "zona_portuaria = [\"Saúde\", \"Gamboa\", \"Santo Cristo\", \"Caju\"]\n", + "\n", + "zona_sul = [\"Gávea\", \"Leblon\", \"Ipanema\", \"Lagoa\", \"Flamengo\", \"Humaitá\", \"Laranjeiras\", \"Jardim Botânico\", \"Copacabana\", \"Leme\", \"Botafogo\", \"Urca\", \"Glória\", \"Catete\", \"Santa Teresa\", \"Cosme Velho\", \"Vidigal\", \"São Conrado\", \"Rocinha\"]\n", + "\n", + "ilha_de_paqueta = [\"Ilha de Paquetá\", \"Paquetá\"]\n", + "\n", + "df_idh.loc[df_idh['Bairro ou grupo de bairros'].isin(centro), 'Região'] = 'Centro'\n", + "df_idh.loc[df_idh['Bairro ou grupo de bairros'].isin(ilha_do_governador), 'Região'] = 'Ilha do Governador'\n", + "df_idh.loc[df_idh['Bairro ou grupo de bairros'].isin(zona_norte), 'Região'] = 'Zona Norte'\n", + "df_idh.loc[df_idh['Bairro ou grupo de bairros'].isin(zona_oeste), 'Região'] = 'Zona Oeste'\n", + "df_idh.loc[df_idh['Bairro ou grupo de bairros'].isin(zona_portuaria), 'Região'] = 'Zona Portuária'\n", + "df_idh.loc[df_idh['Bairro ou grupo de bairros'].isin(zona_sul), 'Região'] = 'Zona Sul'\n", + "df_idh.loc[df_idh['Bairro ou grupo de bairros'].isin(ilha_de_paqueta), 'Região'] = 'Ilha de Paquetá'\n", + "\n", + "def classificar_regiao(bairros):\n", + " bairros_lista = bairros.split('.')\n", + " regioes_encontradas = set() \n", + " \n", + " for bairro in bairros_lista:\n", + " bairro = bairro.strip() \n", + " \n", + " if bairro in zona_sul:\n", + " regioes_encontradas.add('Zona Sul')\n", + " elif bairro in ilha_de_paqueta:\n", + " regioes_encontradas.add('Ilha de Paquetá')\n", + " elif bairro in zona_portuaria:\n", + " regioes_encontradas.add('Zona Portuária')\n", + " elif bairro in zona_oeste:\n", + " regioes_encontradas.add('Zona Oeste')\n", + " elif bairro in zona_norte:\n", + " regioes_encontradas.add('Zona Norte')\n", + " elif bairro in ilha_do_governador:\n", + " regioes_encontradas.add('Ilha do Governador')\n", + " elif bairro in centro:\n", + " regioes_encontradas.add('Centro')\n", + " \n", + " if len(regioes_encontradas) == 1:\n", + " return regioes_encontradas.pop()\n", + " elif len(regioes_encontradas) > 1:\n", + " return 'Regiões Múltiplas'\n", + " else:\n", + " return 'Desconhecida'\n", + " \n", + "df_idh['Região'] = df_idh['Bairro ou grupo de bairros'].apply(classificar_regiao)" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": {}, + "outputs": [ + { + "data": { + 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Ordem segundo o IDHBairro ou grupo de bairrosEsperança de vida ao nascer (em anos)Taxa de alfabetização de adultos (%)Taxa bruta de frequência escolar (%)Renda per capita (em R$ de 2000)Índice de Longevidade (IDH-L)Índice de Educação (IDH-E)Índice de Renda (IDH-R)Índice de Desenvolvimento Humano Municipal (IDH)AnoRegião
01Gávea75.1197.25100.641796.100.8350.9821.0000.9391991Zona Sul
12Jardim Botânico73.6797.8195.241620.820.8110.9701.0000.9271991Zona Sul
23Ipanema74.0096.9893.951606.880.8170.9601.0000.9251991Zona Sul
34Leblon73.6797.4992.231589.110.8110.9571.0000.9231991Zona Sul
45Humaitá72.8097.93102.671422.010.7970.9860.9850.9231991Zona Sul
.......................................
247122Manguinhos66.3091.4869.64188.860.6880.8420.6480.7262000Zona Norte
248123Maré66.5889.4668.76187.250.6930.8260.6460.7222000Zona Norte
249124Acari. Parque Colúmbia63.9391.6879.44174.120.6490.8760.6340.7202000Zona Norte
250125Costa Barros63.9391.3474.09175.000.6490.8560.6350.7132000Zona Norte
251126Complexo do Alemão64.7989.0772.04177.310.6630.8340.6370.7112000Zona Norte
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252 rows × 12 columns

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" + ], + "text/plain": [ + " Ordem segundo o IDH Bairro ou grupo de bairros \\\n", + "0 1 Gávea \n", + "1 2 Jardim Botânico \n", + "2 3 Ipanema \n", + "3 4 Leblon \n", + "4 5 Humaitá \n", + ".. ... ... \n", + "247 122 Manguinhos \n", + "248 123 Maré \n", + "249 124 Acari. Parque Colúmbia \n", + "250 125 Costa Barros \n", + "251 126 Complexo do Alemão \n", + "\n", + " Esperança de vida ao nascer (em anos) \\\n", + "0 75.11 \n", + "1 73.67 \n", + "2 74.00 \n", + "3 73.67 \n", + "4 72.80 \n", + ".. ... \n", + "247 66.30 \n", + "248 66.58 \n", + "249 63.93 \n", + "250 63.93 \n", + "251 64.79 \n", + "\n", + " Taxa de alfabetização de adultos (%) \\\n", + "0 97.25 \n", + "1 97.81 \n", + "2 96.98 \n", + "3 97.49 \n", + "4 97.93 \n", + ".. ... \n", + "247 91.48 \n", + "248 89.46 \n", + "249 91.68 \n", + "250 91.34 \n", + "251 89.07 \n", + "\n", + " Taxa bruta de frequência escolar (%) Renda per capita (em R$ de 2000) \\\n", + "0 100.64 1796.10 \n", + "1 95.24 1620.82 \n", + "2 93.95 1606.88 \n", + "3 92.23 1589.11 \n", + "4 102.67 1422.01 \n", + ".. ... ... \n", + "247 69.64 188.86 \n", + "248 68.76 187.25 \n", + "249 79.44 174.12 \n", + "250 74.09 175.00 \n", + "251 72.04 177.31 \n", + "\n", + " Índice de Longevidade (IDH-L) Índice de Educação (IDH-E) \\\n", + "0 0.835 0.982 \n", + "1 0.811 0.970 \n", + "2 0.817 0.960 \n", + "3 0.811 0.957 \n", + "4 0.797 0.986 \n", + ".. ... ... \n", + "247 0.688 0.842 \n", + "248 0.693 0.826 \n", + "249 0.649 0.876 \n", + "250 0.649 0.856 \n", + "251 0.663 0.834 \n", + "\n", + " Índice de Renda (IDH-R) \\\n", + "0 1.000 \n", + "1 1.000 \n", + "2 1.000 \n", + "3 1.000 \n", + "4 0.985 \n", + ".. ... \n", + "247 0.648 \n", + "248 0.646 \n", + "249 0.634 \n", + "250 0.635 \n", + "251 0.637 \n", + "\n", + " Índice de Desenvolvimento Humano Municipal (IDH) Ano Região \n", + "0 0.939 1991 Zona Sul \n", + "1 0.927 1991 Zona Sul \n", + "2 0.925 1991 Zona Sul \n", + "3 0.923 1991 Zona Sul \n", + "4 0.923 1991 Zona Sul \n", + ".. ... ... ... \n", + "247 0.726 2000 Zona Norte \n", + "248 0.722 2000 Zona Norte \n", + "249 0.720 2000 Zona Norte \n", + "250 0.713 2000 Zona Norte \n", + "251 0.711 2000 Zona Norte \n", + "\n", + "[252 rows x 12 columns]" + ] + }, + "execution_count": 19, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df_idh" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "C:\\Users\\daian\\AppData\\Local\\Temp\\ipykernel_16320\\1700266703.py:1: DeprecationWarning: DataFrameGroupBy.apply operated on the grouping columns. This behavior is deprecated, and in a future version of pandas the grouping columns will be excluded from the operation. Either pass `include_groups=False` to exclude the groupings or explicitly select the grouping columns after groupby to silence this warning.\n", + " df_estatisticas_1991 = df_idh[df_idh['Ano'] == 1991].groupby('Região').apply(lambda x: x.describe().T)\n" + ] + }, + { + "data": { + "text/html": [ + "
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countmeanstdmin25%50%75%max
Região
CentroOrdem segundo o IDH3.063.00000030.51229332.00048.0000064.000078.50093.000
Esperança de vida ao nascer (em anos)3.068.4500003.05947764.93067.4400069.950070.21070.470
Taxa de alfabetização de adultos (%)3.093.7300002.07906292.48092.5300092.580094.35596.130
Taxa bruta de frequência escolar (%)3.076.7400003.39442273.25075.0950076.940078.48580.030
Renda per capita (em R$ de 2000)3.0358.116667124.941498250.590289.58500328.5800411.880495.180
..............................
Zona SulÍndice de Longevidade (IDH-L)16.00.7843120.0449880.6690.785000.79800.8110.835
Índice de Educação (IDH-E)16.00.9355000.0671770.7250.938250.95550.9730.988
Índice de Renda (IDH-R)16.00.9353120.0967800.6310.937500.96601.0001.000
Índice de Desenvolvimento Humano Municipal (IDH)16.00.8851250.0666070.6750.874750.91200.9230.939
Ano16.01991.0000000.0000001991.0001991.000001991.00001991.0001991.000
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70 rows × 8 columns

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" + ], + "text/plain": [ + " count mean \\\n", + "Região \n", + "Centro Ordem segundo o IDH 3.0 63.000000 \n", + " Esperança de vida ao nascer (em anos) 3.0 68.450000 \n", + " Taxa de alfabetização de adultos (%) 3.0 93.730000 \n", + " Taxa bruta de frequência escolar (%) 3.0 76.740000 \n", + " Renda per capita (em R$ de 2000) 3.0 358.116667 \n", + "... ... ... \n", + "Zona Sul Índice de Longevidade (IDH-L) 16.0 0.784312 \n", + " Índice de Educação (IDH-E) 16.0 0.935500 \n", + " Índice de Renda (IDH-R) 16.0 0.935312 \n", + " Índice de Desenvolvimento Humano Municipal (IDH) 16.0 0.885125 \n", + " Ano 16.0 1991.000000 \n", + "\n", + " std \\\n", + "Região \n", + "Centro Ordem segundo o IDH 30.512293 \n", + " Esperança de vida ao nascer (em anos) 3.059477 \n", + " Taxa de alfabetização de adultos (%) 2.079062 \n", + " Taxa bruta de frequência escolar (%) 3.394422 \n", + " Renda per capita (em R$ de 2000) 124.941498 \n", + "... ... \n", + "Zona Sul Índice de Longevidade (IDH-L) 0.044988 \n", + " Índice de Educação (IDH-E) 0.067177 \n", + " Índice de Renda (IDH-R) 0.096780 \n", + " Índice de Desenvolvimento Humano Municipal (IDH) 0.066607 \n", + " Ano 0.000000 \n", + "\n", + " min \\\n", + "Região \n", + "Centro Ordem segundo o IDH 32.000 \n", + " Esperança de vida ao nascer (em anos) 64.930 \n", + " Taxa de alfabetização de adultos (%) 92.480 \n", + " Taxa bruta de frequência escolar (%) 73.250 \n", + " Renda per capita (em R$ de 2000) 250.590 \n", + "... ... \n", + "Zona Sul Índice de Longevidade (IDH-L) 0.669 \n", + " Índice de Educação (IDH-E) 0.725 \n", + " Índice de Renda (IDH-R) 0.631 \n", + " Índice de Desenvolvimento Humano Municipal (IDH) 0.675 \n", + " Ano 1991.000 \n", + "\n", + " 25% \\\n", + "Região \n", + "Centro Ordem segundo o IDH 48.00000 \n", + " Esperança de vida ao nascer (em anos) 67.44000 \n", + " Taxa de alfabetização de adultos (%) 92.53000 \n", + " Taxa bruta de frequência escolar (%) 75.09500 \n", + " Renda per capita (em R$ de 2000) 289.58500 \n", + "... ... \n", + "Zona Sul Índice de Longevidade (IDH-L) 0.78500 \n", + " Índice de Educação (IDH-E) 0.93825 \n", + " Índice de Renda (IDH-R) 0.93750 \n", + " Índice de Desenvolvimento Humano Municipal (IDH) 0.87475 \n", + " Ano 1991.00000 \n", + "\n", + " 50% \\\n", + "Região \n", + "Centro Ordem segundo o IDH 64.0000 \n", + " Esperança de vida ao nascer (em anos) 69.9500 \n", + " Taxa de alfabetização de adultos (%) 92.5800 \n", + " Taxa bruta de frequência escolar (%) 76.9400 \n", + " Renda per capita (em R$ de 2000) 328.5800 \n", + "... ... \n", + "Zona Sul Índice de Longevidade (IDH-L) 0.7980 \n", + " Índice de Educação (IDH-E) 0.9555 \n", + " Índice de Renda (IDH-R) 0.9660 \n", + " Índice de Desenvolvimento Humano Municipal (IDH) 0.9120 \n", + " Ano 1991.0000 \n", + "\n", + " 75% max \n", + "Região \n", + "Centro Ordem segundo o IDH 78.500 93.000 \n", + " Esperança de vida ao nascer (em anos) 70.210 70.470 \n", + " Taxa de alfabetização de adultos (%) 94.355 96.130 \n", + " Taxa bruta de frequência escolar (%) 78.485 80.030 \n", + " Renda per capita (em R$ de 2000) 411.880 495.180 \n", + "... ... ... \n", + "Zona Sul Índice de Longevidade (IDH-L) 0.811 0.835 \n", + " Índice de Educação (IDH-E) 0.973 0.988 \n", + " Índice de Renda (IDH-R) 1.000 1.000 \n", + " Índice de Desenvolvimento Humano Municipal (IDH) 0.923 0.939 \n", + " Ano 1991.000 1991.000 \n", + "\n", + "[70 rows x 8 columns]" + ] + }, + "execution_count": 20, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df_estatisticas_1991 = df_idh[df_idh['Ano'] == 1991].groupby('Região').apply(lambda x: x.describe().T)\n", + "df_estatisticas_1991" + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "C:\\Users\\daian\\AppData\\Local\\Temp\\ipykernel_16320\\2863842909.py:1: DeprecationWarning: DataFrameGroupBy.apply operated on the grouping columns. This behavior is deprecated, and in a future version of pandas the grouping columns will be excluded from the operation. Either pass `include_groups=False` to exclude the groupings or explicitly select the grouping columns after groupby to silence this warning.\n", + " df_estatisticas_2000 = df_idh[df_idh['Ano'] == 2000].groupby('Região').apply(lambda x: x.describe().T)\n" + ] + }, + { + "data": { + "text/html": [ + "
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countmeanstdmin25%50%75%max
Região
CentroOrdem segundo o IDH3.065.00000030.80584432.00051.0000070.000081.5000093.000
Esperança de vida ao nascer (em anos)3.073.1433333.29673169.60071.6550073.710074.9150076.120
Taxa de alfabetização de adultos (%)3.095.8266671.74506094.09094.9500095.810096.6950097.580
Taxa bruta de frequência escolar (%)3.088.4900009.58847780.82083.1150085.410092.3250099.240
Renda per capita (em R$ de 2000)3.0457.080000158.907743324.830368.94000413.0500523.20500633.360
..............................
