janeiro
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Numero,Mes,Ano,Data_Inicio,Data-Final
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1,SET ,1980,01/09/1980,10/09/1980
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2,SET ,1980,11/09/1980,20/09/1980
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3,SET ,1980,21/09/1980,30/09/1980
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1,OUT,1980,01/10/1980,10/10/1980
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2,OUT,1980,11/10/1980,20/10/1980
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3,OUT,1980,21/10/1980,31/10/1980
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1,NOV,1980,01/11/1980,10/11/1980
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2,NOV,1980,11/11/1980,20/11/1980
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3,NOV,1980,21/11/1980,30/11/1980
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1,DEZ,1980,01/12/1980,10/12/1980
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2,DEZ,1980,11/12/1980,20/12/1980
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3,DEZ,1980,21/12/1980,31/12/1980
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1,JAN,1981,01/01/1981,10/01/1981
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2,JAN,1981,11/01/1981,20/01/1981
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3,JAN,1981,21/01/1981,31/01/1981
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1,FEV,1981,01/02/1981,10/02/1981
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2,FEV,1981,11/02/1981,20/02/1981
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3,FEV,1981,21/02/1981,28/02/2981
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1,MAR,1981,01/03/1981,10/03/1981
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2,MAR,1981,11/03/1981,20/03/1981
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3,MAR,1981,21/03/1981,31/03/1981
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1,ABR,1981,01/04/1981,10/04/1981
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2,ABR,1981,11/04/1981,20/04/1981
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3,ABR,1981,21/04/1981,30/04/1981
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CODIGO;INICIO;FINAL
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20015;2020-10-20;2021-04-21
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20015;2021-10-06;2022-04-14
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20015;2022-10-08;2023-04-30
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20015;2023-10-02;2024-04-15
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20013;2020-10-17;2021-04-20
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20013;2021-10-11;2022-04-16
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20013;2022-10-06;2023-04-30
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20013;2023-10-02;2024-04-14
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20009;2020-09-21;2021-04-28
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20009;2021-09-28;2022-04-15
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20009;2022-09-27;2023-04-28
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20009;2023-10-02;2024-04-19
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20003;2020-10-11;2021-04-30
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20003;2021-10-03;2022-04-25
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20003;2022-09-17;2023-04-29
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20003;2023-10-02;2024-04-19
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20001;2020-09-24;2021-04-28
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20001;2021-10-03;2022-04-15
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20001;2022-09-22;2023-04-29
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20001;2023-09-29;2024-04-19
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20014;2020-10-17;2021-04-20
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20014;2021-10-11;2022-04-16
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20014;2022-09-22;2023-04-30
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20014;2023-10-02;2024-04-15
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20017;2020-09-24;2021-03-22
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20017;2021-09-04;2022-04-16
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20017;2022-10-04;2023-04-29
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20017;2023-09-07;2024-04-13
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20005;2020-09-24;2021-04-20
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20005;2021-10-11;2022-04-16
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20005;2022-09-29;2023-04-29
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20005;2023-09-15;2024-03-31
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20002;2020-10-11;2021-04-28
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20002;2021-09-30;2022-04-15
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20002;2022-09-17;2023-04-30
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20002;2023-09-07;2024-04-02
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20006;2020-09-23;2021-04-30
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20006;2021-09-01;2022-04-27
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20006;2022-10-04;2023-04-27
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20006;2023-09-12;2024-04-27
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20007;2020-10-11;2021-04-20
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20007;2021-10-03;2022-04-25
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20007;2022-09-17;2023-04-30
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20007;2023-10-04;2024-04-19
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20012;2020-10-09;2021-04-28
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20012;2021-09-03;2022-04-15
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20012;2022-09-22;2023-04-30
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20012;2023-09-01;2024-04-07
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20008;2020-09-21;2021-04-20
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20008;2021-09-11;2022-04-15
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20008;2022-09-22;2023-04-29
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20008;2023-09-28;2024-04-12
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20011;2020-10-11;2021-04-09
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20011;2021-09-02;2022-04-15
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20011;2022-09-17;2023-04-29
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20011;2023-10-02;2024-04-02
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20010;2020-10-10;2021-04-08
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20010;2021-09-22;2022-04-15
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20010;2022-09-18;2023-04-29
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20010;2023-10-03;2024-04-19
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20016;2020-09-24;2021-04-06
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20016;2021-09-04;2022-04-16
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20016;2022-10-24;2023-04-29
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20016;2023-10-04;2024-04-15
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20004;2020-09-24;2021-04-20
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20004;2021-09-03;2022-04-15
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20004;2022-09-17;2023-04-29
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20004;2023-09-15;2024-04-19
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{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 9,
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"metadata": {},
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"outputs": [],
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"source": [
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"# Carregando\n",
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"#começa tratando os dados e limpa a base\n",
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"import pandas as pd\n",
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"import numpy as np\n",
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"import csv\n",
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"\n",
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"dados = pd.read_csv('BaciaRioDoce_filtro_setembro_abril.csv', sep=';', encoding='utf-8', decimal=',')\n",
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"#dados.head(5)\n",
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"\n",
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"\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 10,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Erro ao converter a coluna 'DATA': name 'dados_df' is not defined\n",
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"<class 'pandas.core.frame.DataFrame'>\n",
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"RangeIndex: 12342 entries, 0 to 12341\n",
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"Data columns (total 3 columns):\n",
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" # Column Non-Null Count Dtype \n",
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"--- ------ -------------- ----- \n",
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" 0 CODIGO 12342 non-null int64 \n",
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" 1 DATA 12342 non-null datetime64[ns]\n",
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" 2 VALOR 12342 non-null object \n",
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"dtypes: datetime64[ns](1), int64(1), object(1)\n",
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"memory usage: 289.4+ KB\n",
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"None\n",
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" CODIGO DATA VALOR\n",
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"0 10004 2020-09-01 0\n",
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"1 10004 2020-09-02 0\n",
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"2 10004 2020-09-03 0\n",
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"3 10004 2020-09-04 0\n",
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"4 10004 2020-09-05 0\n"
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]
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}
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],
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"source": [
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"try:\n",
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" dados['DATA'] = pd.to_datetime(dados['DATA'], format='%Y-%m-%d', errors='coerce')\n",
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" if dados_df['DATA'].isnull().any():\n",
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" dados(\"Aviso: Algumas datas foram convertidas para NaT (Not a Time) devido a formatos inválidos.\")\n",
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"except Exception as e:\n",
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" print(f\"Erro ao converter a coluna 'DATA': {e}\")\n",
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"\n",
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"# Verificar o DataFrame após a conversão\n",
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"print(dados.info())\n",
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"print(dados.head())"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 11,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"<class 'pandas.core.frame.DataFrame'>\n",
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"RangeIndex: 12342 entries, 0 to 12341\n",
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"Data columns (total 3 columns):\n",
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" # Column Non-Null Count Dtype \n",
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"--- ------ -------------- ----- \n",
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" 0 CODIGO 12342 non-null int64 \n",
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" 1 DATA 12342 non-null datetime64[ns]\n",
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" 2 VALOR 12342 non-null float64 \n",
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"dtypes: datetime64[ns](1), float64(1), int64(1)\n",
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"memory usage: 289.4 KB\n",
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"None\n",
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" CODIGO DATA VALOR\n",
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"0 10004 2020-09-01 0.0\n",
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"1 10004 2020-09-02 0.0\n",
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"2 10004 2020-09-03 0.0\n",
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"3 10004 2020-09-04 0.0\n",
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"4 10004 2020-09-05 0.0\n"
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]
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}
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],
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"source": [
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"try:\n",
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" dados['VALOR'] = dados['VALOR'].astype(str) # Garantir que todos os valores são strings\n",
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" \n",
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" # Substituir vírgulas por pontos\n",
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" dados['VALOR'] = dados['VALOR'].str.replace(',', '.', regex=False)\n",
