From cdb8bebd91b481d514648c44d6d0080da168f618 Mon Sep 17 00:00:00 2001 From: Victor-oss Date: Wed, 4 Oct 2023 15:53:09 -0300 Subject: [PATCH] =?UTF-8?q?(#145)=20Refatora=C3=A7=C3=A3o=20e=20automata?= =?UTF-8?q?=C3=A7=C3=A3o=20do=20script=20de=20extra=C3=A7=C3=A3o=20dos=20d?= =?UTF-8?q?ados=20do=20Anu=C3=A1rio=20Estat=C3=ADstico=20de=20Energia=20El?= =?UTF-8?q?=C3=A9trica.=20Cria=C3=A7=C3=A3o=20da=20classe=20excelScrapper?= =?UTF-8?q?=20respons=C3=A1vel=20por=20baixar=20o=20script,=20da=20classe?= =?UTF-8?q?=20anuarioHandler=20respons=C3=A1vel=20por=20transformar=20o=20?= =?UTF-8?q?arquivo=20e=20salvar=20as=20tabelas=20retiradas=20dele=20e=20ta?= =?UTF-8?q?mb=C3=A9m=20foi=20adicionado=20o=20arquivo=20atualiza=5Ftabela.?= =?UTF-8?q?yml=20respons=C3=A1vel=20por=20automatizar=20a=20extra=C3=A7?= =?UTF-8?q?=C3=A3o,=20limpeza=20e=20salvamento=20das=20tabelas=20como=20os?= =?UTF-8?q?=20arquivos=20certos=20usando=20o=20Git=20Actions?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- .github/workflows/atualiza_tabelas.yml | 33 +++ .gitignore | 3 +- 04_PipelineTCU/anuario.py | 12 -- 04_PipelineTCU/anuarioHandler.py | 203 ++++++++++++++++++ 04_PipelineTCU/anuario_proc.py | 170 --------------- 04_PipelineTCU/constants/Anuario.xlsx | Bin 1675064 -> 1481445 bytes 04_PipelineTCU/constants/CapInstFonte(MW).csv | 84 ++++---- .../constants/CapInstRenPaises(GW).csv | 20 +- .../constants/CapInstSolPaises(GW).csv | 20 +- 04_PipelineTCU/constants/GelElFonte(GWh).csv | 2 +- 04_PipelineTCU/excelScrapper.py | 65 ++++++ 04_PipelineTCU/main.py | 22 ++ requirements.txt | 3 + 13 files changed, 391 insertions(+), 246 deletions(-) create mode 100644 .github/workflows/atualiza_tabelas.yml delete mode 100644 04_PipelineTCU/anuario.py create mode 100644 04_PipelineTCU/anuarioHandler.py delete mode 100644 04_PipelineTCU/anuario_proc.py create mode 100644 04_PipelineTCU/excelScrapper.py create mode 100644 04_PipelineTCU/main.py create mode 100644 requirements.txt diff --git a/.github/workflows/atualiza_tabelas.yml b/.github/workflows/atualiza_tabelas.yml new file mode 100644 index 0000000..0b666eb --- /dev/null +++ b/.github/workflows/atualiza_tabelas.yml @@ -0,0 +1,33 @@ +name: run main.py + +on: + schedule: [{cron: "0 0 * * 4"}] #agendamento + +jobs: + build: + runs-on: ubuntu-latest + steps: + - uses: actions/checkout@v3 + - name: Set up Python + uses: actions/setup-python@v4 + with: + python-version: '3.10' + - name: Install dependencies + run: | + pip install --upgrade pip + pip install -r requirements.txt + - name: execute py script # run main.py + env: + SOME_SECRET: ${{ secrets.SOME_SECRET }} + run: python 04_PipelineTCU/main.py + - name: commit files + run: | + git config --local user.email "action@github.com" + git config --local user.name "GitHub Action" + git add -A + git diff-index --quiet HEAD || (git commit -a -m "updated logs" --allow-empty) + - name: push changes + uses: ad-m/github-push-action@v0.6.0 + with: + github_token: ${{ secrets.GITHUB_TOKEN }} + branch: main \ No newline at end of file diff --git a/.gitignore b/.gitignore index a2f8398..d44dd06 100644 --- a/.gitignore +++ b/.gitignore @@ -1,2 +1,3 @@ env* -venv* \ No newline at end of file +venv* +04_PipelineTCU/__pycache__ \ No newline at end of file diff --git a/04_PipelineTCU/anuario.py b/04_PipelineTCU/anuario.py deleted file mode 100644 index 37f3688..0000000 --- a/04_PipelineTCU/anuario.py +++ /dev/null @@ -1,12 +0,0 @@ -import requests -import pathlib - -if __name__ == '__main__': - url_epe = "https://www.epe.gov.br/sites-pt/publicacoes-dados-abertos/publicacoes/PublicacoesArquivos/publicacao-160/topico-168/Anuário Estatístico de Energia Elétrica 2023 - Workbook.xlsx" - arquivo = "Anuario.xlsx" - r = requests.get(url_epe, allow_redirects=True) - output = open(arquivo, 'wb') - output.write(r.content) - output.close() - path = str(pathlib.Path(__file__).parent.resolve()) - pathlib.Path(path + '/' + arquivo).rename(path + '/constants/' + arquivo) \ No newline at end of file diff --git a/04_PipelineTCU/anuarioHandler.py b/04_PipelineTCU/anuarioHandler.py new file mode 100644 index 0000000..8f2614c --- /dev/null +++ b/04_PipelineTCU/anuarioHandler.py @@ -0,0 +1,203 @@ +import math +import pandas as pd +from pathlib import Path + +class AnuarioHandler: + # Uma classe que lê o arquivo correspondente ao Anuário Estatístico de Energia Elétrica, seleciona e transforma as tabelas desejadas e salva as tabelas resultantes em arquivos csv. + + # Atributos: + # file (str): nome do arquivo que será lido + # n_tabelas (str): número de tabelas que o arquivo conseguiu criar, inicialmente é zero + # path (str): caminho até a pasta onde os arquivos serão salvos + + # Métodos: + # def formataSalvaTabela(self, df, nome_tab, cols): + # Formata uma tabela para adicionar o ano do dado como uma coluna e salva essa tabela como arquivo csv + # def formatacaoComum(self, df, apaga_ultimo, e_inteiro, apaga_prim): + # Formata e retorna as tabelas com uma formatação comum a todas + # def tabelasConsRegioes(self, df, regioes, apaga_primeiros): + # Formata e retorna as tabelas que mostram os tipos de Consumo nas regiões geográficas do Brasil + # def generateTables(self): + # Formata e salva todas as tabelas do Anuário Estatístico de Energia Elétrica em arquivos csv + + def __init__(self, file): + # Construtor da classe anuarioHandler. + # Args: + # file (str): nome do arquivo correspondente ao arquivo do Anuário Estatístico de Eletricidade. + self.file = file + self.n_tabelas = 0 + self.path = str(Path(__file__).parent.resolve()) + self.path += "/constants/" + + def formataSalvaTabela(self, df, nome_tab, cols): + # Formata uma tabela para adicionar o ano do dado como uma coluna e salva essa tabela como arquivo csv + + #Args: + # df (DataFrame): DataFrame da tabela que será transformado e salvo como csv + # nome_tab (str): Nome com o qual o DataFrame será salvo como arquivo csv + # cols (list[str]): Lista com os nomes das