Zona SulÍndice de Longevidade (IDH-L)16.00.8610630.0553830.7060.863000.88100.883500.924
Índice de Educação (IDH-E)16.00.9723750.0474100.8180.984750.99150.993250.996
Índice de Renda (IDH-R)16.00.9570000.0863930.6730.952001.00001.000001.000
Índice de Desenvolvimento Humano Municipal (IDH)16.00.9298120.0610230.7320.930250.95650.959000.970
Ano16.02000.0000000.0000002000.0002000.000002000.00002000.000002000.000
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70 rows × 8 columns

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" + ], + "text/plain": [ + " count mean \\\n", + "Região \n", + "Centro Ordem segundo o IDH 3.0 65.000000 \n", + " Esperança de vida ao nascer (em anos) 3.0 73.143333 \n", + " Taxa de alfabetização de adultos (%) 3.0 95.826667 \n", + " Taxa bruta de frequência escolar (%) 3.0 88.490000 \n", + " Renda per capita (em R$ de 2000) 3.0 457.080000 \n", + "... ... ... \n", + "Zona Sul Índice de Longevidade (IDH-L) 16.0 0.861063 \n", + " Índice de Educação (IDH-E) 16.0 0.972375 \n", + " Índice de Renda (IDH-R) 16.0 0.957000 \n", + " Índice de Desenvolvimento Humano Municipal (IDH) 16.0 0.929812 \n", + " Ano 16.0 2000.000000 \n", + "\n", + " std \\\n", + "Região \n", + "Centro Ordem segundo o IDH 30.805844 \n", + " Esperança de vida ao nascer (em anos) 3.296731 \n", + " Taxa de alfabetização de adultos (%) 1.745060 \n", + " Taxa bruta de frequência escolar (%) 9.588477 \n", + " Renda per capita (em R$ de 2000) 158.907743 \n", + "... ... \n", + "Zona Sul Índice de Longevidade (IDH-L) 0.055383 \n", + " Índice de Educação (IDH-E) 0.047410 \n", + " Índice de Renda (IDH-R) 0.086393 \n", + " Índice de Desenvolvimento Humano Municipal (IDH) 0.061023 \n", + " Ano 0.000000 \n", + "\n", + " min \\\n", + "Região \n", + "Centro Ordem segundo o IDH 32.000 \n", + " Esperança de vida ao nascer (em anos) 69.600 \n", + " Taxa de alfabetização de adultos (%) 94.090 \n", + " Taxa bruta de frequência escolar (%) 80.820 \n", + " Renda per capita (em R$ de 2000) 324.830 \n", + "... ... \n", + "Zona Sul Índice de Longevidade (IDH-L) 0.706 \n", + " Índice de Educação (IDH-E) 0.818 \n", + " Índice de Renda (IDH-R) 0.673 \n", + " Índice de Desenvolvimento Humano Municipal (IDH) 0.732 \n", + " Ano 2000.000 \n", + "\n", + " 25% \\\n", + "Região \n", + "Centro Ordem segundo o IDH 51.00000 \n", + " Esperança de vida ao nascer (em anos) 71.65500 \n", + " Taxa de alfabetização de adultos (%) 94.95000 \n", + " Taxa bruta de frequência escolar (%) 83.11500 \n", + " Renda per capita (em R$ de 2000) 368.94000 \n", + "... ... \n", + "Zona Sul Índice de Longevidade (IDH-L) 0.86300 \n", + " Índice de Educação (IDH-E) 0.98475 \n", + " Índice de Renda (IDH-R) 0.95200 \n", + " Índice de Desenvolvimento Humano Municipal (IDH) 0.93025 \n", + " Ano 2000.00000 \n", + "\n", + " 50% \\\n", + "Região \n", + "Centro Ordem segundo o IDH 70.0000 \n", + " Esperança de vida ao nascer (em anos) 73.7100 \n", + " Taxa de alfabetização de adultos (%) 95.8100 \n", + " Taxa bruta de frequência escolar (%) 85.4100 \n", + " Renda per capita (em R$ de 2000) 413.0500 \n", + "... ... \n", + "Zona Sul Índice de Longevidade (IDH-L) 0.8810 \n", + " Índice de Educação (IDH-E) 0.9915 \n", + " Índice de Renda (IDH-R) 1.0000 \n", + " Índice de Desenvolvimento Humano Municipal (IDH) 0.9565 \n", + " Ano 2000.0000 \n", + "\n", + " 75% \\\n", + "Região \n", + "Centro Ordem segundo o IDH 81.50000 \n", + " Esperança de vida ao nascer (em anos) 74.91500 \n", + " Taxa de alfabetização de adultos (%) 96.69500 \n", + " Taxa bruta de frequência escolar (%) 92.32500 \n", + " Renda per capita (em R$ de 2000) 523.20500 \n", + "... ... \n", + "Zona Sul Índice de Longevidade (IDH-L) 0.88350 \n", + " Índice de Educação (IDH-E) 0.99325 \n", + " Índice de Renda (IDH-R) 1.00000 \n", + " Índice de Desenvolvimento Humano Municipal (IDH) 0.95900 \n", + " Ano 2000.00000 \n", + "\n", + " max \n", + "Região \n", + "Centro Ordem segundo o IDH 93.000 \n", + " Esperança de vida ao nascer (em anos) 76.120 \n", + " Taxa de alfabetização de adultos (%) 97.580 \n", + " Taxa bruta de frequência escolar (%) 99.240 \n", + " Renda per capita (em R$ de 2000) 633.360 \n", + "... ... \n", + "Zona Sul Índice de Longevidade (IDH-L) 0.924 \n", + " Índice de Educação (IDH-E) 0.996 \n", + " Índice de Renda (IDH-R) 1.000 \n", + " Índice de Desenvolvimento Humano Municipal (IDH) 0.970 \n", + " Ano 2000.000 \n", + "\n", + "[70 rows x 8 columns]" + ] + }, + "execution_count": 21, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df_estatisticas_2000 = df_idh[df_idh['Ano'] == 2000].groupby('Região').apply(lambda x: x.describe().T)\n", + "df_estatisticas_2000" + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "metadata": {}, + "outputs": [], + "source": [ + "df_estatisticas = pd.merge(df_estatisticas_1991, df_estatisticas_2000, on=['Região'], how='inner')\n" + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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Médias 1991Médias 2000
Região
CentroOrdem segundo o IDH63.00000065.000000
Esperança de vida ao nascer (em anos)68.45000073.143333
Taxa de alfabetização de adultos (%)93.73000095.826667
Taxa bruta de frequência escolar (%)76.74000088.490000
Renda per capita (em R$ de 2000)358.116667457.080000
............
Zona SulÍndice de Longevidade (IDH-L)0.7843120.861063
Índice de Educação (IDH-E)0.9355000.972375
Índice de Renda (IDH-R)0.9353120.957000
Índice de Desenvolvimento Humano Municipal (IDH)0.8851250.929812
Ano1991.0000002000.000000
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70 rows × 2 columns

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" + ], + "text/plain": [ + " Médias 1991 \\\n", + "Região \n", + "Centro Ordem segundo o IDH 63.000000 \n", + " Esperança de vida ao nascer (em anos) 68.450000 \n", + " Taxa de alfabetização de adultos (%) 93.730000 \n", + " Taxa bruta de frequência escolar (%) 76.740000 \n", + " Renda per capita (em R$ de 2000) 358.116667 \n", + "... ... \n", + "Zona Sul Índice de Longevidade (IDH-L) 0.784312 \n", + " Índice de Educação (IDH-E) 0.935500 \n", + " Índice de Renda (IDH-R) 0.935312 \n", + " Índice de Desenvolvimento Humano Municipal (IDH) 0.885125 \n", + " Ano 1991.000000 \n", + "\n", + " Médias 2000 \n", + "Região \n", + "Centro Ordem segundo o IDH 65.000000 \n", + " Esperança de vida ao nascer (em anos) 73.143333 \n", + " Taxa de alfabetização de adultos (%) 95.826667 \n", + " Taxa bruta de frequência escolar (%) 88.490000 \n", + " Renda per capita (em R$ de 2000) 457.080000 \n", + "... ... \n", + "Zona Sul Índice de Longevidade (IDH-L) 0.861063 \n", + " Índice de Educação (IDH-E) 0.972375 \n", + " Índice de Renda (IDH-R) 0.957000 \n", + " Índice de Desenvolvimento Humano Municipal (IDH) 0.929812 \n", + " Ano 2000.000000 \n", + "\n", + "[70 rows x 2 columns]" + ] + }, + "execution_count": 23, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "medias_1991 = df_estatisticas_1991['mean']\n", + "medias_2000 = df_estatisticas_2000['mean']\n", + "\n", + "medias = pd.DataFrame({'Médias 1991':medias_1991, 'Médias 2000':medias_2000})\n", + "\n", + "medias" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "metadata": {}, + "outputs": [], + "source": [ + "# pd.reset_option('display.max_rows')\n" + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "metadata": {}, + "outputs": [], + "source": [ + "# pd.set_option('display.max_rows', None)" + ] + }, + { + "cell_type": "code", + "execution_count": 26, + "metadata": {}, + "outputs": [], + "source": [ + "# df_idh.to_csv('base_final_idh.csv')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### **Qual é a média dos principais indicadores de IDH (índice de longevidade, índice de educação e índice de renda) em cada região do Rio de Janeiro (zona oeste, zona norte, zona sul, etc.) nos anos de 1991 e 2000?**" + ] + }, + { + "cell_type": "code", + "execution_count": 48, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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Ano19912000
Região
Centro0.7243330.802333
Ilha de Paquetá0.7200000.818000
Ilha do Governador0.7300000.810375
Zona Norte0.7069700.776567
Zona Oeste0.6892410.752448
Zona Portuária0.6825000.743500
Zona Sul0.7843120.861062
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" + ], + "text/plain": [ + "Ano 1991 2000\n", + "Região \n", + "Centro 0.724333 0.802333\n", + "Ilha de Paquetá 0.720000 0.818000\n", + "Ilha do Governador 0.730000 0.810375\n", + "Zona Norte 0.706970 0.776567\n", + "Zona Oeste 0.689241 0.752448\n", + "Zona Portuária 0.682500 0.743500\n", + "Zona Sul 0.784312 0.861062" + ] + }, + "execution_count": 48, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Médias Índice de Longevidade (IDH-L)\n", + "medias_IDHL = df_idh.groupby(['Região', 'Ano'])['Índice de Longevidade (IDH-L)'].mean().unstack()\n", + "medias_IDHL" + ] + }, + { + "cell_type": "code", + "execution_count": 64, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "medias_reset = medias_IDHL.reset_index()\n", + "medias_long = medias_reset.melt(id_vars='Região', var_name='Ano', value_name='Média do IDH-L')\n", + "\n", + "plt.figure(figsize=(10, 6))\n", + "ax = sns.barplot(data=medias_long, x='Região', y='Média do IDH-L', hue='Ano', errorbar=None)\n", + "\n", + "for p in ax.patches:\n", + " ax.annotate(f'{p.get_height():.2f}', \n", + " (p.get_x() + p.get_width() / 2., p.get_height()), \n", + " ha='center', va='bottom')\n", + "\n", + "plt.title('Média do Índice de Longevidade (IDH-L) por Região e Ano')\n", + "plt.xticks(rotation=45)\n", + "plt.tight_layout()\n", + "plt.show()\n" + ] + }, + { + "cell_type": "code", + "execution_count": 49, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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Ano19912000
Região
Centro0.8810000.933667
Ilha de Paquetá0.8630000.854000
Ilha do Governador0.9063750.944625
Zona Norte0.8919400.936343
Zona Oeste0.8556550.918069
Zona Portuária0.8070000.864500
Zona Sul0.9355000.972375
\n", + "
