diff --git a/exercicios/projeto-guiado/clima.db b/exercicios/projeto-guiado/clima.db new file mode 100644 index 0000000..c54c46a Binary files /dev/null and b/exercicios/projeto-guiado/clima.db differ diff --git a/exercicios/projeto-guiado/projeto-ray.ipynb b/exercicios/projeto-guiado/projeto-ray.ipynb new file mode 100644 index 0000000..db8717b --- /dev/null +++ b/exercicios/projeto-guiado/projeto-ray.ipynb @@ -0,0 +1,4669 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "import pandas as pd\n", + "import numpy as np\n", + "import matplotlib.pyplot as plt" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "df = pd.read_csv('INMET_MS_ITAQUIRAI_2020.CSV', delimiter=';', skiprows=8, encoding='latin1')" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Data object\n", + "Hora UTC object\n", + "PRECIPITAÇÃO TOTAL, HORÁRIO (mm) object\n", + "PRESSAO ATMOSFERICA AO NIVEL DA ESTACAO, HORARIA (mB) object\n", + "PRESSÃO ATMOSFERICA MAX.NA HORA ANT. (AUT) (mB) object\n", + "PRESSÃO ATMOSFERICA MIN. NA HORA ANT. (AUT) (mB) object\n", + "RADIACAO GLOBAL (Kj/m²) object\n", + "TEMPERATURA DO AR - BULBO SECO, HORARIA (°C) object\n", + "TEMPERATURA DO PONTO DE ORVALHO (°C) object\n", + "TEMPERATURA MÁXIMA NA HORA ANT. (AUT) (°C) object\n", + "TEMPERATURA MÍNIMA NA HORA ANT. (AUT) (°C) object\n", + "TEMPERATURA ORVALHO MAX. NA HORA ANT. (AUT) (°C) object\n", + "TEMPERATURA ORVALHO MIN. NA HORA ANT. (AUT) (°C) object\n", + "UMIDADE REL. MAX. NA HORA ANT. (AUT) (%) float64\n", + "UMIDADE REL. MIN. NA HORA ANT. (AUT) (%) float64\n", + "UMIDADE RELATIVA DO AR, HORARIA (%) float64\n", + "VENTO, DIREÇÃO HORARIA (gr) (° (gr)) float64\n", + "VENTO, RAJADA MAXIMA (m/s) object\n", + "VENTO, VELOCIDADE HORARIA (m/s) object\n", + "Unnamed: 19 float64\n", + "dtype: object" + ] + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df.dtypes" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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DataHora UTCPRECIPITAÇÃO TOTAL, HORÁRIO (mm)TEMPERATURA DO AR - BULBO SECO, HORARIA (°C)TEMPERATURA DO PONTO DE ORVALHO (°C)UMIDADE RELATIVA DO AR, HORARIA (%)RADIACAO GLOBAL (Kj/m²)VENTO, DIREÇÃO HORARIA (gr) (° (gr))VENTO, VELOCIDADE HORARIA (m/s)
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DataHora UTCPRECIPITAÇÃO TOTAL, HORÁRIO (mm)TEMPERATURA DO AR - BULBO SECO, HORARIA (°C)TEMPERATURA DO PONTO DE ORVALHO (°C)UMIDADE RELATIVA DO AR, HORARIA (%)RADIACAO GLOBAL (Kj/m²)VENTO, DIREÇÃO HORARIA (gr) (° (gr))VENTO, VELOCIDADE HORARIA (m/s)
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DataHora UTCPRECIPITAÇÃO TOTAL, HORÁRIO (mm)TEMPERATURA DO AR - BULBO SECO, HORARIA (°C)TEMPERATURA DO PONTO DE ORVALHO (°C)UMIDADE RELATIVA DO AR, HORARIA (%)RADIACAO GLOBAL (Kj/m²)VENTO, DIREÇÃO HORARIA (gr) (° (gr))VENTO, VELOCIDADE HORARIA (m/s)