colunas que será o header do arquivo csv + + df_final = pd.DataFrame() + ind_col = 1 + while ind_col < len(df.columns): + df_aux = df.iloc[1:, 0:1] + num_rows = len(df_aux) + new_column_data = [df.iloc[0, ind_col]] * num_rows + df_aux['Ano'] = new_column_data + df_aux['Geracao'] = df.iloc[1:,ind_col] + df_final = pd.concat([df_final, df_aux]) + ind_col += 1 + df_final['Ano'] = df_final['Ano'].astype('int64') + df_final.to_csv(self.path + nome_tab, header=cols, index=False) + + def formatacaoComum(self, df, apaga_ultimo, e_inteiro, apaga_prim): + # Formata e retorna as tabelas com uma formatação comum a todas + #Args: + # df (DataFrame): DataFrame da tabela que será formatada + # apaga_ultimo (bool): variável se informa se é necessário apagar a última linha + # e_inteior (bool): variável se informa se é necessário converter as colunas para int64 + # apaga_prim (bool): variável se informa se é necessário apagar a linha de índice 1 + + # Retorna: DataFrame + + df.dropna(inplace=True) + coluna = 1 + n_cols = df.columns.size + while coluna < n_cols: + if isinstance(df.iloc[0, coluna], str): + df.drop(df.columns[coluna:], axis=1, inplace=True) + break + coluna += 1 + if apaga_ultimo: + df.drop(index=df.iloc[-1].name, inplace=True) + if apaga_prim: + df.drop(index=df.iloc[1].name, inplace=True) + if e_inteiro: + df.iloc[:, 1:] = df.iloc[:, 1:].applymap(lambda x : math.floor(x) if (x*10 - int(x)*10) < 5 else math.ceil(x)) + for c in df.columns: + if df[c].dtype == 'float64': + df[c] = df[c].astype('int64') + return df + + def tabelasConsRegioes(self, df, regioes, apaga_primeiros): + # Formata e retorna as tabelas que mostram os tipos de Consumo nas regiões geográficas do Brasil + + #Args: + # df (DataFrame): DataFrame da tabela que será formatada + # regioes (list[str]): lista com os nomes das regiões + # apaga_primeiros (bool): variável se informa se é necessário apagar as primeiras linhas da tabela + + # Retorna: DataFrame + + if apaga_primeiros: + df.drop(df.iloc[1:7].index, inplace=True) + linha = 1 + while linha < len(regioes) + 1: + if not df.iloc[linha, 0] in regioes: + df.drop(index=df.iloc[linha].name, inplace=True) + else: + linha += 1 + df.drop(index=df.iloc[7:].index, inplace=True) + return df + + def generateTables(self): + # Formata e salva todas as tabelas do Anuário Estatístico de Energia Elétrica em arquivos csv + cols1 = ["Pais", "Ano","Cap_Inst"] + cols2 = ["Pais", "Ano","Geracao"] + dictCapInst = { + "Capacidade instalada de geração renovável no mundo" : + "CapInstRenPaises(GW).csv", + "Capacidade instalada de geração nuclear no mundo" : + "CapInstNucPaises(GW).csv", + "Capacidade instalada de geração térmica fóssil no mundo" : + "CapInstTermFosPaises(GW).csv", + "Capacidade instalada de geração hidrelétrica no mundo": + "CapInstHidPaises(GW).csv", + "Capacidade instalada de geração eólica no mundo": + "CapInstEolPaises(GW).csv", + "Capacidade instalada de geração solar no mundo": + "CapInstSolPaises(GW).csv", + "Capacidade