" + ], + "text/plain": [ + "Ano 1991 2000\n", + "Região \n", + "Centro 0.881000 0.933667\n", + "Ilha de Paquetá 0.863000 0.854000\n", + "Ilha do Governador 0.906375 0.944625\n", + "Zona Norte 0.891940 0.936343\n", + "Zona Oeste 0.855655 0.918069\n", + "Zona Portuária 0.807000 0.864500\n", + "Zona Sul 0.935500 0.972375" + ] + }, + "execution_count": 49, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Médias Índice de Educação (IDH-E)\n", + "medias_IDHE = df_idh.groupby(['Região', 'Ano'])['Índice de Educação (IDH-E)'].mean().unstack()\n", + "medias_IDHE" + ] + }, + { + "cell_type": "code", + "execution_count": 149, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "medias_reset = medias_IDHE.reset_index()\n", + "medias_long = medias_reset.melt(id_vars='Região', var_name='Ano', value_name='Média do IDH-E')\n", + "\n", + "plt.figure(figsize=(10, 6))\n", + "ax = sns.barplot(data=medias_long, x='Região', y='Média do IDH-E', hue='Ano', errorbar=None)\n", + "\n", + "for p in ax.patches:\n", + " ax.annotate(f'{p.get_height():.2f}', \n", + " (p.get_x() + p.get_width() / 2., p.get_height()), \n", + " ha='center', va='bottom')\n", + "\n", + "plt.title('Média do Índice de Educação (IDH-E) por Região e Ano')\n", + "plt.xticks(rotation=45)\n", + "plt.tight_layout()\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 50, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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Ano19912000
Região
Centro0.7480000.788667
Ilha de Paquetá0.7420000.795000
Ilha do Governador0.7780000.823500
Zona Norte0.7328360.780657
Zona Oeste0.7172410.762069
Zona Portuária0.6770000.710500
Zona Sul0.9353120.957000
\n", + "
" + ], + "text/plain": [ + "Ano 1991 2000\n", + "Região \n", + "Centro 0.748000 0.788667\n", + "Ilha de Paquetá 0.742000 0.795000\n", + "Ilha do Governador 0.778000 0.823500\n", + "Zona Norte 0.732836 0.780657\n", + "Zona Oeste 0.717241 0.762069\n", + "Zona Portuária 0.677000 0.710500\n", + "Zona Sul 0.935312 0.957000" + ] + }, + "execution_count": 50, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Médias Índice de Renda (IDH-R)\n", + "medias_IDHR = df_idh.groupby(['Região', 'Ano'])['Índice de Renda (IDH-R)'].mean().unstack()\n", + "medias_IDHR" + ] + }, + { + "cell_type": "code", + "execution_count": 150, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "medias_reset = medias_IDHR.reset_index()\n", + "medias_long = medias_reset.melt(id_vars='Região', var_name='Ano', value_name='Média do IDH-R')\n", + "\n", + "plt.figure(figsize=(10, 6))\n", + "ax = sns.barplot(data=medias_long, x='Região', y='Média do IDH-R', hue='Ano', errorbar=None)\n", + "\n", + "for p in ax.patches:\n", + " ax.annotate(f'{p.get_height():.2f}', \n", + " (p.get_x() + p.get_width() / 2., p.get_height()), \n", + " ha='center', va='bottom')\n", + "\n", + "plt.title('Média do Índice de Renda (IDH-R) por Região e Ano')\n", + "plt.xticks(rotation=45)\n", + "plt.tight_layout()\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### **Qual é a dispersão dos indicadores de IDH dentro de uma mesma zona? Existe desigualdade interna?**" + ] + }, + { + "cell_type": "code", + "execution_count": 100, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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Bairro ou grupo de bairrosÍndice de Desenvolvimento Humano Municipal (IDH)_1991Índice de Desenvolvimento Humano Municipal (IDH)_2000
0Gávea0.9390.970
1Jardim Botânico0.9270.957
2Ipanema0.9250.962
3Leblon0.9230.967
4Humaitá0.9230.959
5Flamengo0.9190.959
6Laranjeiras0.9190.957
7Lagoa0.9150.959
8Botafogo. Urca0.9090.952
9Leme0.9030.955
10Copacabana0.9020.956
11Glória0.8830.940
12Catete0.8500.901
13Vidigal. São Conrado0.8400.873
14Santa Teresa. Cosme Velho0.8100.878
15Rocinha0.6750.732
\n", + "
" + ], + "text/plain": [ + " Bairro ou grupo de bairros \\\n", + "0 Gávea \n", + "1 Jardim Botânico \n", + "2 Ipanema \n", + "3 Leblon \n", + "4 Humaitá \n", + "5 Flamengo \n", + "6 Laranjeiras \n", + "7 Lagoa \n", + "8 Botafogo. Urca \n", + "9 Leme \n", + "10 Copacabana \n", + "11 Glória \n", + "12 Catete \n", + "13 Vidigal. São Conrado \n", + "14 Santa Teresa. Cosme Velho \n", + "15 Rocinha \n", + "\n", + " Índice de Desenvolvimento Humano Municipal (IDH)_1991 \\\n", + "0 0.939 \n", + "1 0.927 \n", + "2 0.925 \n", + "3 0.923 \n", + "4 0.923 \n", + "5 0.919 \n", + "6 0.919 \n", + "7 0.915 \n", + "8 0.909 \n", + "9 0.903 \n", + "10 0.902 \n", + "11 0.883 \n", + "12 0.850 \n", + "13 0.840 \n", + "14 0.810 \n", + "15 0.675 \n", + "\n", + " Índice de Desenvolvimento Humano Municipal (IDH)_2000 \n", + "0 0.970 \n", + "1 0.957 \n", + "2 0.962 \n", + "3 0.967 \n", + "4 0.959 \n", + "5 0.959 \n", + "6 0.957 \n", + "7 0.959 \n", + "8 0.952 \n", + "9 0.955 \n", + "10 0.956 \n", + "11 0.940 \n", + "12 0.901 \n", + "13 0.873 \n", + "14 0.878 \n", + "15 0.732 " + ] + }, + "execution_count": 100, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "zonasul = df_idh[df_idh['Região'] == 'Zona Sul'][['Bairro ou grupo de bairros', 'Índice de Desenvolvimento Humano Municipal (IDH)', 'Ano']]\n", + "\n", + "zonasul_1991 = zonasul[zonasul['Ano'] == 1991]\n", + "zonasul_2000 = zonasul[zonasul['Ano'] == 2000]\n", + "\n", + "zonasul_1991_2000 = pd.merge(zonasul_1991, zonasul_2000, on='Bairro ou grupo de bairros', suffixes=('_1991', '_2000'))\n", + "zonasul_1991_2000 = zonasul_1991_2000.drop(['Ano_1991', 'Ano_2000'], axis=1)\n", + "zonasul_1991_2000" + ] + }, + { + "cell_type": "code", + "execution_count": 102, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "\n", + "\n", + "# Supondo que zonasul_merge já esteja definido\n", + "plt.figure(figsize=(10, 6))\n", + "\n", + "# Gerando o gráfico de dispersão\n", + "plt.scatter(zonasul_1991_2000['Índice de Desenvolvimento Humano Municipal (IDH)_1991'],\n", + " zonasul_1991_2000['Índice de Desenvolvimento Humano Municipal (IDH)_2000'])\n", + "\n", + "# Adicionando título e rótulos aos eixos\n", + "plt.title('Dispersão do IDH de 1991 e 2000 - Zona Sul')\n", + "plt.xlabel('IDH 1991')\n", + "plt.ylabel('IDH 2000')\n", + "\n", + "# Exibindo a grade\n", + "plt.grid()\n", + "\n", + "# Exibindo o gráfico\n", + "plt.show()\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Com o gráfico de dispersão, podemos identificar que, embora os bairros estejam situados na mesma região, podemos observar a disparidade do índice de IDH entre alguns bairros, não tendo padrão, ou seja, existe desigualdade interna. " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### **Quais zonas apresentam a maior variação nos indicadores de IDH entre 1991 e 2000?**" + ] + }, + { + "cell_type": "code", + "execution_count": 103, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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Ordem segundo o IDHBairro ou grupo de bairrosEsperança de vida ao nascer (em anos)Taxa de alfabetização de adultos (%)Taxa bruta de frequência escolar (%)Renda per capita (em R$ de 2000)Índice de Longevidade (IDH-L)Índice de Educação (IDH-E)Índice de Renda (IDH-R)Índice de Desenvolvimento Humano Municipal (IDH)AnoRegião
01Gávea75.1197.25100.641796.100.8350.9821.0000.9391991Zona Sul
12Jardim Botânico73.6797.8195.241620.820.8110.9701.0000.9271991Zona Sul
23Ipanema74.0096.9893.951606.880.8170.9601.0000.9251991Zona Sul
34Leblon73.6797.4992.231589.110.8110.9571.0000.9231991Zona Sul
45Humaitá72.8097.93102.671422.010.7970.9860.9850.9231991Zona Sul
.......................................
247122Manguinhos66.3091.4869.64188.860.6880.8420.6480.7262000Zona Norte
248123Maré66.5889.4668.76187.250.6930.8260.6460.7222000Zona Norte
249124Acari. Parque Colúmbia63.9391.6879.44174.120.6490.8760.6340.7202000Zona Norte
250125Costa Barros63.9391.3474.09175.000.6490.8560.6350.7132000Zona Norte
251126Complexo do Alemão64.7989.0772.04177.310.6630.8340.6370.7112000Zona Norte
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252 rows × 12 columns

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" + ], + "text/plain": [ + " Ordem segundo o IDH Bairro ou grupo de bairros \\\n", + "0 1 Gávea \n", + "1 2 Jardim Botânico \n", + "2 3 Ipanema \n", + "3 4 Leblon \n", + "4 5 Humaitá \n", + ".. ... ... \n", + "247 122 Manguinhos \n", + "248 123 Maré \n", + "249 124 Acari. Parque Colúmbia \n", + "250 125 Costa Barros \n", + "251 126 Complexo do Alemão \n", + "\n", + " Esperança de vida ao nascer (em anos) \\\n", + "0 75.11 \n", + "1 73.67 \n", + "2 74.00 \n", + "3 73.67 \n", + "4 72.80 \n", + ".. ... \n", + "247 66.30 \n", + "248 66.58 \n", + "249 63.93 \n", + "250 63.93 \n", + "251 64.79 \n", + "\n", + " Taxa de alfabetização de adultos (%) \\\n", + "0 97.25 \n", + "1 97.81 \n", + "2 96.98 \n", + "3 97.49 \n", + "4 97.93 \n", + ".. ... \n", + "247 91.48 \n", + "248 89.46 \n", + "249 91.68 \n", + "250 91.34 \n", + "251 89.07 \n", + "\n", + " Taxa bruta de frequência escolar (%) Renda per capita (em R$ de 2000) \\\n", + "0 100.64 1796.10 \n", + "1 95.24 1620.82 \n", + "2 93.95 1606.88 \n", + "3 92.23 1589.11 \n", + "4 102.67 1422.01 \n", + ".. ... ... \n", + "247 69.64 188.86 \n", + "248 68.76 187.25 \n", + "249 79.44 174.12 \n", + "250 74.09 175.00 \n", + "251 72.04 177.31 \n", + "\n", + " Índice de Longevidade (IDH-L) Índice de Educação (IDH-E) \\\n", + "0 0.835 0.982 \n", + "1 0.811 0.970 \n", + "2 0.817 0.960 \n", + "3 0.811 0.957 \n", + "4 0.797 0.986 \n", + ".. ... ... \n", + "247 0.688 0.842 \n", + "248 0.693 0.826 \n", + "249 0.649 0.876 \n", + "250 0.649 0.856 \n", + "251 0.663 0.834 \n", + "\n", + " Índice de Renda (IDH-R) \\\n", + "0 1.000 \n", + "1 1.000 \n", + "2 1.000 \n", + "3 1.000 \n", + "4 0.985 \n", + ".. ... \n", + "247 0.648 \n", + "248 0.646 \n", + "249 0.634 \n", + "250 0.635 \n", + "251 0.637 \n", + "\n", + " Índice de Desenvolvimento Humano Municipal (IDH) Ano Região \n", + "0 0.939 1991 Zona Sul \n", + "1 0.927 1991 Zona Sul \n", + "2 0.925 1991 Zona Sul \n", + "3 0.923 1991 Zona Sul \n", + "4 0.923 1991 Zona Sul \n", + ".. ... ... ... \n", + "247 0.726 2000 Zona Norte \n", + "248 0.722 2000 Zona Norte \n", + "249 0.720 2000 Zona Norte \n", + "250 0.713 2000 Zona Norte \n", + "251 0.711 2000 Zona Norte \n", + "\n", + "[252 rows x 12 columns]" + ] + }, + "execution_count": 103, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df_idh" + ] + }, + { + "cell_type": "code", + "execution_count": 133, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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Ano19912000
Região
Centro0.7843330.841667
Ilha de Paquetá0.7750000.822000
Ilha do Governador0.8046250.859500
Zona Norte0.7772690.831149
Zona Oeste0.7538970.810862
Zona Portuária0.7220000.772500
Zona Sul0.8851250.929812
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" + ], + "text/plain": [ + "Ano 1991 2000\n", + "Região \n", + "Centro 0.784333 0.841667\n", + "Ilha de Paquetá 0.775000 0.822000\n", + "Ilha do Governador 0.804625 0.859500\n", + "Zona Norte 0.777269 0.831149\n", + "Zona Oeste 0.753897 0.810862\n", + "Zona Portuária 0.722000 0.772500\n", + "Zona Sul 0.885125 0.929812" + ] + }, + "execution_count": 133, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df_variacao = df_idh.groupby(['Região', 'Ano'])['Índice de Desenvolvimento Humano Municipal (IDH)'].mean().unstack()\n", + "df_variacao" + ] + }, + { + "cell_type": "code", + "execution_count": 134, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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Ano19912000Variação
Região
Centro0.7843330.8416670.057333
Ilha de Paquetá0.7750000.8220000.047000
Ilha do Governador0.8046250.8595000.054875
Zona Norte0.7772690.8311490.053881
Zona Oeste0.7538970.8108620.056966
Zona Portuária0.7220000.7725000.050500
Zona Sul0.8851250.9298120.044687
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" + ], + "text/plain": [ + "Ano 1991 2000 Variação\n", + "Região \n", + "Centro 0.784333 0.841667 0.057333\n", + "Ilha de Paquetá 0.775000 0.822000 0.047000\n", + "Ilha do Governador 0.804625 0.859500 0.054875\n", + "Zona Norte 0.777269 0.831149 0.053881\n", + "Zona Oeste 0.753897 0.810862 0.056966\n", + "Zona Portuária 0.722000 0.772500 0.050500\n", + "Zona Sul 0.885125 0.929812 0.044687" + ] + }, + "execution_count": 134, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df_variacao['Variação'] = df_variacao[2000] - df_variacao[1991]\n", + "df_variacao" + ] + }, + { + "cell_type": "code", + "execution_count": 138, + "metadata": {}, + "outputs": [], + "source": [ + "df_variacao = df_variacao.reset_index()" + ] + }, + { + "cell_type": "code", + "execution_count": 139, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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AnoRegião19912000Variação
0Centro0.7843330.8416670.057333
4Zona Oeste0.7538970.8108620.056966
2Ilha do Governador0.8046250.8595000.054875
3Zona Norte0.7772690.8311490.053881
5Zona Portuária0.7220000.7725000.050500
1Ilha de Paquetá0.7750000.8220000.047000
6Zona Sul0.8851250.9298120.044687
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" + ], + "text/plain": [ + "Ano Região 1991 2000 Variação\n", + "0 Centro 0.784333 0.841667 0.057333\n", + "4 Zona Oeste 0.753897 0.810862 0.056966\n", + "2 Ilha do Governador 0.804625 0.859500 0.054875\n", + "3 Zona Norte 0.777269 0.831149 0.053881\n", + "5 Zona Portuária 0.722000 0.772500 0.050500\n", + "1 Ilha de Paquetá 0.775000 0.822000 0.047000\n", + "6 Zona Sul 0.885125 0.929812 0.044687" + ] + }, + "execution_count": 139, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df_variacao_ordenada = df_variacao.sort_values(by='Variação', ascending=False)\n", + "df_variacao_ordenada" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "As zonas que apresentam maior variação são: Centro, Zona Oeste e Ilha do Governador. " + ] + }, + { + "cell_type": "code", + "execution_count": 147, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plt.figure(figsize=(10, 6))\n", + "plt.plot(df_variacao_ordenada['Região'], df_variacao_ordenada['Variação'], marker='o', color='coral', linestyle='-')\n", + "plt.xticks(rotation=90)\n", + "plt.title('Variação dos Índices de IDH entre 1991 e 2000 por Região')\n", + "plt.xlabel('Região')\n", + "plt.ylabel('Variação (Índice 2000 - Índice 1991)')\n", + "plt.tight_layout()\n", + "plt.grid() \n", + "plt.show()\n" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "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": "3.12.3" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/material/IDH_1991.csv b/material/IDH_1991.csv new file mode 100644 index 0000000..afd3ac7 --- /dev/null +++ b/material/IDH_1991.csv @@ -0,0 +1,127 @@ +Ordem segundo o IDH;Bairro ou grupo de bairros;Esperana de vida ao nascer (em anos);Taxa de alfabetizao de adultos (%);Taxa bruta de frequncia escolar (%);Renda per capita (em R$ de 2000);ndice de Longevidade (IDH-L);ndice de Educao (IDH-E);ndice de Renda (IDH-R);ndice de Desenvolvimento Humano Municipal (IDH) +1;Gvea;75,11;97,25;100,64;1796,1;0,835;0,982;1;0,939 +2;Jardim Botnico;73,67;97,81;95,24;1620,82;0,811;0,97;1;0,927 +3;Ipanema;74;96,98;93,95;1606,88;0,817;0,96;1;0,925 +4;Leblon;73,67;97,49;92,23;1589,11;0,811;0,957;1;0,923 +5;Humait;72,8;97,93;102,67;1422,01;0,797;0,986;0,985;0,923 +6;Flamengo;72,94;98,25;103,5;1297,93;0,799;0,988;0,969;0,919 +7;Laranjeiras;73,67;98,01;101,66;1212,77;0,811;0,987;0,958;0,919 +8;Jo, Barra da Tijuca;72,9;96,86;91,83;1782,9;0,798;0,952;1;0,917 +9;Lagoa;72,94;97,24;89,04;2277,53;0,799;0,945;1;0,915 +10;Botafogo, Urca;74,09;96,82;95,29;1129,88;0,818;0,963;0,946;0,909 +11;Jardim Guanabara;75,39;97,89;95,98;909;0,84;0,973;0,91;0,907 +12;Leme;72,59;97,16;89,66;1307,33;0,793;0,947;0,971;0,903 +13;Copacabana;72,38;97,56;91,05;1250,6;0,79;0,954;0,963;0,902 +14;Maracan;74,17;97,94;100,26;843,6;0,82;0,986;0,897;0,901 +15;Mier;73,67;98,2;100,03;658,31;0,811;0,988;0,856;0,885 +16;Glria;72,23;98,02;88,74;918,9;0,787;0,949;0,912;0,883 +17;Graja;71,76;96,89;97,57;787,77;0,779;0,971;0,886;0,879 +18;Tijuca, Alto da Boa Vista;70,58;96,48;95,74;838,29;0,76;0,962;0,896;0,873 +19;Todos os Santos;72,92;98,09;95,72;574,31;0,799;0,973;0,833;0,868 +20;Andara;71,76;96,55;89,33;644,69;0,779;0,941;0,853;0,858 +21;Vila da Penha;72,12;98,03;94,24;491,56;0,785;0,968;0,807;0,853 +22;Catete;71,76;95,01;85,47;639,09;0,779;0,918;0,851;0,85 +23;Riachuelo;71,09;97,18;91,28;536,54;0,768;0,952;0,822;0,847 +24;Moner, Portuguesa;70,72;96,93;89,96;556,69;0,762;0,946;0,828;0,845 +25;Cachambi;70,24;97,43;95,48;497,91;0,754;0,968;0,809;0,844 +26;Freguesia (Jacarepagu);70,62;96,08;87,76;584,57;0,76;0,933;0,836;0,843 +27;Pechincha;70,47;97,12;87,99;554,56;0,758;0,941;0,827;0,842 +28;Vidigal, So Conrado;67,38;91,62;74,09;1198,69;0,706;0,858;0,956;0,84 +29;Vila Isabel;67,63;96,06;90,79;680,96;0,71;0,943;0,862;0,838 +30;Campinho, Vila Valqueire;71,76;96,57;87,95;435,78;0,779;0,937;0,787;0,835 +31;Anil;71,41;95,07;82,06;523,94;0,773;0,907;0,818;0,833 +32;Centro;70,47;96,13;80,03;495,18;0,758;0,908;0,809;0,825 +33;Higienpolis;69,02;96,98;89,12;400,62;0,734;0,944;0,773;0,817 +34;Bonsucesso;70,62;93,37;82,81;446,47;0,76;0,898;0,791;0,817 +35;gua Santa, Encantado;72,94;94,4;77,02;374,68;0,799;0,886;0,762;0,816 +36;Vila Cosmos;72,59;97,12;79,28;312,31;0,793;0,912;0,732;0,812 +37;Abolio;67,22;96,85;88,21;449,7;0,704;0,94;0,792;0,812 +38;Cocot, Bancrios;69,51;94,64;85,94;407,38;0,742;0,917;0,776;0,812 +39;Santa Teresa, Cosme Velho;68,6;94,1;75,47;540,84;0,727;0,879;0,823;0,81 +40;Taquara;70,62;94,79;80,24;368,62;0,76;0,899;0,759;0,806 +41;Engenho de Dentro;67,22;95,23;86,48;417,47;0,704;0,923;0,78;0,802 +42;Rio Comprido;67,74;93,99;83,62;433,54;0,712;0,905;0,786;0,801 +43;Ramos;69,02;96,48;80,6;367,02;0,734;0,912;0,759;0,801 +44;Olaria;69,6;95,76;80,84;351,4;0,743;0,908;0,751;0,801 +45;Lins de Vasconcelos;67,74;93,56;81,4;456,57;0,712;0,895;0,795;0,801 +46;Engenho Novo;67,38;94,35;79,75;438,03;0,706;0,895;0,788;0,796 +47;Praa Seca;67,74;94,19;86,27;366,78;0,712;0,915;0,758;0,795 +48;Ribeira, Cacuia;68,19;95,28;82,39;359,9;0,72;0,91;0,755;0,795 +49;Freguesia;68,06;93,93;78,75;410,25;0,718;0,889;0,777;0,794 +50;Jacar, Rocha, Sampaio;68,4;93,94;81,24;376,59;0,723;0,897;0,763;0,794 +51;Engenho da Rainha;69,95;95,13;80,78;310,48;0,749;0,903;0,731;0,794 +52;Zumbi, Pitangueiras, Praia da Bandeira;68,6;92,83;82,61;374,98;0,727;0,894;0,762;0,794 +53;Quintino Bocaiva;68,76;95,89;81,54;330,88;0,729;0,911;0,741;0,794 +54;Cidade Nova, Praa da Bandeira;65,74;94,81;84;436,87;0,679;0,912;0,788;0,793 +55;Oswaldo Cruz;69,6;95,68;83,18;290,23;0,743;0,915;0,719;0,793 +56;Madureira;68,61;95,47;80,74;337,86;0,727;0,906;0,745;0,792 +57;Piedade;67,38;96,06;82,44;355,52;0,706;0,915;0,753;0,792 +58;Itanhang;66,92;86,88;62,18;800,97;0,699;0,786;0,889;0,791 +59;Deodoro, Vila Militar, Campo dos Afonsos, Jardim Sulacap;70,82;95,9;78,49;272,37;0,764;0,901;0,709;0,791 +60;Pilares;69,74;95,72;80,1;294,62;0,746;0,905;0,722;0,791 +61;Bento Ribeiro;69,6;95,87;81,49;280,98;0,743;0,911;0,714;0,789 +62;Recreio dos Bandeirantes, Grumari;68,78;84,41;68,47;614,44;0,73;0,791;0,845;0,788 +63;Tanque;67,74;94,19;78,63;353,53;0,712;0,89;0,752;0,785 +64;Estcio;69,95;92,48;73,25;328,58;0,749;0,861;0,74;0,783 +65;Penha Circular;66,57;95,05;81,69;345,12;0,693;0,906;0,748;0,782 +66;Maria da Graa, Del Castilho;66,9;94,67;81,34;332,67;0,698;0,902;0,742;0,781 +67;Brs de Pina;67,38;95,3;83,15;294,81;0,706;0,913;0,722;0,78 +68;Jardim Amrica;68,19;95,11;81,67;277,04;0,72;0,906;0,712;0,779 +69;Jardim Carioca;66,68;94,12;75,11;359,83;0,695;0,878;0,755;0,776 +70;Cascadura;67,74;94,11;78,3;302,19;0,712;0,888;0,726;0,776 +71;Paquet;68,19;91,89;75,01;332,42;0,72;0,863;0,742;0,775 +72;Parque Anchieta;69,11;95,13;79,19;243,53;0,735;0,898;0,69;0,774 +73;So Cristvo, Vasco da Gama;66,65;93,82;77,28;324,48;0,694;0,883;0,738;0,772 +74;Coelho Neto;68,69;95,33;76,88;247,99;0,728;0,892;0,693;0,771 +75;Curicica;68,22;94,41;76,65;255,61;0,72;0,885;0,698;0,768 +76;Toms Coelho;66,6;94,51;84,03;252,46;0,693;0,91;0,696;0,767 +77;Inhama;67,93;93,72;75,51;260,46;0,715;0,877;0,701;0,764 +78;Turiau;67,93;93,92;74,5;263,45;0,715;0,874;0,703;0,764 +79;Rocha Miranda;68,33;94,94;75,96;232,86;0,722;0,886;0,683;0,764 +80;Tau;66,62;89,95;77,97;322,59;0,694;0,86;0,737;0,763 +81;Guadalupe;66,92;95,51;78,82;246,39;0,699;0,899;0,692;0,763 +82;Benfica;68,6;91,4;71,98;269,77;0,727;0,849;0,707;0,761 +83;Cavalcanti, Engenheiro Leal, Vaz Lobo;67,05;95,1;78,85;226,67;0,701;0,897;0,678;0,759 +84;Penha;65,57;93,39;75,57;299,1;0,676;0,875;0,724;0,758 +85;Pavuna;67,18;93,73;74,44;233,91;0,703;0,873;0,683;0,753 +86;Campo Grande;65,77;93,31;77,54;252,69;0,679;0,881;0,696;0,752 +87;Marechal Hermes;64,35;94,55;79,65;264,47;0,656;0,896;0,704;0,752 +88;Sade, Gamboa, Santo Cristo;66,92;92,04;70,67;269,06;0,699;0,849;0,707;0,752 +89;Ricardo de Albuquerque;66,62;94,52;76,21;218,11;0,694;0,884;0,672;0,75 +90;Realengo;65,79;94,19;76,39;237,95;0,68;0,883;0,686;0,749 +91;Magalhes Bastos;66,13;93,91;74,11;229,96;0,685;0,873;0,681;0,746 +92;Galeo, Cidade Universitria;64,61;92,87;76,24;260,33;0,66;0,873;0,701;0,745 +93;Catumbi;64,93;92,58;76,94;250,59;0,666;0,874;0,695;0,745 +94;Padre Miguel;67,3;93,28;70,79;212,23;0,705;0,858;0,667;0,743 +95;Senador Vasconcelos;66,62;91,88;74,82;215,53;0,694;0,862;0,67;0,742 +96;Bangu;65,64;93,01;74,43;217,91;0,677;0,868;0,672;0,739 +97;Vista Alegre, Iraj;57,04;96,73;83,62;353,93;0,534;0,924;0,752;0,737 +98;Mangueira, So Francisco Xavier;64,46;89,52;71,36;276,58;0,658;0,835;0,711;0,735 +99;Honrio Gurgel;64,69;94,03;70,92;225,3;0,662;0,863;0,677;0,734 +100;Cordovil;64,46;93,49;73,64;218,69;0,658;0,869;0,672;0,733 +101;Vicente de Carvalho;64,46;91,53;72,74;238,81;0,658;0,853;0,687;0,732 +102;Anchieta;65,45;93,24;71,04;189,64;0,674;0,858;0,648;0,727 +103;Jacarepagu;64,92;86,09;66,03;282,48;0,665;0,794;0,715;0,725 +104;Santssimo;64,93;91,78;74,26;184,52;0,666;0,859;0,644;0,723 +105;Senador Camar;64,32;90,31;67,96;188,38;0,655;0,829;0,647;0,71 +106;Colgio;62,87;90,57;66,15;219,45;0,631;0,824;0,673;0,709 +107;Camorim, Vargem Pequena, Vargem Grande;62,37;84,04;61,33;327,36;0,623;0,765;0,739;0,709 +108;Sepetiba;63,67;90,67;65,54;193,12;0,645;0,823;0,651;0,706 +109;Parada de Lucas;62,93;89,6;67,65;204,22;0,632;0,823;0,661;0,705 +110;Cosmos;64,5;91,04;64,74;162,91;0,658;0,823;0,623;0,701 +111;Gardnia Azul;63,19;86,26;71,13;196,17;0,637;0,812;0,654;0,701 +112;Vigrio Geral;62,51;92,28;66;176,96;0,625;0,835;0,637;0,699 +113;Pacincia;62,84;91,77;69,18;156,33;0,631;0,842;0,616;0,696 +114;Inhoaba;62,37;90,35;67,6;175,98;0,623;0,828;0,636;0,695 +115;Cidade de Deus;62,51;90,34;65,16;174,08;0,625;0,819;0,634;0,693 +116;Santa Cruz;62,49;90,26;66,16;170,16;0,625;0,822;0,63;0,692 +117;Caju;64,93;82,73;64,06;187,79;0,666;0,765;0,647;0,692 +118;Costa Barros;61,76;90,02;64,77;182,72;0,613;0,816;0,642;0,69 +119;Barros Filho;64,03;87,27;64,94;157,4;0,65;0,798;0,617;0,689 +120;Guaratiba, Barra de Guaratiba, Pedra de Guaratiba;62,37;87,55;64,59;168,54;0,623;0,799;0,629;0,683 +121;Jacarezinho;62,32;86,87;64,61;157,13;0,622;0,794;0,617;0,678 +122;Rocinha;65,15;81,49;54,47;170,57;0,669;0,725;0,631;0,675 +123;Manguinhos;62,32;85,92;62,98;157,26;0,622;0,783;0,617;0,674 +124;Mar;62,71;83,31;60,57;156,26;0,628;0,757;0,616;0,667 +125;Complexo do Alemo;62,36;83,6;56,52;144,01;0,623;0,746;0,602;0,657 +126;Acari, Parque Colmbia;60,29;86,21;60,57;147,17;0,588;0,777;0,606;0,657 diff --git a/material/IDH_2000.csv b/material/IDH_2000.csv new file mode 100644 index 0000000..9a6b6c4 --- /dev/null +++ b/material/IDH_2000.csv @@ -0,0 +1,127 @@ +Ordem segundo o IDH;Bairro ou grupo de bairros;Esperana de vida ao nascer (em anos);Taxa de alfabetizao de adultos (%);Taxa bruta de frequncia escolar (%);Renda per capita (em R$ de 2000);ndice de Longevidade (IDH-L);ndice de Educao (IDH-E);ndice de Renda (IDH-R);ndice de Desenvolvimento Humano Municipal (IDH) +1;Gvea;80,45;98,08;118,13;2139,56;0,924;0,987;1;0,97 +2;Leblon;79,47;99,01;105,18;2441,28;0,908;0,993;1;0,967 +3;Jardim Guanabara;80,47;98,92;111,15;1316,86;0,924;0,993;0,972;0,963 +4;Ipanema;78,68;98,78;107,98;2465,45;0,895;0,992;1;0,962 +5;Lagoa;77,91;99,46;115,26;2955,29;0,882;0,996;1;0,959 +6;Flamengo;77,91;99,28;119,08;1781,71;0,882;0,995;1;0,959 +7;Humait;77,91;99,28;122,2;1830,65;0,882;0,995;1;0,959 +8;Jo, Barra da Tijuca;77,84;99,38;110,09;2488,47;0,881;0,996;1;0,959 +9;Laranjeiras;77,84;98,74;115,98;1679,22;0,881;0,992;1;0,957 +10;Jardim Botnico;77,84;98,71;104,89;1952,77;0,881;0,991;1;0,957 +11;Copacabana;77,78;98,48;107,54;1623,42;0,88;0,99;1;0,956 +12;Leme;77,47;98,75;112,07;1713,89;0,875;0,992;1;0,955 +13;Botafogo, Urca;78,25;98,46;113,01;1376,47;0,888;0,99;0,979;0,952 +14;Maracan;77,91;98,91;113,97;1206,73;0,882;0,993;0,957;0,944 +15;Glria;77,37;99,06;114,55;1183,28;0,873;0,994;0,954;0,94 +16;Graja;77,84;97,9;107;1134,93;0,881;0,986;0,947;0,938 +17;Mier;77,37;99,01;108,63;1000,16;0,873;0,993;0,926;0,931 +18;Tijuca, Alto da Boa Vista;75,04;98,02;107,38;1204,61;0,834;0,987;0,957;0,926 +19;Todos os Santos;77,91;98,55;108,2;825,91;0,882;0,99;0,894;0,922 +20;Anil;77,15;97,3;101,85;768,26;0,869;0,982;0,882;0,911 +21;Vila da Penha;77,64;98,79;103,71;669,34;0,877;0,992;0,859;0,909 +22;Andara;74,99;98,05;103,85;897,07;0,833;0,987;0,908;0,909 +23;Riachuelo;76,44;98,31;102,75;715,92;0,857;0,989;0,87;0,905 +24;Campinho, Vila Valqueire;77,47;97,86;96,69;684,94;0,875;0,975;0,863;0,904 +25;Moner, Portuguesa;76,43;97,21;100,52;730,4;0,857;0,981;0,873;0,904 +26;Catete;74,99;96,65;100,4;822,22;0,833;0,978;0,893;0,901 +27;Vila Isabel;73,46;97,16;100,89;931,25;0,808;0,981;0,914;0,901 +28;Cachambi;75,7;98,14;102,23;709,05;0,845;0,988;0,868;0,9 +29;Pechincha;75,67;97,72;97,92;751,28;0,844;0,978;0,878;0,9 +30;Freguesia (Jacarepagu);75,07;97,46;98,82;766,82;0,834;0,979;0,882;0,898 +31;Recreio dos Bandeirantes, Grumari;72,55;95,03;91,75;1166,18;0,793;0,939;0,952;0,894 +32;Centro;76,12;97,58;99,24;633,36;0,852;0,981;0,85;0,894 +33;Higienpolis;74,06;97,46;100,28;614,41;0,818;0,983;0,845;0,882 +34;Santa Teresa, Cosme Velho;74,06;96,14;92,6;701,19;0,818;0,95;0,867;0,878 +35;gua Santa, Encantado;76,21;97,48;95,65;496,66;0,853;0,969;0,809;0,877 +36;Taquara;76,21;96,53;92,28;544,29;0,853;0,951;0,824;0,876 +37;Vila Cosmos;77,2;97,58;89,46;498,82;0,87;0,949;0,81;0,876 +38;Vidigal, So Conrado;71,12;94,76;82;1131,47;0,769;0,905;0,946;0,873 +39;Cidade Nova, Praa da Bandeira;72,05;96,29;96,84;640,31;0,784;0,965;0,851;0,867 +40;Bonsucesso;74,7;95,72;86,94;552,99;0,828;0,928;0,827;0,861 +41;Cocot, Bancrios;74,06;96,48;91,67;518,28;0,818;0,949;0,816;0,861 +42;Maria da Graa, Del Castilho;72,66;98,35;95,47;505,4;0,794;0,974;0,812;0,86 +43;Ribeira, Cacuia;72,85;96,48;95,37;527,2;0,797;0,961;0,819;0,859 +44;Lins de Vasconcelos;72,73;95,54;92,3;583,35;0,795;0,945;0,836;0,859 +45;Engenho Novo;72,37;96,29;93,33;573,33;0,789;0,953;0,833;0,858 +46;Zumbi, Pitangueiras, Praia da Bandeira;73,53;96,9;91,34;517,83;0,809;0,95;0,816;0,858 +47;Ramos;73,94;97,13;88,7;508,76;0,816;0,943;0,813;0,857 +48;Engenho de Dentro;72,66;96,67;92,77;536,54;0,794;0,954;0,822;0,857 +49;Abolio;73,28;97,07;95,69;467,23;0,805;0,966;0,799;0,857 +50;Deodoro, Vila Militar, Campo dos Afonsos, Jardim Sulacap;73,59;97,75;93,26;462,13;0,81;0,963;0,797;0,856 +51;Oswaldo Cruz;73,59;97,75;94,12;441,34;0,81;0,965;0,789;0,855 +52;Olaria;73,87;96,93;90,95;460,31;0,814;0,949;0,796;0,853 +53;Bento Ribeiro;75,05;97,95;88,15;399,85;0,834;0,947;0,773;0,851 +54;Piedade;72,66;97,08;95,51;447,64;0,794;0,966;0,792;0,85 +55;Quintino Bocaiva;73,91;96,8;91,97;424,67;0,815;0,952;0,783;0,85 +56;Rio Comprido;70,28;97;92,6;590,26;0,755;0,955;0,838;0,849 +57;Praa Seca;71,7;96,18;91,79;498,32;0,778;0,947;0,81;0,845 +58;Jardim Amrica;72,66;97,03;87,72;426,12;0,794;0,939;0,783;0,839 +59;Jacar, Rocha, Sampaio;70,64;95,9;90,65;513,62;0,761;0,941;0,815;0,839 +60;Freguesia;70,28;95,23;89,35;557,35;0,755;0,933;0,828;0,839 +61;Jardim Carioca;72,66;95,97;86,23;436,33;0,794;0,927;0,787;0,836 +62;Engenho da Rainha;73,36;96,93;89,2;362,62;0,806;0,944;0,757;0,835 +63;Brs de Pina;72,66;96,45;88,41;397,15;0,794;0,938;0,772;0,835 +64;So Cristvo, Vasco da Gama;72,27;95,44;89,08;412,39;0,788;0,933;0,778;0,833 +65;Cascadura;72,15;95,97;86,35;428,76;0,786;0,928;0,785;0,833 +66;Parque Anchieta;73,71;96,31;87,17;355,31;0,812;0,933;0,753;0,833 +67;Madureira;70,97;96,81;90,42;419,81;0,766;0,947;0,781;0,831 +68;Pilares;72,55;96,79;86,05;389,81;0,793;0,932;0,769;0,831 +69;Tanque;71,49;95,95;86,87;439,87;0,775;0,929;0,789;0,831 +70;Estcio;73,71;94,09;80,82;413,05;0,812;0,897;0,778;0,829 +71;Curicica;72,57;96,15;88,33;362,72;0,793;0,935;0,757;0,828 +72;Penha Circular;71,15;96,23;83,38;444,77;0,769;0,919;0,791;0,826 +73;Benfica;73,59;94,5;81,35;376,65;0,81;0,901;0,763;0,825 +74;Paquet;74,06;94,22;67,66;457,61;0,818;0,854;0,795;0,822 +75;Itanhang;70,28;91,44;74,3;650,96;0,755;0,857;0,854;0,822 +76;Tau;71,24;93,2;83,99;416,19;0,771;0,901;0,78;0,817 +77;Rocha Miranda;70,99;96,62;87,07;338,1;0,766;0,934;0,745;0,815 +78;Marechal Hermes;70,11;96,09;87,78;366,28;0,752;0,933;0,758;0,814 +79;Turiau;70,11;97,37;87,15;336,57;0,752;0,94;0,744;0,812 +80;Guadalupe;70,11;97,27;85,58;336,89;0,752;0,934;0,744;0,81 +81;Inhama;70,64;96,39;86,56;324,3;0,761;0,931;0,738;0,81 +82;Campo Grande;69,8;95,98;87,42;351,11;0,747;0,931;0,751;0,81 +83;Cavalcanti, Engenheiro Leal, Vaz Lobo;70,41;96,29;84,68;328,64;0,757;0,924;0,74;0,807 +84;Ricardo de Albuquerque;70,97;96,42;89,06;283;0,766;0,94;0,715;0,807 +85;Coelho Neto;70,86;96,88;84,77;299,89;0,764;0,928;0,725;0,806 +86;Padre Miguel;70,11;95,72;87,21;313,85;0,752;0,929;0,732;0,804 +87;Penha;69,59;95,12;82,23;373,05;0,743;0,908;0,761;0,804 +88;Honrio Gurgel;69,88;96,56;88,09;303,98;0,748;0,937;0,727;0,804 +89;Realengo;69,63;95,97;87,44;316,41;0,744;0,931;0,734;0,803 +90;Senador Vasconcelos;69,68;95,88;88,68;302,44;0,745;0,935;0,726;0,802 +91;Toms Coelho;69,88;95,89;83,8;325,92;0,748;0,919;0,739;0,802 +92;Magalhes Bastos;68,9;95,72;90,24;318,03;0,732;0,939;0,735;0,802 +93;Catumbi;69,6;95,81;85,41;324,83;0,743;0,923;0,738;0,802 +94;Mangueira, So Francisco Xavier;68,34;94,2;88,51;357,43;0,722;0,923;0,754;0,8 +95;Vista Alegre, Iraj;62,81;98,08;92,99;473,39;0,63;0,964;0,801;0,798 +96;Bangu;69,78;95,45;82,95;296,55;0,746;0,913;0,723;0,794 +97;Sade, Gamboa, Santo Cristo;70,28;94,21;77,52;320,57;0,755;0,886;0,736;0,792 +98;Cordovil;68,32;95,83;87,92;290,49;0,722;0,932;0,72;0,791 +99;Pavuna;69,27;95,96;82,51;286,38;0,738;0,915;0,717;0,79 +100;Anchieta;68,9;95,65;84,75;278,18;0,732;0,92;0,712;0,788 +101;Santssimo;69,36;95,04;80,94;256,08;0,739;0,903;0,698;0,78 +102;Galeo, Cidade Universitria;67,79;93,92;80,64;300,31;0,713;0,895;0,725;0,778 +103;Vicente de Carvalho;67,51;93,79;78,52;296,63;0,709;0,887;0,723;0,773 +104;Jacarepagu;67,51;90,18;77,14;331,44;0,709;0,858;0,742;0,769 +105;Senador Camar;67,39;93,63;83,67;251,09;0,707;0,903;0,695;0,768 +106;Gardnia Azul;67,79;93,78;76,4;274,68;0,713;0,88;0,71;0,768 +107;Vigrio Geral;66,66;93,52;74,73;296,6;0,694;0,873;0,723;0,763 +108;Colgio;67,33;94,52;74,33;262,37;0,706;0,878;0,703;0,762 +109;Sepetiba;66,3;93,64;79,65;264,8;0,688;0,89;0,704;0,761 +110;Cosmos;67,51;94,86;82,17;205,9;0,709;0,906;0,662;0,759 +111;Caju;68,9;90,43;71,97;236,59;0,732;0,843;0,685;0,753 +112;Pacincia;66,66;94,36;81,02;203,43;0,694;0,899;0,66;0,751 +113;Cidade de Deus;66,66;93,56;81,1;207,56;0,694;0,894;0,663;0,751 +114;Barros Filho;66,66;93,6;82,15;198,96;0,694;0,898;0,656;0,75 +115;Inhoaba;65,99;93,63;81,38;207,61;0,683;0,895;0,663;0,747 +116;Camorim, Vargem Pequena, Vargem Grande;66,3;90,8;69,28;279,09;0,688;0,836;0,713;0,746 +117;Parada de Lucas;65,35;92,38;82,15;220,27;0,672;0,89;0,673;0,745 +118;Guaratiba, Barra de Guaratiba, Pedra de Guaratiba;66,66;90,74;74,37;234,37;0,694;0,853;0,684;0,744 +119;Santa Cruz;65,52;93,19;79,82;206,23;0,675;0,887;0,662;0,742 +120;Rocinha;67,33;87,9;69,5;219,95;0,706;0,818;0,673;0,732 +121;Jacarezinho;66,3;92,2;75,68;177,98;0,688;0,867;0,638;0,731 +122;Manguinhos;66,3;91,48;69,64;188,86;0,688;0,842;0,648;0,726 +123;Mar;66,58;89,46;68,76;187,25;0,693;0,826;0,646;0,722 +124;Acari, Parque Colmbia;63,93;91,68;79,44;174,12;0,649;0,876;0,634;0,72 +125;Costa Barros;63,93;91,34;74,09;175;0,649;0,856;0,635;0,713 +126;Complexo do Alemo;64,79;89,07;72,04;177,31;0,663;0,834;0,637;0,711 diff --git a/material /nome-projeto.md b/material/IDH_RJ.md similarity index 50% rename from material /nome-projeto.md rename to material/IDH_RJ.md index 3df5cb3..de49e0d 100644 --- a/material /nome-projeto.md +++ b/material/IDH_RJ.md @@ -1,37 +1,36 @@ -# Projeto Final de Análise de Dados - -## Contexto -Este projeto consiste na análise de **[escolha o tema do seu projeto, por exemplo: dados educacionais do ENEM]**. - -## Etapas do projeto: -1. **Selecionar a Base de Dados** [Escolher e explorar a base de dados relevante ao