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DataHora UTCPRECIPITAÇÃO TOTAL, HORÁRIO (mm)TEMPERATURA DO AR - BULBO SECO, HORARIA (°C)TEMPERATURA DO PONTO DE ORVALHO (°C)UMIDADE RELATIVA DO AR, HORARIA (%)RADIACAO GLOBAL (Kj/m²)VENTO, DIREÇÃO HORARIA (gr) (° (gr))VENTO, VELOCIDADE HORARIA (m/s)
02020-01-010000 UTC0.00.00.00.970.011.00.0
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32020-01-010300 UTC0.00.00.00.830.0332.00.0
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DataHora UTCPRECIPITAÇÃO TOTAL, HORÁRIO (mm)TEMPERATURA DO AR - BULBO SECO, HORARIA (°C)TEMPERATURA DO PONTO DE ORVALHO (°C)UMIDADE RELATIVA DO AR, HORARIA (%)RADIACAO GLOBAL (Kj/m²)VENTO, DIREÇÃO HORARIA (gr) (° (gr))VENTO, VELOCIDADE HORARIA (m/s)
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DataHora UTCPRECIPITAÇÃO TOTAL, HORÁRIO (mm)TEMPERATURA DO AR - BULBO SECO, HORARIA (°C)TEMPERATURA DO PONTO DE ORVALHO (°C)UMIDADE RELATIVA DO AR, HORARIA (%)RADIACAO GLOBAL (Kj/m²)VENTO, DIREÇÃO HORARIA (gr) (° (gr))VENTO, VELOCIDADE HORARIA (m/s)Data e Hora
02020-01-0100:000.00.00.00.970.011.00.02020-01-01 00:00
12020-01-0101:000.00.00.00.880.010.00.02020-01-01 01:00
22020-01-0102:000.024.00.00.880.0345.00.02020-01-01 02:00
32020-01-0103:000.00.00.00.830.0332.00.02020-01-01 03:00
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DataHora UTCPRECIPITAÇÃO TOTAL, HORÁRIO (mm)TEMPERATURA DO AR - BULBO SECO, HORARIA (°C)TEMPERATURA DO PONTO DE ORVALHO (°C)UMIDADE RELATIVA DO AR, HORARIA (%)RADIACAO GLOBAL (Kj/m²)VENTO, DIREÇÃO HORARIA (gr) (° (gr))VENTO, VELOCIDADE HORARIA (m/s)Data e Hora
02020-01-0100:000.00.00.00.970.011.00.02020-01-01 00:00
12020-01-0101:000.00.00.00.880.010.00.02020-01-01 01:00
22020-01-0102:000.024.00.00.880.0345.00.02020-01-01 02:00
32020-01-0103:000.00.00.00.830.0332.00.02020-01-01 03:00
42020-01-0104:000.00.00.00.890.0316.00.02020-01-01 04:00
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DataHora UTCPRECIPITAÇÃO TOTAL, HORÁRIO (mm)TEMPERATURA DO AR - BULBO SECO, HORARIA (°C)TEMPERATURA DO PONTO DE ORVALHO (°C)UMIDADE RELATIVA DO AR, HORARIA (%)RADIACAO GLOBAL (Kj/m²)VENTO, DIREÇÃO HORARIA (gr) (° (gr))VENTO, VELOCIDADE HORARIA (m/s)Data e Hora
02020-01-0100:000.00.00.00.970.011.00.0NaT
12020-01-0101:000.00.00.00.880.010.00.0NaT
22020-01-0102:000.024.00.00.880.0345.00.0NaT
32020-01-0103:000.00.00.00.830.0332.00.0NaT
42020-01-0104:000.00.00.00.890.0316.00.0NaT
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DataHora UTCPRECIPITAÇÃO TOTAL, HORÁRIO (mm)TEMPERATURA DO AR - BULBO SECO, HORARIA (°C)TEMPERATURA DO PONTO DE ORVALHO (°C)UMIDADE RELATIVA DO AR, HORARIA (%)RADIACAO GLOBAL (Kj/m²)VENTO, DIREÇÃO HORARIA (gr) (° (gr))VENTO, VELOCIDADE HORARIA (m/s)Data e HoraData e Hora BR
02020-01-0100:000.00.00.00.970.011.00.0NaTNaT
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22020-01-0102:000.024.00.00.880.0345.00.0NaTNaT
32020-01-0103:000.00.00.00.830.0332.00.0NaTNaT