instalada de geração biomassa no mundo": + "CapInstBioPaises(GW).csv" + } + dictGer = { + "Geração renovável no mundo" : "GerRenPaises(TWh).csv", + "Geração nuclear no mundo" : "GerNucPaises(TWh).csv", + "Geração térmica fóssil no mundo" : "GerTermFosPaises(TWh).csv", + "Geração hidrelétrica no mundo" : "GerHidPaises(TWh).csv", + "Geração eólica no mundo" : "GerEolPaises(TWh).csv", + "Geração solar no mundo" : "GerSolPaises(TWh).csv", + "Geração biomassa no mundo" : "GerBioPaises(TWh).csv" + } + dictCapGerEm = { + "Capacidade instalada de geração elétrica no Brasil (MW)" : [False, True, True, "CapInstFonte(MW).csv", ["Fonte", "Ano","Cap_Inst"]], + "Geração elétrica por fonte no Brasil (GWh)" : [False, True, True, "GelElFonte(GWh).csv", ["Fonte", "Ano","Geracao"]], + "Emissões de GEE no SIN - MtCO2" : [False, False, True, "EmGEESIN(MtCO2).csv", ["Fonte", "Ano","Emissoes"]], + "Emissões de GEE no Sistema Isolado - MtCO2" : [False, False, True, "EmGEESistIso(MtCO2).csv", ["Fonte", "Ano","Emissoes"]], + "Emissões de GEE provenientes da Geração Elétrica no Brasil - MtCO2" : [False, False, True, "EmGEEGerEl(MtCO2).csv", ["Subsistema", "Ano","Emissoes"]] + } + keysCapInst = dictCapInst.keys() + keysGer = dictGer.keys() + keysCapGerEm = dictCapGerEm.keys() + for sheet_name, df in pd.read_excel(self.path + self.file, sheet_name=None).items(): + try: + if self.n_tabelas == 24: + break + df.drop('Unnamed: 0', axis=1, inplace=True) + passou = False + for key in keysCapInst: + if df.iloc[5, 0].find(key) != -1: + df = self.formatacaoComum(df, True, True, True) + self.formataSalvaTabela(df, dictCapInst[key], cols1) + self.n_tabelas += 1 + passou = True + break + if passou: + continue + passou = False + for key in keysGer: + if df.iloc[5, 0].find(key) != -1: + df = self.formatacaoComum(df, True, True, True) + self.formataSalvaTabela(df, dictGer[key], cols2) + self.n_tabelas += 1 + passou = True + break + if passou: + continue + passou = False + for key in keysCapGerEm: + if df.iloc[5, 0].find(key) != -1: + df = self.formatacaoComum(df, dictCapGerEm[key][0], dictCapGerEm[key][1], dictCapGerEm[key][2]) + self.formataSalvaTabela(df, dictCapGerEm[key][3], dictCapGerEm[key][4]) + self.n_tabelas += 1 + passou = True + break + if passou: + continue + if df.iloc[5, 0].find("Consumo médio total por subsistema, região e UF") != -1: + regioes = ["Norte","Nordeste","Sudeste","Sul", "Centro-Oeste", "Regiões geográficas"] + cols3 = ["Subsistema", "Ano","Cons_Med_Tot"] + df = self.formatacaoComum(df, False, False, True) + self.formataSalvaTabela(df.iloc[0:7,:], 'ConsMedTotSubsis(kWh_mes).csv', cols3) + df = self.tabelasConsRegioes(df, regioes, True) + cols3 = ["Regiao", "Ano","Cons_Med_Tot"] + self.formataSalvaTabela(df,'ConsMedTotReg(kWh_mes).csv', cols3) + self.n_tabelas += 1 + elif df.iloc[5, 0].find("Consumo médio residencial por subsistema, região e UF") != -1: + regioes = ["Norte","Nordeste","Sudeste","Sul", "Centro-Oeste", "Regiões