tema.] -2. **Definir Objetivo e Perguntas** [Estabelecer o objetivo e formular perguntas-chave com base nas variáveis disponíveis.] -3. **Realizar Análise Exploratória** [Identificar correlações, padrões e outliers nos dados.] -4. **Gerar Base Final** [Limpar e estruturar os dados para a visualização.] -5. **Criar Visualizações no Tableau** [Desenvolver gráficos que sintetizem os principais insights.] -6. **Preparar Apresentação Final** [Apresentar o tema, dados e visualizações de forma clara e objetiva.] - ---- - -## Bases Escolhidas -- **Base 1**: [Nome da base de dados e fonte (por exemplo, Microdados do ENEM, INEP)] -- **Base 2**: [Nome da base de dados e fonte (opcional, caso use outra base complementar)] - ---- - -### Objetivo Geral: -Realizar uma análise dos dados com o objetivo de **[escreva o objetivo do seu projeto, por exemplo: identificar as variáveis que influenciam o desempenho dos alunos no ENEM]**. - -### As perguntas norteadoras deste projeto são: -1. **[Pergunta sobre o perfil dos dados]** - Quais são as principais características da base de dados selecionada? -2. **[Pergunta comparativa]** - Há diferenças de desempenho entre os grupos de interesse (ex.: escolas públicas vs. privadas)? -3. **[Pergunta relacional]** - Existe correlação entre fatores socioeconômicos e os resultados dos alunos? -4. **[Pergunta exploratória]** - Quais insights podem ser extraídos a partir dos padrões identificados nos dados? - ---- - -## Ferramentas Utilizadas -- **Python (Jupyter Notebook)**: Para a análise exploratória de dados utilizando bibliotecas como Pandas, Seaborn, Matplotlib, etc. -- **Tableau**: Para criar as visualizações finais e apresentar os insights gerados. -- **GitHub**: Para versionamento do projeto e documentação. -- **Google Colab** (opcional): Para execução de notebooks de forma colaborativa e em nuvem. +# Projeto Final de Análise de Dados + +## Contexto +Este projeto consiste na análise de Índice de Desenvolvimento Humano (IDH) Municipal, por Regiões no Município do Rio de Janeiro em 1991/2000. + +## Etapas do projeto: +1. **Selecionar a Base de Dados** [Escolher e explorar a base de dados relevante ao tema.] +2. **Definir Objetivo e Perguntas** [Estabelecer o objetivo e formular perguntas-chave com base nas variáveis disponíveis.] +3. **Realizar Análise Exploratória** [Identificar correlações, padrões e outliers nos dados.] +4. **Gerar Base Final** [Limpar e estruturar os dados para a visualização.] +5. **Criar Visualizações no Tableau** [Desenvolver gráficos que sintetizem os principais insights.] +6. **Preparar Apresentação Final** [Apresentar o tema, dados e visualizações de forma clara e objetiva.] + +--- + +## Bases Escolhidas +- **Base 1**: Índice de Desenvolvimento Humano (IDH) Municipal, por ordem de IDH, segundo os Bairros ou grupo de Bairros, no Município do Rio de Janeiro em 1991/2000. Fonte: DataRio + +--- + +### Objetivo Geral: +Realizar uma análise dos dados com o objetivo de entender se a região de habitação influencia nos indicadores de IDH.. + +### As perguntas norteadoras deste projeto são: +1. Qual é a média dos principais indicadores de IDH (índice de longevidade, índice de educação e índice de renda) em cada região do Rio de Janeiro (zona oeste, zona norte, zona sul, etc.) nos anos de 1991 e 2000? +2. Qual é a dispersão dos indicadores de IDH dentro de uma mesma zona? Existe desigualdade interna? +3. Quais zonas apresentam a maior variação nos indicadores de IDH entre 1991 e 2000? + + +--- + +## Ferramentas Utilizadas +- **Python (Jupyter Notebook)**: Para a análise exploratória de dados utilizando bibliotecas como Pandas, Seaborn, Matplotlib, etc. +- **Tableau**: Para criar as visualizações finais e apresentar os insights gerados. +- **GitHub**: Para versionamento do projeto e documentação. +- **Visual Studio Code** (opcional): Para execução de notebooks de forma colaborativa e em nuvem. diff --git a/material/base_final_idh.csv b/material/base_final_idh.csv new file mode 100644 index 0000000..19d2114 --- /dev/null +++ b/material/base_final_idh.csv @@ -0,0 +1,253 @@ +,Ordem segundo o IDH,Bairro ou grupo de bairros,Esperança de vida ao nascer (em anos),Taxa de alfabetização de adultos (%),Taxa bruta de frequência escolar (%),Renda per capita (em R$ de 2000),Índice de Longevidade (IDH-L),Índice de Educação (IDH-E),Índice de Renda (IDH-R),Índice de Desenvolvimento Humano Municipal (IDH),Ano,Região +0,1,Gávea,75.11,97.25,100.64,1796.1,0.835,0.982,1.0,0.939,1991,Zona Sul +1,2,Jardim Botânico,73.67,97.81,95.24,1620.82,0.811,0.97,1.0,0.927,1991,Zona Sul +2,3,Ipanema,74.0,96.98,93.95,1606.88,0.817,0.96,1.0,0.925,1991,Zona Sul +3,4,Leblon,73.67,97.49,92.23,1589.11,0.811,0.957,1.0,0.923,1991,Zona Sul +4,5,Humaitá,72.8,97.93,102.67,1422.01,0.797,0.986,0.985,0.923,1991,Zona Sul +5,6,Flamengo,72.94,98.25,103.5,1297.93,0.799,0.988,0.969,0.919,1991,Zona Sul +6,7,Laranjeiras,73.67,98.01,101.66,1212.77,0.811,0.987,0.958,0.919,1991,Zona Sul +7,8,Joá. Barra da Tijuca,72.9,96.86,91.83,1782.9,0.798,0.952,1.0,0.917,1991,Zona Oeste +8,9,Lagoa,72.94,97.24,89.04,2277.53,0.799,0.945,1.0,0.915,1991,Zona Sul +9,10,Botafogo. Urca,74.09,96.82,95.29,1129.88,0.818,0.963,0.946,0.909,1991,Zona Sul +10,11,Jardim Guanabara,75.39,97.89,95.98,909.0,0.84,0.973,0.91,0.907,1991,Ilha do Governador +11,12,Leme,72.59,97.16,89.66,1307.33,0.793,0.947,0.971,0.903,1991,Zona Sul +12,13,Copacabana,72.38,97.56,91.05,1250.6,0.79,0.954,0.963,0.902,1991,Zona Sul +13,14,Maracanã,74.17,97.94,100.26,843.6,0.82,0.986,0.897,0.901,1991,Zona Norte +14,15,Méier,73.67,98.2,100.03,658.31,0.811,0.988,0.856,0.885,1991,Zona Norte +15,16,Glória,72.23,98.02,88.74,918.9,0.787,0.949,0.912,0.883,1991,Zona Sul +16,17,Grajaú,71.76,96.89,97.57,787.77,0.779,0.971,0.886,0.879,1991,Zona Norte +17,18,Tijuca. Alto da Boa Vista,70.58,96.48,95.74,838.29,0.76,0.962,0.896,0.873,1991,Zona Norte +18,19,Todos os Santos,72.92,98.09,95.72,574.31,0.799,0.973,0.833,0.868,1991,Zona Norte +19,20,Andaraí,71.76,96.55,89.33,644.69,0.779,0.941,0.853,0.858,1991,Zona Norte +20,21,Vila da Penha,72.12,98.03,94.24,491.56,0.785,0.968,0.807,0.853,1991,Zona Norte +21,22,Catete,71.76,95.01,85.47,639.09,0.779,0.918,0.851,0.85,1991,Zona Sul +22,23,Riachuelo,71.09,97.18,91.28,536.54,0.768,0.952,0.822,0.847,1991,Zona Norte +23,24,Moneró. Portuguesa,70.72,96.93,89.96,556.69,0.762,0.946,0.828,0.845,1991,Ilha do Governador +24,25,Cachambi,70.24,97.43,95.48,497.91,0.754,0.968,0.809,0.844,1991,Zona Norte +25,26,Freguesia (Jacarepaguá),70.62,96.08,87.76,584.57,0.76,0.933,0.836,0.843,1991,Zona Oeste +26,27,Pechincha,70.47,97.12,87.99,554.56,0.758,0.941,0.827,0.842,1991,Zona Oeste +27,28,Vidigal. São Conrado,67.38,91.62,74.09,1198.69,0.706,0.858,0.956,0.84,1991,Zona Sul +28,29,Vila Isabel,67.63,96.06,90.79,680.96,0.71,0.943,0.862,0.838,1991,Zona Norte +29,30,Campinho. Vila Valqueire,71.76,96.57,87.95,435.78,0.779,0.937,0.787,0.835,1991,Zona Norte +30,31,Anil,71.41,95.07,82.06,523.94,0.773,0.907,0.818,0.833,1991,Zona Oeste +31,32,Centro,70.47,96.13,80.03,495.18,0.758,0.908,0.809,0.825,1991,Centro +32,33,Higienópolis,69.02,96.98,89.12,400.62,0.734,0.944,0.773,0.817,1991,Zona Norte +33,34,Bonsucesso,70.62,93.37,82.81,446.47,0.76,0.898,0.791,0.817,1991,Zona Norte +34,35,Água Santa. Encantado,72.94,94.4,77.02,374.68,0.799,0.886,0.762,0.816,1991,Zona Norte +35,36,Vila Cosmos,72.59,97.12,79.28,312.31,0.793,0.912,0.732,0.812,1991,Zona Norte +36,37,Abolição,67.22,96.85,88.21,449.7,0.704,0.94,0.792,0.812,1991,Zona Norte +37,38,Cocotá. Bancários,69.51,94.64,85.94,407.38,0.742,0.917,0.776,0.812,1991,Ilha do Governador +38,39,Santa Teresa. Cosme Velho,68.6,94.1,75.47,540.84,0.727,0.879,0.823,0.81,1991,Zona Sul +39,40,Taquara,70.62,94.79,80.24,368.62,0.76,0.899,0.759,0.806,1991,Zona Oeste +40,41,Engenho de Dentro,67.22,95.23,86.48,417.47,0.704,0.923,0.78,0.802,1991,Zona Norte +41,42,Rio Comprido,67.74,93.99,83.62,433.54,0.712,0.905,0.786,0.801,1991,Zona Norte +42,43,Ramos,69.02,96.48,80.6,367.02,0.734,0.912,0.759,0.801,1991,Zona Norte +43,44,Olaria,69.6,95.76,80.84,351.4,0.743,0.908,0.751,0.801,1991,Zona Norte +44,45,Lins de Vasconcelos,67.74,93.56,81.4,456.57,0.712,0.895,0.795,0.801,1991,Zona Norte +45,46,Engenho Novo,67.38,94.35,79.75,438.03,0.706,0.895,0.788,0.796,1991,Zona Norte +46,47,Praça Seca,67.74,94.19,86.27,366.78,0.712,0.915,0.758,0.795,1991,Zona Norte +47,48,Ribeira. Cacuia,68.19,95.28,82.39,359.9,0.72,0.91,0.755,0.795,1991,Ilha do Governador +48,49,Freguesia,68.06,93.93,78.75,410.25,0.718,0.889,0.777,0.794,1991,Zona Oeste +49,50,Jacaré. Rocha. Sampaio,68.4,93.94,81.24,376.59,0.723,0.897,0.763,0.794,1991,Zona Norte +50,51,Engenho da Rainha,69.95,95.13,80.78,310.48,0.749,0.903,0.731,0.794,1991,Zona Norte +51,52,Zumbi. Pitangueiras. Praia da Bandeira,68.6,92.83,82.61,374.98,0.727,0.894,0.762,0.794,1991,Ilha do Governador +52,53,Quintino Bocaiúva,68.76,95.89,81.54,330.88,0.729,0.911,0.741,0.794,1991,Zona Norte +53,54,Cidade Nova. Praça da Bandeira,65.74,94.81,84.0,436.87,0.679,0.912,0.788,0.793,1991,Zona Norte +54,55,Oswaldo Cruz,69.6,95.68,83.18,290.23,0.743,0.915,0.719,0.793,1991,Zona Norte +55,56,Madureira,68.61,95.47,80.74,337.86,0.727,0.906,0.745,0.792,1991,Zona Norte +56,57,Piedade,67.38,96.06,82.44,355.52,0.706,0.915,0.753,0.792,1991,Zona Norte +57,58,Itanhangá,66.92,86.88,62.18,800.97,0.699,0.786,0.889,0.791,1991,Zona Oeste +58,59,Deodoro. Vila Militar. Campo dos Afonsos. Jardim Sulacap,70.82,95.9,78.49,272.37,0.764,0.901,0.709,0.791,1991,Zona Oeste +59,60,Pilares,69.74,95.72,80.1,294.62,0.746,0.905,0.722,0.791,1991,Zona Norte +60,61,Bento Ribeiro,69.6,95.87,81.49,280.98,0.743,0.911,0.714,0.789,1991,Zona Norte +61,62,Recreio dos Bandeirantes. Grumari,68.78,84.41,68.47,614.44,0.73,0.791,0.845,0.788,1991,Zona Oeste +62,63,Tanque,67.74,94.19,78.63,353.53,0.712,0.89,0.752,0.785,1991,Zona Oeste +63,64,Estácio,69.95,92.48,73.25,328.58,0.749,0.861,0.74,0.783,1991,Centro +64,65,Penha Circular,66.57,95.05,81.69,345.12,0.693,0.906,0.748,0.782,1991,Zona Norte +65,66,Maria da Graça. Del Castilho,66.9,94.67,81.34,332.67,0.698,0.902,0.742,0.781,1991,Zona Norte +66,67,Brás de Pina,67.38,95.3,83.15,294.81,0.706,0.913,0.722,0.78,1991,Zona Norte +67,68,Jardim América,68.19,95.11,81.67,277.04,0.72,0.906,0.712,0.779,1991,Zona Norte +68,69,Jardim Carioca,66.68,94.12,75.11,359.83,0.695,0.878,0.755,0.776,1991,Ilha do Governador +69,70,Cascadura,67.74,94.11,78.3,302.19,0.712,0.888,0.726,0.776,1991,Zona Norte +70,71,Paquetá,68.19,91.89,75.01,332.42,0.72,0.863,0.742,0.775,1991,Ilha de Paquetá +71,72,Parque Anchieta,69.11,95.13,79.19,243.53,0.735,0.898,0.69,0.774,1991,Zona Norte +72,73,São Cristóvão. Vasco da