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" \n",
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" # Converter a coluna 'VALOR' para float\n",
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" dados['VALOR'] = pd.to_numeric(dados['VALOR'], errors='coerce')\n",
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" \n",
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" # Tratar valores NaN substituindo por 0\n",
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" dados['VALOR'] = dados['VALOR'].fillna(0)\n",
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" \n",
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"except Exception as e:\n",
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" print(f\"Erro ao converter a coluna 'VALOR': {e}\")\n",
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"\n",
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"# Verificar o DataFrame após a conversão\n",
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"print(dados.info())\n",
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"print(dados.head())"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"metadata": {},
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"outputs": [],
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"source": []
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": []
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},
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{
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"cell_type": "code",
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"execution_count": 4,
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"metadata": {},
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"outputs": [],
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"source": []
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "venv",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.12.4"
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},
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"orig_nbformat": 4
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},
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"nbformat": 4,
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"nbformat_minor": 2
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}
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@@ -0,0 +1,18 @@
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CODIGO;LATITUDE;LONGITUDE;NOME;1p;2p;3p;4p;5p;6p;7p;8p;9p;10p;1c;2c;3c;4c;5c;6c;7c;8c;9c;10c
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20001;-18,23;-43,65;DIAMANTINA; CDOMATODENTRO; ITAMARANDIBA; GUANHAES; CARBONITA;CAPELINHA; TIMOTEO;G. VALADARES; CARATINGA; TEOFILO OTONI; MANHUACU;20002;20014;20012;20015;20013;20011;20007;20003;20016;20010
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20002;-19,02;-43,43; CDOMATODENTRO; GUANHAES;DIAMANTINA; TIMOTEO; ITAMARANDIBA;G. VALADARES; CARATINGA; CARBONITA;CAPELINHA; MANHUACU; VICOSA;20012;20001;20011;20014;20007;20003;20015;20013;20010;20009
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20003;-19,74;-42,14; CARATINGA; TIMOTEO; MANHUACU; CAPARAO;G. VALADARES; AIMORES; GUANHAES; VICOSA; CDOMATODENTRO;MANTENA; TEOFILO OTONI;20011;20010;20004;20007;20005;20012;20009;20002;20017;20016
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20004;-20,53;-41,91; CAPARAO; MANHUACU; CARATINGA; VICOSA; TIMOTEO; AIMORES;G. VALADARES;MANTENA; BARBACENA; GUANHAES; CDOMATODENTRO;20010;20003;20009;20011;20005;20007;20017;20008;20012;20002
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20005;-19,53;-41,09; AIMORES;MANTENA;LINHARES; CARATINGA;G. VALADARES; CAPARAO; MANHUACU; TIMOTEO; TEOFILO OTONI; GUANHAES; VICOSA;20017;20006;20003;20007;20004;20010;20011;20016;20012;20009
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20006;-19,36;-40,07;LINHARES; AIMORES;MANTENA;G. VALADARES; TEOFILO OTONI; CARATINGA; CAPARAO; MANHUACU; TIMOTEO;CAPELINHA; GUANHAES;20005;20017;20007;20016;20003;20004;20010;20011;20013;20012
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20007;-18,83;-41,98;G. VALADARES; CARATINGA; GUANHAES; TIMOTEO;MANTENA; TEOFILO OTONI; AIMORES;CAPELINHA; ITAMARANDIBA; MANHUACU; CDOMATODENTRO;20003;20012;20011;20017;20016;20005;20013;20014;20010;20002
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20008;-21,23;-43,77; BARBACENA; VICOSA; MANHUACU; CAPARAO; TIMOTEO; CARATINGA; CDOMATODENTRO; GUANHAES;G. VALADARES;DIAMANTINA; AIMORES;20009;20010;20004;20011;20003;20002;20012;20007;20001;20005
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20009;-20,76;-42,86; VICOSA; MANHUACU; CAPARAO; BARBACENA; TIMOTEO; CARATINGA; CDOMATODENTRO; GUANHAES;G. VALADARES; AIMORES;DIAMANTINA;20010;20004;20008;20011;20003;20002;20012;20007;20005;20001
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20010;-20,26;-42,18; MANHUACU; CAPARAO; CARATINGA; TIMOTEO; VICOSA; AIMORES;G. VALADARES; GUANHAES; CDOMATODENTRO; BARBACENA;MANTENA;20004;20003;20011;20009;20005;20007;20012;20002;20008;20017
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20011;-19,57;-42,62; TIMOTEO; CARATINGA; MANHUACU; GUANHAES;G. VALADARES; CDOMATODENTRO; CAPARAO; VICOSA; AIMORES;DIAMANTINA; ITAMARANDIBA;20003;20010;20012;20007;20002;20004;20009;20005;20001;20014
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20012;-18,79;-42,94; GUANHAES; CDOMATODENTRO; TIMOTEO;DIAMANTINA; ITAMARANDIBA;G. VALADARES;CAPELINHA; CARATINGA; CARBONITA; MANHUACU; TEOFILO OTONI;20002;20011;20001;20014;20007;20013;20003;20015;20010;20016
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20013;-17,71;-42,39;CAPELINHA; ITAMARANDIBA; CARBONITA; TEOFILO OTONI;G. VALADARES; GUANHAES;DIAMANTINA; CDOMATODENTRO;MANTENA; TIMOTEO; CARATINGA;20014;20015;20016;20007;20012;20001;20002;20017;20011;20003
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20014;-17,86;-42,85; ITAMARANDIBA; CARBONITA;CAPELINHA;DIAMANTINA; GUANHAES; CDOMATODENTRO;G. VALADARES; TEOFILO OTONI; TIMOTEO; CARATINGA;MANTENA;20015;20013;20001;20012;20002;20007;20016;20011;20003;20017
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20015;-17,533;-43,012; CARBONITA; ITAMARANDIBA;CAPELINHA;DIAMANTINA; GUANHAES; TEOFILO OTONI; CDOMATODENTRO;G. VALADARES; TIMOTEO; CARATINGA;MANTENA;20014;20013;20001;20012;20016;20002;20007;20011;20003;20017
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20016;-17,89;-41,52; TEOFILO OTONI;CAPELINHA;MANTENA;G. VALADARES; ITAMARANDIBA; CARBONITA; GUANHAES; AIMORES; CARATINGA; TIMOTEO;LINHARES;20013;20017;20007;20014;20015;20012;20005;20003;20011;20006
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20017;-18,78;-40,99;MANTENA; AIMORES;G. VALADARES; TEOFILO OTONI;LINHARES; CARATINGA;CAPELINHA; TIMOTEO; MANHUACU; GUANHAES; CAPARAO;20005;20007;20016;20006;20003;20013;20011;20010;20012;20004
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Reference in New Issue
Block a user