geográficas"] + cols3 = ["Subsistema", "Ano","Cons_Med_Res"] + df = self.formatacaoComum(df, False, False,True) + self.formataSalvaTabela(df.iloc[0:7,:], 'ConsMedResSubsis(kWh_mes).csv', cols3) + df = self.tabelasConsRegioes(df, regioes, True) + cols3 = ["Regiao", "Ano","Cons_Med_Res"] + self.formataSalvaTabela(df,'ConsMedResReg(kWh_mes).csv', cols3) + self.n_tabelas += 1 + elif df.iloc[5, 0].find("Consumo médio anual per capita por região e UF (kWh/hab)") != -1: + regioes = ["Norte","Nordeste","Sudeste","Sul", "Centro-Oeste", "Brasil"] + cols3 = ["Regiao", "Ano","Cons_Med_An_PC"] + df = self.formatacaoComum(df, False, False, False) + df = self.tabelasConsRegioes(df, regioes, False) + self.formataSalvaTabela(df,'ConsMedAnPerCapReg(kWh_hab).csv', cols3) + self.n_tabelas += 1 + except Exception as e: + continue \ No newline at end of file diff --git a/04_PipelineTCU/anuario_proc.py b/04_PipelineTCU/anuario_proc.py deleted file mode 100644 index 882b683..0000000 --- a/04_PipelineTCU/anuario_proc.py +++ /dev/null @@ -1,170 +0,0 @@ -from pathlib import Path -import pandas as pd -import math -import os - -def formataSalvaTabela(df, nome_tab, cols): - df_final = pd.DataFrame() - ind_col = 1 - while ind_col < len(df.columns): - df_aux = df.iloc[1:, 0:1] - num_rows = len(df_aux) - new_column_data = [df.iloc[0, ind_col]] * num_rows - df_aux['Ano'] = new_column_data - df_aux['Geracao'] = df.iloc[1:,ind_col] - df_final = pd.concat([df_final, df_aux]) - ind_col += 1 - df_final['Ano'] = df_final['Ano'].astype('int64') - df_final.to_csv(path + nome_tab, header=cols, index=False) - -def tabelasCapGerEm(df, apaga_ultimo, e_inteiro, apaga_prim): - df.dropna(inplace=True) - coluna = 1 - n_cols = df.columns.size - while coluna < n_cols: - if isinstance(df.iloc[0, coluna], str): - df.drop(df.columns[coluna:], axis=1, inplace=True) - break - coluna += 1 - if apaga_ultimo: - df.drop(index=df.iloc[-1].name, inplace=True) - if apaga_prim: - df.drop(index=df.iloc[1].name, inplace=True) - if e_inteiro: - df.iloc[:, 1:] = df.iloc[:, 1:].applymap(lambda x : math.floor(x) if (x*10 - int(x)*10) < 5 else math.ceil(x)) - for c in df.columns: - if df[c].dtype == 'float64': - df[c] = df[c].astype('int64') - return df - -def tabelasConsRegioes(df, regioes, apaga_primeiros): - if apaga_primeiros: - df.drop(df.iloc[1:7].index, inplace=True) - linha = 1 - while linha < len(regioes) + 1: - if not df.iloc[linha, 0] in regioes: - df.drop(index=df.iloc[linha].name, inplace=True) - else: - linha += 1 - df.drop(index=df.iloc[7:].index, inplace=True) - return df - -if __name__ == '__main__' : - arquivo = "Anuario.xlsx" - path = str(Path(__file__).parent.resolve()) - path += "/constants/" - n_tabelas = 0 - cols1 = ["Pais", "Ano","Cap_Inst"] - cols2 = ["Pais", "Ano","Geracao"] - cols3 = ["Fonte", "Ano","Cap_Inst"] - cols4 = ["Fonte", "Ano","Geracao"] - cols5 = ["Fonte", "Ano","Emissoes"] - cols6 = ["Subsistema", "Ano","Emissoes"] - for sheet_name, df in pd.read_excel(path + arquivo, sheet_name=None).items(): - try: - if n_tabelas == 22: - break - df.drop('Unnamed: 0', axis=1, inplace=True) - if df.iloc[5, 0].find("Capacidade instalada de geração renovável no mundo – 10 maiores") != -1: - df = tabelasCapGerEm(df, True, True, True) - formataSalvaTabela(df,'CapInstRenPaises(GW).csv', cols1) - n_tabelas += 1 - elif df.iloc[5, 0].find("Capacidade instalada de geração nuclear no mundo - 10 maiores") != -1: - df = tabelasCapGerEm(df, True, True, True) - formataSalvaTabela(df,'CapInstNucPaises(GW).csv', cols1) - n_tabelas += 1 - elif df.iloc[5, 0].find("Capacidade instalada de geração térmica fóssil no mundo – 10 maiores") != -1: - df = tabelasCapGerEm(df, True, True, True) - formataSalvaTabela(df, 'CapInstTermFosPaises(GW).csv', cols1) - n_tabelas += 1 - elif df.iloc[5, 0].find("Capacidade instalada de geração hidrelétrica no mundo - 10 maiores") != -1: - df = tabelasCapGerEm(df, True, True, True) - formataSalvaTabela(df, 'CapInstHidPaises(GW).csv', cols1) - n_tabelas += 1 - elif df.iloc[5, 0].find("Capacidade instalada de geração eólica no mundo - 10 maiores") != -1: - df = tabelasCapGerEm(df, True, True, True) - formataSalvaTabela(df, 'CapInstEolPaises(GW).csv', cols1) - n_tabelas += 1 - elif df.iloc[5, 0].find("Capacidade instalada de geração solar no mundo - 10 maiores") != -1: - df = tabelasCapGerEm(df, True, True, True) - formataSalvaTabela(df, 'CapInstSolPaises(GW).csv', cols1) - n_tabelas += 1 - elif df.iloc[5, 0].find("Capacidade instalada de geração biomassa no mundo - 10 maiores países") != -1: - df = tabelasCapGerEm(df, True, True, True) - formataSalvaTabela(df, 'CapInstBioPaises(GW).csv', cols1) - n_tabelas += 1 - elif df.iloc[5, 0].find("Geração renovável no mundo – 10 maiores") != -1: - df = tabelasCapGerEm(df, True, True, True) - formataSalvaTabela(df, 'GerRenPaises(TWh).csv', cols2) - n_tabelas += 1 - elif df.iloc[5, 0].find("Geração nuclear no mundo - 10 maiores") != -1: - df = tabelasCapGerEm(df, True, True, True) - formataSalvaTabela(df, 'GerNucPaises(TWh).csv', cols2) - n_tabelas += 1 - elif df.iloc[5, 0].find("Geração térmica fóssil no mundo – 10 maiores") != -1: - df = tabelasCapGerEm(df, True, True, True) - formataSalvaTabela(df, 'GerTermFosPaises(TWh).csv', cols2) - n_tabelas += 1 - elif df.iloc[5, 0].find("Geração hidrelétrica no mundo ") != -1: - df = tabelasCapGerEm(df, True, True, True) - formataSalvaTabela(df, 'GerHidPaises(TWh).csv', cols2) - n_tabelas += 1 - elif df.iloc[5, 0].find("Geração eólica no mundo - 10 maiores") != -1: - df = tabelasCapGerEm(df, True, True, True) - formataSalvaTabela(df, 'GerEolPaises(TWh).csv', cols2) - n_tabelas += 1 - elif df.iloc[5, 0].find("Geração solar no mundo - 10 maiores") != -1: - df = tabelasCapGerEm(df, True, True, True) - formataSalvaTabela(df, 'GerSolPaises(TWh).csv', cols2) - n_tabelas += 1 - elif df.iloc[5, 0].find("Geração biomassa no mundo - 10 maiores") != -1: - df = tabelasCapGerEm(df, True, True, True) - formataSalvaTabela(df, 'GerBioPaises(TWh).csv', cols2) - n_tabelas += 1 - elif df.iloc[5, 0].find("Capacidade instalada de geração elétrica no Brasil (MW)") != -1: - df = tabelasCapGerEm(df, False, True, True) - formataSalvaTabela(df, 'CapInstFonte(MW).csv', cols3) - n_tabelas += 1 - elif df.iloc[5, 0].find("Geração elétrica por fonte no Brasil (GWh)") != -1: - df = tabelasCapGerEm(df, False, True, True) - formataSalvaTabela(df, 'GelElFonte(GWh).csv', cols4) - n_tabelas += 1 - elif df.iloc[5, 0].find("Emissões de GEE no SIN - MtCO2") != -1: - df = tabelasCapGerEm(df, False, False, True) - formataSalvaTabela(df, 'EmGEESIN(MtCO2).csv', cols5) - n_tabelas += 1 - elif df.iloc[5, 0].find("Emissões de GEE no Sistema Isolado - MtCO2") != -1: - df = tabelasCapGerEm(df, False, False, True) - formataSalvaTabela(df, 'EmGEESistIso(MtCO2).csv', cols5) - n_tabelas += 1 - elif df.iloc[5, 0].find("Emissões de GEE provenientes da Geração Elétrica no Brasil - MtCO2") != -1: - df = tabelasCapGerEm(df, False, False, True) - formataSalvaTabela(df, 'EmGEEGerEl(MtCO2).csv', cols6) - n_tabelas += 1 - elif df.iloc[5, 0].find("Consumo médio total por subsistema, região e UF") != -1: - regioes = ["Norte","Nordeste","Sudeste","Sul", "Centro-Oeste", "Regiões geográficas"] - cols7 = ["Subsistema", "Ano","Cons_Med_Tot"] - cols8 = ["Regiao", "Ano","Cons_Med_Tot"] - df = tabelasCapGerEm(df, False, False, True) - formataSalvaTabela(df.iloc[0:7,:], 'ConsMedTotSubsis(kWh_mes).csv', cols7) - df = tabelasConsRegioes(df, regioes, True) - formataSalvaTabela(df,'ConsMedTotReg(kWh_mes).csv', cols8) - n_tabelas += 1 - elif df.iloc[5, 0].find("Consumo médio residencial por subsistema, região e UF") != -1: - regioes = ["Norte","Nordeste","Sudeste","Sul", "Centro-Oeste", "Regiões geográficas"] - cols7 = ["Subsistema", "Ano","Cons_Med_Res"] - cols8 = ["Regiao", "Ano","Cons_Med_Res"] - df = tabelasCapGerEm(df, False, False,True) - formataSalvaTabela(df.iloc[0:7,:], 'ConsMedResSubsis(kWh_mes).csv', cols7) - df = tabelasConsRegioes(df, regioes, True) - formataSalvaTabela(df,'ConsMedResReg(kWh_mes).csv', cols8) - n_tabelas += 1 - elif df.iloc[5, 0].find("Consumo médio anual per capita por região e UF (kWh/hab)") != -1: - regioes = ["Norte","Nordeste","Sudeste","Sul", "Centro-Oeste", "Brasil"] - cols8 = ["Regiao", "Ano","Cons_Med_An_PC"] - df = tabelasCapGerEm(df, False, False, False) - df = tabelasConsRegioes(df, regioes, False) - formataSalvaTabela(df,'ConsMedAnPerCapReg(kWh_hab).csv', cols8) - n_tabelas += 1 - except Exception as e: - continue \ No newline at end of file diff --git a/04_PipelineTCU/constants/Anuario.xlsx b/04_PipelineTCU/constants/Anuario.xlsx index 02c10c1ae859f782bb4686bbc6afd436eb6637cf..0974d00d35599e880af898d1eb1961df7c84a5e8 100644 GIT binary patch literal 1481445 zcmeEv1yt2(_celaNJ=9q-Cc?xDj*$#Al)I2ltDL&2qGyU9fC9pN=pa=(xH@qbORuJ zNceClC@64UdV-g}{~rSe$=?sjgTFIgFDEFY0$5NfBb_F+%U|C?->9aKR-wd1t&lY 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