Gama,66.65,93.82,77.28,324.48,0.694,0.883,0.738,0.772,1991,Zona Norte +73,74,Coelho Neto,68.69,95.33,76.88,247.99,0.728,0.892,0.693,0.771,1991,Zona Norte +74,75,Curicica,68.22,94.41,76.65,255.61,0.72,0.885,0.698,0.768,1991,Zona Oeste +75,76,Tomás Coelho,66.6,94.51,84.03,252.46,0.693,0.91,0.696,0.767,1991,Zona Norte +76,77,Inhaúma,67.93,93.72,75.51,260.46,0.715,0.877,0.701,0.764,1991,Zona Norte +77,78,Turiaçu,67.93,93.92,74.5,263.45,0.715,0.874,0.703,0.764,1991,Zona Norte +78,79,Rocha Miranda,68.33,94.94,75.96,232.86,0.722,0.886,0.683,0.764,1991,Zona Norte +79,80,Tauá,66.62,89.95,77.97,322.59,0.694,0.86,0.737,0.763,1991,Ilha do Governador +80,81,Guadalupe,66.92,95.51,78.82,246.39,0.699,0.899,0.692,0.763,1991,Zona Norte +81,82,Benfica,68.6,91.4,71.98,269.77,0.727,0.849,0.707,0.761,1991,Zona Norte +82,83,Cavalcanti. Engenheiro Leal. Vaz Lobo,67.05,95.1,78.85,226.67,0.701,0.897,0.678,0.759,1991,Zona Norte +83,84,Penha,65.57,93.39,75.57,299.1,0.676,0.875,0.724,0.758,1991,Zona Norte +84,85,Pavuna,67.18,93.73,74.44,233.91,0.703,0.873,0.683,0.753,1991,Zona Norte +85,86,Campo Grande,65.77,93.31,77.54,252.69,0.679,0.881,0.696,0.752,1991,Zona Oeste +86,87,Marechal Hermes,64.35,94.55,79.65,264.47,0.656,0.896,0.704,0.752,1991,Zona Norte +87,88,Saúde. Gamboa. Santo Cristo,66.92,92.04,70.67,269.06,0.699,0.849,0.707,0.752,1991,Zona Portuária +88,89,Ricardo de Albuquerque,66.62,94.52,76.21,218.11,0.694,0.884,0.672,0.75,1991,Zona Norte +89,90,Realengo,65.79,94.19,76.39,237.95,0.68,0.883,0.686,0.749,1991,Zona Oeste +90,91,Magalhães Bastos,66.13,93.91,74.11,229.96,0.685,0.873,0.681,0.746,1991,Zona Oeste +91,92,Galeão. Cidade Universitária,64.61,92.87,76.24,260.33,0.66,0.873,0.701,0.745,1991,Ilha do Governador +92,93,Catumbi,64.93,92.58,76.94,250.59,0.666,0.874,0.695,0.745,1991,Centro +93,94,Padre Miguel,67.3,93.28,70.79,212.23,0.705,0.858,0.667,0.743,1991,Zona Oeste +94,95,Senador Vasconcelos,66.62,91.88,74.82,215.53,0.694,0.862,0.67,0.742,1991,Zona Oeste +95,96,Bangu,65.64,93.01,74.43,217.91,0.677,0.868,0.672,0.739,1991,Zona Oeste +96,97,Vista Alegre. Irajá,57.04,96.73,83.62,353.93,0.534,0.924,0.752,0.737,1991,Zona Norte +97,98,Mangueira. São Francisco Xavier,64.46,89.52,71.36,276.58,0.658,0.835,0.711,0.735,1991,Zona Norte +98,99,Honório Gurgel,64.69,94.03,70.92,225.3,0.662,0.863,0.677,0.734,1991,Zona Norte +99,100,Cordovil,64.46,93.49,73.64,218.69,0.658,0.869,0.672,0.733,1991,Zona Norte +100,101,Vicente de Carvalho,64.46,91.53,72.74,238.81,0.658,0.853,0.687,0.732,1991,Zona Norte +101,102,Anchieta,65.45,93.24,71.04,189.64,0.674,0.858,0.648,0.727,1991,Zona Norte +102,103,Jacarepaguá,64.92,86.09,66.03,282.48,0.665,0.794,0.715,0.725,1991,Zona Oeste +103,104,Santíssimo,64.93,91.78,74.26,184.52,0.666,0.859,0.644,0.723,1991,Zona Oeste +104,105,Senador Camará,64.32,90.31,67.96,188.38,0.655,0.829,0.647,0.71,1991,Zona Oeste +105,106,Colégio,62.87,90.57,66.15,219.45,0.631,0.824,0.673,0.709,1991,Zona Norte +106,107,Camorim. Vargem Pequena. Vargem Grande,62.37,84.04,61.33,327.36,0.623,0.765,0.739,0.709,1991,Zona Oeste +107,108,Sepetiba,63.67,90.67,65.54,193.12,0.645,0.823,0.651,0.706,1991,Zona Oeste +108,109,Parada de Lucas,62.93,89.6,67.65,204.22,0.632,0.823,0.661,0.705,1991,Zona Norte +109,110,Cosmos,64.5,91.04,64.74,162.91,0.658,0.823,0.623,0.701,1991,Zona Oeste +110,111,Gardênia Azul,63.19,86.26,71.13,196.17,0.637,0.812,0.654,0.701,1991,Zona Oeste +111,112,Vigário Geral,62.51,92.28,66.0,176.96,0.625,0.835,0.637,0.699,1991,Zona Norte +112,113,Paciência,62.84,91.77,69.18,156.33,0.631,0.842,0.616,0.696,1991,Zona Oeste +113,114,Inhoaíba,62.37,90.35,67.6,175.98,0.623,0.828,0.636,0.695,1991,Zona Oeste +114,115,Cidade de Deus,62.51,90.34,65.16,174.08,0.625,0.819,0.634,0.693,1991,Zona Oeste +115,116,Santa Cruz,62.49,90.26,66.16,170.16,0.625,0.822,0.63,0.692,1991,Zona Oeste +116,117,Caju,64.93,82.73,64.06,187.79,0.666,0.765,0.647,0.692,1991,Zona Portuária +117,118,Costa Barros,61.76,90.02,64.77,182.72,0.613,0.816,0.642,0.69,1991,Zona Norte +118,119,Barros Filho,64.03,87.27,64.94,157.4,0.65,0.798,0.617,0.689,1991,Zona Norte +119,120,Guaratiba. Barra de Guaratiba. Pedra de Guaratiba,62.37,87.55,64.59,168.54,0.623,0.799,0.629,0.683,1991,Zona Oeste +120,121,Jacarezinho,62.32,86.87,64.61,157.13,0.622,0.794,0.617,0.678,1991,Zona Norte +121,122,Rocinha,65.15,81.49,54.47,170.57,0.669,0.725,0.631,0.675,1991,Zona Sul +122,123,Manguinhos,62.32,85.92,62.98,157.26,0.622,0.783,0.617,0.674,1991,Zona Norte +123,124,Maré,62.71,83.31,60.57,156.26,0.628,0.757,0.616,0.667,1991,Zona Norte +124,125,Complexo do Alemão,62.36,83.6,56.52,144.01,0.623,0.746,0.602,0.657,1991,Zona Norte +125,126,Acari. Parque Colúmbia,60.29,86.21,60.57,147.17,0.588,0.777,0.606,0.657,1991,Zona Norte +126,1,Gávea,80.45,98.08,118.13,2139.56,0.924,0.987,1.0,0.97,2000,Zona Sul +127,2,Leblon,79.47,99.01,105.18,2441.28,0.908,0.993,1.0,0.967,2000,Zona Sul +128,3,Jardim Guanabara,80.47,98.92,111.15,1316.86,0.924,0.993,0.972,0.963,2000,Ilha do Governador +129,4,Ipanema,78.68,98.78,107.98,2465.45,0.895,0.992,1.0,0.962,2000,Zona Sul +130,5,Lagoa,77.91,99.46,115.26,2955.29,0.882,0.996,1.0,0.959,2000,Zona Sul +131,6,Flamengo,77.91,99.28,119.08,1781.71,0.882,0.995,1.0,0.959,2000,Zona Sul +132,7,Humaitá,77.91,99.28,122.2,1830.65,0.882,0.995,1.0,0.959,2000,Zona Sul +133,8,Joá. Barra da Tijuca,77.84,99.38,110.09,2488.47,0.881,0.996,1.0,0.959,2000,Zona Oeste +134,9,Laranjeiras,77.84,98.74,115.98,1679.22,0.881,0.992,1.0,0.957,2000,Zona Sul +135,10,Jardim Botânico,77.84,98.71,104.89,1952.77,0.881,0.991,1.0,0.957,2000,Zona Sul +136,11,Copacabana,77.78,98.48,107.54,1623.42,0.88,0.99,1.0,0.956,2000,Zona Sul +137,12,Leme,77.47,98.75,112.07,1713.89,0.875,0.992,1.0,0.955,2000,Zona Sul +138,13,Botafogo. Urca,78.25,98.46,113.01,1376.47,0.888,0.99,0.979,0.952,2000,Zona Sul +139,14,Maracanã,77.91,98.91,113.97,1206.73,0.882,0.993,0.957,0.944,2000,Zona Norte +140,15,Glória,77.37,99.06,114.55,1183.28,0.873,0.994,0.954,0.94,2000,Zona Sul +141,16,Grajaú,77.84,97.9,107.0,1134.93,0.881,0.986,0.947,0.938,2000,Zona Norte +142,17,Méier,77.37,99.01,108.63,1000.16,0.873,0.993,0.926,0.931,2000,Zona Norte +143,18,Tijuca. Alto da Boa Vista,75.04,98.02,107.38,1204.61,0.834,0.987,0.957,0.926,2000,Zona Norte +144,19,Todos os Santos,77.91,98.55,108.2,825.91,0.882,0.99,0.894,0.922,2000,Zona Norte +145,20,Anil,77.15,97.3,101.85,768.26,0.869,0.982,0.882,0.911,2000,Zona Oeste +146,21,Vila da Penha,77.64,98.79,103.71,669.34,0.877,0.992,0.859,0.909,2000,Zona Norte +147,22,Andaraí,74.99,98.05,103.85,897.07,0.833,0.987,0.908,0.909,2000,Zona Norte +148,23,Riachuelo,76.44,98.31,102.75,715.92,0.857,0.989,0.87,0.905,2000,Zona Norte +149,24,Campinho. Vila Valqueire,77.47,97.86,96.69,684.94,0.875,0.975,0.863,0.904,2000,Zona Norte +150,25,Moneró. Portuguesa,76.43,97.21,100.52,730.4,0.857,0.981,0.873,0.904,2000,Ilha do Governador +151,26,Catete,74.99,96.65,100.4,822.22,0.833,0.978,0.893,0.901,2000,Zona Sul +152,27,Vila Isabel,73.46,97.16,100.89,931.25,0.808,0.981,0.914,0.901,2000,Zona Norte +153,28,Cachambi,75.7,98.14,102.23,709.05,0.845,0.988,0.868,0.9,2000,Zona Norte +154,29,Pechincha,75.67,97.72,97.92,751.28,0.844,0.978,0.878,0.9,2000,Zona Oeste +155,30,Freguesia (Jacarepaguá),75.07,97.46,98.82,766.82,0.834,0.979,0.882,0.898,2000,Zona Oeste +156,31,Recreio dos Bandeirantes. Grumari,72.55,95.03,91.75,1166.18,0.793,0.939,0.952,0.894,2000,Zona Oeste +157,32,Centro,76.12,97.58,99.24,633.36,0.852,0.981,0.85,0.894,2000,Centro +158,33,Higienópolis,74.06,97.46,100.28,614.41,0.818,0.983,0.845,0.882,2000,Zona Norte +159,34,Santa Teresa. Cosme Velho,74.06,96.14,92.6,701.19,0.818,0.95,0.867,0.878,2000,Zona Sul +160,35,Água Santa. Encantado,76.21,97.48,95.65,496.66,0.853,0.969,0.809,0.877,2000,Zona Norte +161,36,Taquara,76.21,96.53,92.28,544.29,0.853,0.951,0.824,0.876,2000,Zona Oeste +162,37,Vila Cosmos,77.2,97.58,89.46,498.82,0.87,0.949,0.81,0.876,2000,Zona Norte +163,38,Vidigal. São Conrado,71.12,94.76,82.0,1131.47,0.769,0.905,0.946,0.873,2000,Zona Sul +164,39,Cidade Nova. Praça da Bandeira,72.05,96.29,96.84,640.31,0.784,0.965,0.851,0.867,2000,Zona Norte +165,40,Bonsucesso,74.7,95.72,86.94,552.99,0.828,0.928,0.827,0.861,2000,Zona Norte +166,41,Cocotá. Bancários,74.06,96.48,91.67,518.28,0.818,0.949,0.816,0.861,2000,Ilha do Governador +167,42,Maria da Graça. Del Castilho,72.66,98.35,95.47,505.4,0.794,0.974,0.812,0.86,2000,Zona Norte +168,43,Ribeira. Cacuia,72.85,96.48,95.37,527.2,0.797,0.961,0.819,0.859,2000,Ilha do Governador +169,44,Lins de Vasconcelos,72.73,95.54,92.3,583.35,0.795,0.945,0.836,0.859,2000,Zona Norte +170,45,Engenho Novo,72.37,96.29,93.33,573.33,0.789,0.953,0.833,0.858,2000,Zona Norte +171,46,Zumbi. Pitangueiras. Praia da Bandeira,73.53,96.9,91.34,517.83,0.809,0.95,0.816,0.858,2000,Ilha do Governador +172,47,Ramos,73.94,97.13,88.7,508.76,0.816,0.943,0.813,0.857,2000,Zona Norte +173,48,Engenho de Dentro,72.66,96.67,92.77,536.54,0.794,0.954,0.822,0.857,2000,Zona Norte +174,49,Abolição,73.28,97.07,95.69,467.23,0.805,0.966,0.799,0.857,2000,Zona Norte +175,50,Deodoro. Vila Militar. Campo dos Afonsos. Jardim Sulacap,73.59,97.75,93.26,462.13,0.81,0.963,0.797,0.856,2000,Zona Oeste +176,51,Oswaldo Cruz,73.59,97.75,94.12,441.34,0.81,0.965,0.789,0.855,2000,Zona Norte +177,52,Olaria,73.87,96.93,90.95,460.31,0.814,0.949,0.796,0.853,2000,Zona Norte +178,53,Bento Ribeiro,75.05,97.95,88.15,399.85,0.834,0.947,0.773,0.851,2000,Zona Norte +179,54,Piedade,72.66,97.08,95.51,447.64,0.794,0.966,0.792,0.85,2000,Zona Norte +180,55,Quintino Bocaiúva,73.91,96.8,91.97,424.67,0.815,0.952,0.783,0.85,2000,Zona Norte +181,56,Rio Comprido,70.28,97.0,92.6,590.26,0.755,0.955,0.838,0.849,2000,Zona Norte +182,57,Praça Seca,71.7,96.18,91.79,498.32,0.778,0.947,0.81,0.845,2000,Zona Norte +183,58,Jardim América,72.66,97.03,87.72,426.12,0.794,0.939,0.783,0.839,2000,Zona Norte +184,59,Jacaré. Rocha. Sampaio,70.64,95.9,90.65,513.62,0.761,0.941,0.815,0.839,2000,Zona Norte +185,60,Freguesia,70.28,95.23,89.35,557.35,0.755,0.933,0.828,0.839,2000,Zona Oeste +186,61,Jardim Carioca,72.66,95.97,86.23,436.33,0.794,0.927,0.787,0.836,2000,Ilha do Governador +187,62,Engenho da Rainha,73.36,96.93,89.2,362.62,0.806,0.944,0.757,0.835,2000,Zona Norte +188,63,Brás de Pina,72.66,96.45,88.41,397.15,0.794,0.938,0.772,0.835,2000,Zona Norte +189,64,São Cristóvão. Vasco da Gama,72.27,95.44,89.08,412.39,0.788,0.933,0.778,0.833,2000,Zona Norte +190,65,Cascadura,72.15,95.97,86.35,428.76,0.786,0.928,0.785,0.833,2000,Zona Norte +191,66,Parque Anchieta,73.71,96.31,87.17,355.31,0.812,0.933,0.753,0.833,2000,Zona Norte +192,67,Madureira,70.97,96.81,90.42,419.81,0.766,0.947,0.781,0.831,2000,Zona Norte +193,68,Pilares,72.55,96.79,86.05,389.81,0.793,0.932,0.769,0.831,2000,Zona Norte +194,69,Tanque,71.49,95.95,86.87,439.87,0.775,0.929,0.789,0.831,2000,Zona Oeste +195,70,Estácio,73.71,94.09,80.82,413.05,0.812,0.897,0.778,0.829,2000,Centro +196,71,Curicica,72.57,96.15,88.33,362.72,0.793,0.935,0.757,0.828,2000,Zona Oeste +197,72,Penha Circular,71.15,96.23,83.38,444.77,0.769,0.919,0.791,0.826,2000,Zona Norte +198,73,Benfica,73.59,94.5,81.35,376.65,0.81,0.901,0.763,0.825,2000,Zona Norte +199,74,Paquetá,74.06,94.22,67.66,457.61,0.818,0.854,0.795,0.822,2000,Ilha de Paquetá +200,75,Itanhangá,70.28,91.44,74.3,650.96,0.755,0.857,0.854,0.822,2000,Zona Oeste +201,76,Tauá,71.24,93.2,83.99,416.19,0.771,0.901,0.78,0.817,2000,Ilha do Governador +202,77,Rocha Miranda,70.99,96.62,87.07,338.1,0.766,0.934,0.745,0.815,2000,Zona Norte +203,78,Marechal Hermes,70.11,96.09,87.78,366.28,0.752,0.933,0.758,0.814,2000,Zona Norte +204,79,Turiaçu,70.11,97.37,87.15,336.57,0.752,0.94,0.744,0.812,2000,Zona Norte +205,80,Guadalupe,70.11,97.27,85.58,336.89,0.752,0.934,0.744,0.81,2000,Zona Norte +206,81,Inhaúma,70.64,96.39,86.56,324.3,0.761,0.931,0.738,0.81,2000,Zona Norte +207,82,Campo Grande,69.8,95.98,87.42,351.11,0.747,0.931,0.751,0.81,2000,Zona Oeste +208,83,Cavalcanti. Engenheiro Leal. Vaz Lobo,70.41,96.29,84.68,328.64,0.757,0.924,0.74,0.807,2000,Zona Norte +209,84,Ricardo de Albuquerque,70.97,96.42,89.06,283.0,0.766,0.94,0.715,0.807,2000,Zona Norte +210,85,Coelho Neto,70.86,96.88,84.77,299.89,0.764,0.928,0.725,0.806,2000,Zona Norte +211,86,Padre Miguel,70.11,95.72,87.21,313.85,0.752,0.929,0.732,0.804,2000,Zona Oeste +212,87,Penha,69.59,95.12,82.23,373.05,0.743,0.908,0.761,0.804,2000,Zona Norte +213,88,Honório Gurgel,69.88,96.56,88.09,303.98,0.748,0.937,0.727,0.804,2000,Zona Norte +214,89,Realengo,69.63,95.97,87.44,316.41,0.744,0.931,0.734,0.803,2000,Zona Oeste +215,90,Senador Vasconcelos,69.68,95.88,88.68,302.44,0.745,0.935,0.726,0.802,2000,Zona Oeste +216,91,Tomás Coelho,69.88,95.89,83.8,325.92,0.748,0.919,0.739,0.802,2000,Zona Norte +217,92,Magalhães Bastos,68.9,95.72,90.24,318.03,0.732,0.939,0.735,0.802,2000,Zona Oeste +218,93,Catumbi,69.6,95.81,85.41,324.83,0.743,0.923,0.738,0.802,2000,Centro +219,94,Mangueira. São Francisco Xavier,68.34,94.2,88.51,357.43,0.722,0.923,0.754,0.8,2000,Zona Norte +220,95,Vista Alegre. Irajá,62.81,98.08,92.99,473.39,0.63,0.964,0.801,0.798,2000,Zona Norte +221,96,Bangu,69.78,95.45,82.95,296.55,0.746,0.913,0.723,0.794,2000,Zona Oeste +222,97,Saúde. Gamboa. Santo Cristo,70.28,94.21,77.52,320.57,0.755,0.886,0.736,0.792,2000,Zona Portuária +223,98,Cordovil,68.32,95.83,87.92,290.49,0.722,0.932,0.72,0.791,2000,Zona Norte +224,99,Pavuna,69.27,95.96,82.51,286.38,0.738,0.915,0.717,0.79,2000,Zona Norte +225,100,Anchieta,68.9,95.65,84.75,278.18,0.732,0.92,0.712,0.788,2000,Zona Norte +226,101,Santíssimo,69.36,95.04,80.94,256.08,0.739,0.903,0.698,0.78,2000,Zona Oeste +227,102,Galeão. Cidade Universitária,67.79,93.92,80.64,300.31,0.713,0.895,0.725,0.778,2000,Ilha do Governador +228,103,Vicente de Carvalho,67.51,93.79,78.52,296.63,0.709,0.887,0.723,0.773,2000,Zona Norte +229,104,Jacarepaguá,67.51,90.18,77.14,331.44,0.709,0.858,0.742,0.769,2000,Zona Oeste +230,105,Senador Camará,67.39,93.63,83.67,251.09,0.707,0.903,0.695,0.768,2000,Zona Oeste +231,106,Gardênia Azul,67.79,93.78,76.4,274.68,0.713,0.88,0.71,0.768,2000,Zona Oeste +232,107,Vigário Geral,66.66,93.52,74.73,296.6,0.694,0.873,0.723,0.763,2000,Zona Norte +233,108,Colégio,67.33,94.52,74.33,262.37,0.706,0.878,0.703,0.762,2000,Zona Norte +234,109,Sepetiba,66.3,93.64,79.65,264.8,0.688,0.89,0.704,0.761,2000,Zona Oeste +235,110,Cosmos,67.51,94.86,82.17,205.9,0.709,0.906,0.662,0.759,2000,Zona Oeste +236,111,Caju,68.9,90.43,71.97,236.59,0.732,0.843,0.685,0.753,2000,Zona Portuária +237,112,Paciência,66.66,94.36,81.02,203.43,0.694,0.899,0.66,0.751,2000,Zona Oeste +238,113,Cidade de Deus,66.66,93.56,81.1,207.56,0.694,0.894,0.663,0.751,2000,Zona Oeste +239,114,Barros Filho,66.66,93.6,82.15,198.96,0.694,0.898,0.656,0.75,2000,Zona Norte +240,115,Inhoaíba,65.99,93.63,81.38,207.61,0.683,0.895,0.663,0.747,2000,Zona Oeste +241,116,Camorim. Vargem Pequena. Vargem Grande,66.3,90.8,69.28,279.09,0.688,0.836,0.713,0.746,2000,Zona Oeste +242,117,Parada de Lucas,65.35,92.38,82.15,220.27,0.672,0.89,0.673,0.745,2000,Zona Norte +243,118,Guaratiba. Barra de Guaratiba. Pedra de Guaratiba,66.66,90.74,74.37,234.37,0.694,0.853,0.684,0.744,2000,Zona Oeste +244,119,Santa Cruz,65.52,93.19,79.82,206.23,0.675,0.887,0.662,0.742,2000,Zona Oeste +245,120,Rocinha,67.33,87.9,69.5,219.95,0.706,0.818,0.673,0.732,2000,Zona Sul +246,121,Jacarezinho,66.3,92.2,75.68,177.98,0.688,0.867,0.638,0.731,2000,Zona Norte +247,122,Manguinhos,66.3,91.48,69.64,188.86,0.688,0.842,0.648,0.726,2000,Zona Norte +248,123,Maré,66.58,89.46,68.76,187.25,0.693,0.826,0.646,0.722,2000,Zona Norte +249,124,Acari. Parque Colúmbia,63.93,91.68,79.44,174.12,0.649,0.876,0.634,0.72,2000,Zona Norte +250,125,Costa Barros,63.93,91.34,74.09,175.0,0.649,0.856,0.635,0.713,2000,Zona Norte +251,126,Complexo do Alemão,64.79,89.07,72.04,177.31,0.663,0.834,0.637,0.711,2000,Zona Norte diff --git a/material/base_variacao.csv b/material/base_variacao.csv new file mode 100644 index 0000000..a6d7b31 --- /dev/null +++ b/material/base_variacao.csv @@ -0,0 +1,127 @@ +,Bairro ou grupo de bairros,Índice de Desenvolvimento Humano Municipal (IDH)_1991,Região,Índice de Desenvolvimento Humano Municipal (IDH)_2000 +0,Gávea,0.939,Zona Sul,0.97 +1,Jardim Botânico,0.927,Zona Sul,0.957 +2,Ipanema,0.925,Zona Sul,0.962 +3,Leblon,0.923,Zona Sul,0.967 +4,Humaitá,0.923,Zona Sul,0.959 +5,Flamengo,0.919,Zona Sul,0.959 +6,Laranjeiras,0.919,Zona Sul,0.957 +7,Joá. Barra da Tijuca,0.917,Zona Oeste,0.959 +8,Lagoa,0.915,Zona Sul,0.959 +9,Botafogo. Urca,0.909,Zona Sul,0.952 +10,Jardim Guanabara,0.907,Ilha do Governador,0.963 +11,Leme,0.903,Zona Sul,0.955 +12,Copacabana,0.902,Zona Sul,0.956 +13,Maracanã,0.901,Zona Norte,0.944 +14,Méier,0.885,Zona Norte,0.931 +15,Glória,0.883,Zona Sul,0.94 +16,Grajaú,0.879,Zona Norte,0.938 +17,Tijuca. Alto da Boa Vista,0.873,Zona Norte,0.926 +18,Todos os Santos,0.868,Zona Norte,0.922 +19,Andaraí,0.858,Zona Norte,0.909 +20,Vila da Penha,0.853,Zona Norte,0.909 +21,Catete,0.85,Zona Sul,0.901 +22,Riachuelo,0.847,Zona Norte,0.905 +23,Moneró. Portuguesa,0.845,Ilha do Governador,0.904 +24,Cachambi,0.844,Zona Norte,0.9 +25,Freguesia (Jacarepaguá),0.843,Zona Oeste,0.898 +26,Pechincha,0.842,Zona Oeste,0.9 +27,Vidigal. São Conrado,0.84,Zona Sul,0.873 +28,Vila Isabel,0.838,Zona Norte,0.901 +29,Campinho. Vila Valqueire,0.835,Zona Norte,0.904 +30,Anil,0.833,Zona Oeste,0.911 +31,Centro,0.825,Centro,0.894 +32,Higienópolis,0.817,Zona Norte,0.882 +33,Bonsucesso,0.817,Zona Norte,0.861 +34,Água Santa. Encantado,0.816,Zona Norte,0.877 +35,Vila Cosmos,0.812,Zona Norte,0.876 +36,Abolição,0.812,Zona Norte,0.857 +37,Cocotá. Bancários,0.812,Ilha do Governador,0.861 +38,Santa Teresa. Cosme Velho,0.81,Zona Sul,0.878 +39,Taquara,0.806,Zona Oeste,0.876 +40,Engenho de Dentro,0.802,Zona Norte,0.857 +41,Rio Comprido,0.801,Zona Norte,0.849 +42,Ramos,0.801,Zona Norte,0.857 +43,Olaria,0.801,Zona Norte,0.853 +44,Lins de Vasconcelos,0.801,Zona Norte,0.859 +45,Engenho Novo,0.796,Zona Norte,0.858 +46,Praça Seca,0.795,Zona Norte,0.845 +47,Ribeira. Cacuia,0.795,Ilha do Governador,0.859 +48,Freguesia,0.794,Zona Oeste,0.839 +49,Jacaré. Rocha. Sampaio,0.794,Zona Norte,0.839 +50,Engenho da Rainha,0.794,Zona Norte,0.835 +51,Zumbi. Pitangueiras. Praia da Bandeira,0.794,Ilha do Governador,0.858 +52,Quintino Bocaiúva,0.794,Zona Norte,0.85 +53,Cidade Nova. Praça da Bandeira,0.793,Zona Norte,0.867 +54,Oswaldo Cruz,0.793,Zona Norte,0.855 +55,Madureira,0.792,Zona Norte,0.831 +56,Piedade,0.792,Zona Norte,0.85 +57,Itanhangá,0.791,Zona Oeste,0.822 +58,Deodoro. Vila Militar. Campo dos Afonsos. Jardim Sulacap,0.791,Zona Oeste,0.856 +59,Pilares,0.791,Zona Norte,0.831 +60,Bento Ribeiro,0.789,Zona Norte,0.851 +61,Recreio dos Bandeirantes. Grumari,0.788,Zona Oeste,0.894 +62,Tanque,0.785,Zona Oeste,0.831 +63,Estácio,0.783,Centro,0.829 +64,Penha Circular,0.782,Zona Norte,0.826 +65,Maria da Graça. Del Castilho,0.781,Zona Norte,0.86 +66,Brás de Pina,0.78,Zona Norte,0.835 +67,Jardim América,0.779,Zona Norte,0.839 +68,Jardim Carioca,0.776,Ilha do Governador,0.836 +69,Cascadura,0.776,Zona Norte,0.833 +70,Paquetá,0.775,Ilha de Paquetá,0.822 +71,Parque Anchieta,0.774,Zona Norte,0.833 +72,São Cristóvão. Vasco da Gama,0.772,Zona Norte,0.833 +73,Coelho Neto,0.771,Zona Norte,0.806 +74,Curicica,0.768,Zona Oeste,0.828 +75,Tomás Coelho,0.767,Zona Norte,0.802 +76,Inhaúma,0.764,Zona Norte,0.81 +77,Turiaçu,0.764,Zona Norte,0.812 +78,Rocha Miranda,0.764,Zona Norte,0.815 +79,Tauá,0.763,Ilha do Governador,0.817 +80,Guadalupe,0.763,Zona Norte,0.81 +81,Benfica,0.761,Zona Norte,0.825 +82,Cavalcanti. Engenheiro Leal. Vaz Lobo,0.759,Zona Norte,0.807 +83,Penha,0.758,Zona Norte,0.804 +84,Pavuna,0.753,Zona Norte,0.79 +85,Campo Grande,0.752,Zona Oeste,0.81 +86,Marechal Hermes,0.752,Zona Norte,0.814 +87,Saúde. Gamboa. Santo Cristo,0.752,Zona Portuária,0.792 +88,Ricardo de Albuquerque,0.75,Zona Norte,0.807 +89,Realengo,0.749,Zona Oeste,0.803 +90,Magalhães Bastos,0.746,Zona Oeste,0.802 +91,Galeão. Cidade Universitária,0.745,Ilha do Governador,0.778 +92,Catumbi,0.745,Centro,0.802 +93,Padre Miguel,0.743,Zona Oeste,0.804 +94,Senador Vasconcelos,0.742,Zona Oeste,0.802 +95,Bangu,0.739,Zona Oeste,0.794 +96,Vista Alegre. Irajá,0.737,Zona Norte,0.798 +97,Mangueira. São Francisco Xavier,0.735,Zona Norte,0.8 +98,Honório Gurgel,0.734,Zona Norte,0.804 +99,Cordovil,0.733,Zona Norte,0.791 +100,Vicente de Carvalho,0.732,Zona Norte,0.773 +101,Anchieta,0.727,Zona Norte,0.788 +102,Jacarepaguá,0.725,Zona Oeste,0.769 +103,Santíssimo,0.723,Zona Oeste,0.78 +104,Senador Camará,0.71,Zona Oeste,0.768 +105,Colégio,0.709,Zona Norte,0.762 +106,Camorim. Vargem Pequena. Vargem Grande,0.709,Zona Oeste,0.746 +107,Sepetiba,0.706,Zona Oeste,0.761 +108,Parada de Lucas,0.705,Zona Norte,0.745 +109,Cosmos,0.701,Zona Oeste,0.759 +110,Gardênia Azul,0.701,Zona Oeste,0.768 +111,Vigário Geral,0.699,Zona Norte,0.763 +112,Paciência,0.696,Zona Oeste,0.751 +113,Inhoaíba,0.695,Zona Oeste,0.747 +114,Cidade de Deus,0.693,Zona Oeste,0.751 +115,Santa Cruz,0.692,Zona Oeste,0.742 +116,Caju,0.692,Zona Portuária,0.753 +117,Costa Barros,0.69,Zona Norte,0.713 +118,Barros Filho,0.689,Zona Norte,0.75 +119,Guaratiba. Barra de Guaratiba. Pedra de Guaratiba,0.683,Zona Oeste,0.744 +120,Jacarezinho,0.678,Zona Norte,0.731 +121,Rocinha,0.675,Zona Sul,0.732 +122,Manguinhos,0.674,Zona Norte,0.726 +123,Maré,0.667,Zona Norte,0.722 +124,Complexo do Alemão,0.657,Zona Norte,0.711 +125,Acari. Parque Colúmbia,0.657,Zona Norte,0.72