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DataHora UTCPRECIPITAÇÃO TOTAL, HORÁRIO (mm)TEMPERATURA DO AR - BULBO SECO, HORARIA (°C)TEMPERATURA DO PONTO DE ORVALHO (°C)UMIDADE RELATIVA DO AR, HORARIA (%)RADIACAO GLOBAL (Kj/m²)VENTO, DIREÇÃO HORARIA (gr) (° (gr))VENTO, VELOCIDADE HORARIA (m/s)Data e HoraData e Hora BR
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42020-01-0104:000.00.00.00.890.0316.00.0NaTNaN
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DataPRECIPITAÇÃO TOTAL, HORÁRIO (mm)TEMPERATURA DO AR - BULBO SECO, HORARIA (°C)TEMPERATURA DO PONTO DE ORVALHO (°C)UMIDADE RELATIVA DO AR, HORARIA (%)RADIACAO GLOBAL (Kj/m²)VENTO, DIREÇÃO HORARIA (gr) (° (gr))VENTO, VELOCIDADE HORARIA (m/s)Data e Hora
count87848784.0000008784.0000008784.0000008784.0000008784.0000008784.0000008784.0000000
mean2020-07-01 11:59:59.9999997440.0302822.4116581.5392760.63272576.901298184.8894580.203097NaT
min2020-01-01 00:00:000.0000000.0000000.0000000.0000000.0000000.0000000.000000NaT
25%2020-04-01 00:00:000.0000000.0000000.0000000.4900000.000000133.0000000.000000NaT
50%2020-07-01 12:00:000.0000000.0000000.0000000.6700000.000000171.0000000.000000NaT
75%2020-10-01 00:00:000.0000000.0000000.0000000.8200000.000000254.0000000.000000NaT
max2020-12-31 00:00:0040.00000040.00000025.0000001.0000003886.000000360.0000008.000000NaT
stdNaN0.6941427.2915064.8890040.241409414.22431181.7847190.753577NaN
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76.901298 \n", + "min 0.000000 0.000000 \n", + "25% 0.490000 0.000000 \n", + "50% 0.670000 0.000000 \n", + "75% 0.820000 0.000000 \n", + "max 1.000000 3886.000000 \n", + "std 0.241409 414.224311 \n", + "\n", + " VENTO, DIREÇÃO HORARIA (gr) (° (gr)) VENTO, VELOCIDADE HORARIA (m/s) \\\n", + "count 8784.000000 8784.000000 \n", + "mean 184.889458 0.203097 \n", + "min 0.000000 0.000000 \n", + "25% 133.000000 0.000000 \n", + "50% 171.000000 0.000000 \n", + "75% 254.000000 0.000000 \n", + "max 360.000000 8.000000 \n", + "std 81.784719 0.753577 \n", + "\n", + " Data e Hora \n", + "count 0 \n", + "mean NaT \n", + "min NaT \n", + "25% NaT \n", + "50% NaT \n", + "75% NaT \n", + "max NaT \n", + "std NaN " + ] + }, + "execution_count": 36, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df.describe()" + ] + }, + { + "cell_type": "code", + "execution_count": 37, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "df.set_index('Data e Hora BR', inplace=True)\n", + "\n", + "df[['PRECIPITAÇÃO TOTAL, HORÁRIO (mm)', 'TEMPERATURA DO AR - BULBO SECO, HORARIA (°C)',\n", + " 'UMIDADE RELATIVA DO AR, HORARIA (%)']].plot(subplots=True)\n", + "\n", + "plt.suptitle('Séries Temporais das Variáveis')\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 48, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plt.scatter(df['Data e Hora'] ,df['TEMPERATURA DO AR - BULBO SECO, HORARIA (°C)'],\n", + " c=df['UMIDADE RELATIVA DO AR, HORARIA (%)'], \n", + " cmap='viridis', \n", + " alpha=0.7, \n", + " edgecolors='w')\n", + "plt.colorbar(label='Umidade Relativa do Ar (%)')\n", + "\n", + "plt.title('Temperatura do Ar x Umidade Relativa do Ar')\n", + "plt.xlabel('Hora e Data')\n", + "plt.ylabel('TEMPERATURA DO AR - BULBO SECO, HORARIA (°C)')\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 39, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 39, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "correlacao = df.corr\n", + "\n", + "correlacao" + ] + }, + { + "cell_type": "code", + "execution_count": 40, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "8784" + ] + }, + "execution_count": 40, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "import sqlite3\n", + "\n", + "conn = sqlite3.connect('clima.db')\n", + "# cursor = conn.cursor()\n", + "\n", + "# persistindo o DataFrame no banco de dados\n", + "df.to_sql('clima', conn, if_exists='replace')" + ] + }, + { + "cell_type": "code", + "execution_count": 41, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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Data e Hora BRDataHora UTCPRECIPITAÇÃO TOTAL, HORÁRIO (mm)TEMPERATURA DO AR - BULBO SECO, HORARIA (°C)TEMPERATURA DO PONTO DE ORVALHO (°C)UMIDADE RELATIVA DO AR, HORARIA (%)RADIACAO GLOBAL (Kj/m²)VENTO, DIREÇÃO HORARIA (gr) (° (gr))VENTO, VELOCIDADE HORARIA (m/s)Data e Hora
0None2020-01-01 00:00:0000:000.00.00.00.970.011.00.0None
1None2020-01-01 00:00:0001:000.00.00.00.880.010.00.0None
2None2020-01-01 00:00:0002:000.024.00.00.880.0345.00.0None
3None2020-01-01 00:00:0003:000.00.00.00.830.0332.00.0None
4None2020-01-01 00:00:0004:000.00.00.00.890.0316.00.0None
....................................
8779None2020-12-31 00:00:0019:000.00.00.00.970.032.00.0None
8780None2020-12-31 00:00:0020:000.00.00.00.910.0355.00.0None
8781None2020-12-31 00:00:0021:000.00.023.00.890.0315.00.0None
8782None2020-12-31 00:00:0022:000.00.00.00.880.0291.00.0None
8783None2020-12-31 00:00:0023:000.00.00.00.940.0132.00.0None
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8784 rows × 11 columns

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" + ], + "text/plain": [ + " Data e Hora BR Data Hora UTC \\\n", + "0 None 2020-01-01 00:00:00 00:00 \n", + "1 None 2020-01-01 00:00:00 01:00 \n", + "2 None 2020-01-01 00:00:00 02:00 \n", + "3 None 2020-01-01 00:00:00 03:00 \n", + "4 None 2020-01-01 00:00:00 04:00 \n", + "... ... ... ... \n", + "8779 None 2020-12-31 00:00:00 19:00 \n", + "8780 None 2020-12-31 00:00:00 20:00 \n", + "8781 None 2020-12-31 00:00:00 21:00 \n", + "8782 None 2020-12-31 00:00:00 22:00 \n", + "8783 None 2020-12-31 00:00:00 23:00 \n", + "\n", + " PRECIPITAÇÃO TOTAL, HORÁRIO (mm) \\\n", + "0 0.0 \n", + "1 0.0 \n", + "2 0.0 \n", + "3 0.0 \n", + "4 0.0 \n", + "... ... \n", + "8779 0.0 \n", + "8780 0.0 \n", + "8781 0.0 \n", + "8782 0.0 \n", + "8783 0.0 \n", + "\n", + " TEMPERATURA DO AR - BULBO SECO, HORARIA (°C) \\\n", + "0 0.0 \n", + "1 0.0 \n", + "2 24.0 \n", + "3 0.0 \n", + "4 0.0 \n", + "... ... \n", + "8779 0.0 \n", + "8780 0.0 \n", + "8781 0.0 \n", + "8782 0.0 \n", + "8783 0.0 \n", + "\n", + " TEMPERATURA DO PONTO DE ORVALHO (°C) \\\n", + "0 0.0 \n", + "1 0.0 \n", + "2 0.0 \n", + "3 0.0 \n", + "4 0.0 \n", + "... ... \n", + "8779 0.0 \n", + "8780 0.0 \n", + "8781 23.0 \n", + "8782 0.0 \n", + "8783 0.0 \n", + "\n", + " UMIDADE RELATIVA DO AR, HORARIA (%) RADIACAO GLOBAL (Kj/m²) \\\n", + "0 0.97 0.0 \n", + "1 0.88 0.0 \n", + "2 0.88 0.0 \n", + "3 0.83 0.0 \n", + "4 0.89 0.0 \n", + "... ... ... \n", + "8779 0.97 0.0 \n", + "8780 0.91 0.0 \n", + "8781 0.89 0.0 \n", + "8782 0.88 0.0 \n", + "8783 0.94 0.0 \n", + "\n", + " VENTO, DIREÇÃO HORARIA (gr) (° (gr)) VENTO, VELOCIDADE HORARIA (m/s) \\\n", + "0 11.0 0.0 \n", + "1 10.0 0.0 \n", + "2 345.0 0.0 \n", + "3 332.0 0.0 \n", + "4 316.0 0.0 \n", + "... ... ... \n", + "8779 32.0 0.0 \n", + "8780 355.0 0.0 \n", + "8781 315.0 0.0 \n", + "8782 291.0 0.0 \n", + "8783 132.0 0.0 \n", + "\n", + " Data e Hora \n", + "0 None \n", + "1 None \n", + "2 None \n", + "3 None \n", + "4 None \n", + "... ... \n", + "8779 None \n", + "8780 None \n", + "8781 None \n", + "8782 None \n", + "8783 None \n", + "\n", + "[8784 rows x 11 columns]" + ] + }, + "execution_count": 41, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "cursor = conn.cursor()\n", + "cursor.execute('SELECT * FROM clima')\n", + "\n", + "col_names = [description[0] for description in cursor.description]\n", + "\n", + "# for row in rows:\n", + "# print(row)\n", + "\n", + "df_db = pd.DataFrame(cursor.fetchall(), columns=col_names)\n", + "\n", + "df_db" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**Perguntas para Reflexão:**\n", + "Ao final do projeto, as alunas devem refletir sobre as seguintes questões baseadas nos dados analisados:\n", + "\n", + "1. Qual foi a média de valores de uma coluna específica?\n", + "2. Qual o total de registros após a limpeza dos dados?\n", + "3. Quais foram os valores máximos e mínimos identificados?\n", + "4. Quantos registros tinham valores nulos antes do tratamento?\n", + "5. Qual foi o impacto da normalização de uma coluna específica?\n", + "6. Que padrões emergiram após a análise dos dados?\n", + "7. Como os dados foram agrupados e quais insights foram gerados?\n", + "8. Quais visualizações forneceram as informações mais valiosas?\n", + "9. Como o uso de SQL contribuiu para a organização dos resultados?\n", + "10. De que forma os gráficos ajudaram na compreensão dos dados?" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**1**" + ] + }, + { + "cell_type": "code", + "execution_count": 49, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "np.float64(184.88945810564664)" + ] + }, + "execution_count": 49, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df['VENTO, DIREÇÃO HORARIA (gr) (° (gr))'].mean()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**2**" + ] + }, + { + "cell_type": "code", + "execution_count": 50, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(8784, 10)" + ] + }, + "execution_count": 50, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df.shape" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**3**" + ] + }, + { + "cell_type": "code", + "execution_count": 51, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Valores máximos por coluna:\n", + "Data 2020-12-31 00:00:00\n", + "Hora UTC 23:00\n", + "PRECIPITAÇÃO TOTAL, HORÁRIO (mm) 40.0\n", + "TEMPERATURA DO AR - BULBO SECO, HORARIA (°C) 40.0\n", + "TEMPERATURA DO PONTO DE ORVALHO (°C) 1.0\n", + "UMIDADE RELATIVA DO AR, HORARIA (%) 1.0\n", + "RADIACAO GLOBAL (Kj/m²) 3886.0\n", + "VENTO, DIREÇÃO HORARIA (gr) (° (gr)) 360.0\n", + "VENTO, VELOCIDADE HORARIA (m/s) 8.0\n", + "Data e Hora NaT\n", + "dtype: object\n", + "\n", + "Valores mínimos por coluna:\n", + "Data 2020-01-01 00:00:00\n", + "Hora UTC 00:00\n", + "PRECIPITAÇÃO TOTAL, HORÁRIO (mm) 0.0\n", + "TEMPERATURA DO AR - BULBO SECO, HORARIA (°C) 0.0\n", + "TEMPERATURA DO PONTO DE ORVALHO (°C) 0.0\n", + "UMIDADE RELATIVA DO AR, HORARIA (%) 0.0\n", + "RADIACAO GLOBAL (Kj/m²) 0.0\n", + "VENTO, DIREÇÃO HORARIA (gr) (° (gr)) 0.0\n", + "VENTO, VELOCIDADE HORARIA (m/s) 0.0\n", + "Data e Hora NaT\n", + "dtype: object\n" + ] + } + ], + "source": [ + "maximos = df.max()\n", + "minimos = df.min()\n", + "\n", + "print(\"Valores máximos por coluna:\")\n", + "print(maximos)\n", + "print(\"\\nValores mínimos por coluna:\")\n", + "print(minimos)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**4**" + ] + }, + { + "cell_type": "code", + "execution_count": 52, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Total de registros com pelo menos um valor nulo: 8784\n" + ] + } + ], + "source": [ + "total_nulos = df.isna().any(axis=1).sum()\n", + "print(f\"Total de registros com pelo menos um valor nulo: {total_nulos}\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**5**" + ] + }, + { + "cell_type": "code", + "execution_count": 53, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Data e Hora BR\n", + "NaN 0.00\n", + "NaN 0.00\n", + "NaN 0.00\n", + "NaN 0.00\n", + "NaN 0.00\n", + " ... \n", + "NaN 0.00\n", + "NaN 0.00\n", + "NaN 0.92\n", + "NaN 0.00\n", + "NaN 0.00\n", + "Name: TEMPERATURA DO PONTO DE ORVALHO (°C), Length: 8784, dtype: float64" + ] + }, + "execution_count": 53, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df['TEMPERATURA DO PONTO DE ORVALHO (°C)'] = (df['TEMPERATURA DO PONTO DE ORVALHO (°C)'] - df['TEMPERATURA DO PONTO DE ORVALHO (°C)'].min()) / (df['TEMPERATURA DO PONTO DE ORVALHO (°C)'].max() - df['TEMPERATURA DO PONTO DE ORVALHO (°C)'].min())\n", + "df['TEMPERATURA DO PONTO DE ORVALHO (°C)']" + ] + } + ], + "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": "3.12.5" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +}