Teste.ipynb

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     "text": [
      "0    995\n",
      "Name: tabela, dtype: object\n",
      "https://servicodados.ibge.gov.br/api/v3/agregados/995/metadados\n",
      "RESULTADO/RESULTADO/RESULTADO\n",
      "tabela_id                   object\n",
      "var_id                      object\n",
      "tabela_classificacoes.id    object\n",
      "categ_id                    object\n",
      "nivel_0                     object\n",
      "dtype: object\n",
      "     tabela_id var_id tabela_classificacoes.id categ_id nivel_0\n",
      "0          995    630                    12762   116830      N1\n",
      "1          995    707                    12762   116830      N1\n",
      "2          995   1637                    12762   116830      N1\n",
      "3          995   1636                    12762   116830      N1\n",
      "4          995   1639                    12762   116830      N1\n",
      "...        ...    ...                      ...      ...     ...\n",
      "2401       995    707                    12388   107695      N1\n",
      "2402       995   1637                    12388   107695      N1\n",
      "2403       995   1636                    12388   107695      N1\n",
      "2404       995   1639                    12388   107695      N1\n",
      "2405       995   1638                    12388   107695      N1\n",
      "\n",
      "[2406 rows x 5 columns]\n",
      "Request failed with status code 200\n"
     ]
    },
    {
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     "text": [
      "C:\\Users\\Alexandre Rebello\\AppData\\Local\\Temp\\ipykernel_32332\\1823616759.py:67: FutureWarning: Downcasting object dtype arrays on .fillna, .ffill, .bfill is deprecated and will change in a future version. Call result.infer_objects(copy=False) instead. To opt-in to the future behavior, set `pd.set_option('future.no_silent_downcasting', True)`\n",
      "  resultado[['tabela_id','var_id','tabela_classificacoes.id','categ_id']] = resultado[['tabela_id','var_id','tabela_classificacoes.id','categ_id']].fillna(-1)\n"
     ]
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   ],
   "source": [
    "#lista de parametros para API\n",
    "\n",
    "import requests\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "\n",
    "response = requests.get('https://servicodados.ibge.gov.br/api/v3/agregados')\n",
    "\n",
    "if response.status_code == 200:\n",
    "    data = response.json()\n",
    "\n",
    "    resultado = pd.DataFrame({'categ_id':[], 'categ_nome':[], 'categ_unidade':[], 'categ_nivel':[], 'tabela_id':[],\n",
    "       'tabela_classificacoes.id':[], 'tabela_classificacoes.nome':[],                      \n",
    "       'var_id':[], 'var_nome':[], 'var_unidade':[], 'var_sumarizacao':[], 'tabela_id':[],\n",
    "       'Tabela_nome':[], 'Tabela_URL':[], 'Tabela_pesquisa':[], 'Tabela_assunto':[],\n",
    "       'Tabela_periodicidade.frequencia':[], 'Tabela_periodicidade.inicio':[],\n",
    "       'Tabela_periodicidade.fim':[], 'Tabela_nivelTerritorial.Administrativo':[]})\n",
    "    \n",
    "  \n",
    "    lista = pd.DataFrame({'tabela':['995']})\n",
    "    print(lista['tabela'])\n",
    "    for item in lista['tabela']:\n",
    "        tab = item\n",
    "        #print(IdTabela)\n",
    "        enderecoT = 'https://servicodados.ibge.gov.br/api/v3/agregados/'+tab+'/metadados'\n",
    "        print(enderecoT)\n",
    "        responseT = requests.get(enderecoT)\n",
    "        dataT = responseT.json()\n",
    "        #print(dataT)\n",
    "        df_categ = pd.json_normalize(dataT,\n",
    "            record_path=['classificacoes','categorias'],\n",
    "            meta=[\"id\",[\"classificacoes\",\"id\"],[\"classificacoes\",\"nome\"]],\n",
    "            meta_prefix='tabela_',\n",
    "            record_prefix='categ_'\n",
    "            )\n",
    "       # print(df_categ)\n",
    "                #Variaveis x classificacao\n",
    "\n",
    "        df_var = pd.json_normalize(dataT,\n",
    "            record_path=['variaveis'],\n",
    "            meta=[\"id\",\"nome\",\"URL\",\"pesquisa\",\"assunto\",[\"periodicidade\",\"frequencia\"],[\"periodicidade\",\"inicio\"],[\"periodicidade\",\"fim\"],[\"nivelTerritorial\",\"Administrativo\"]],\n",
    "            meta_prefix='tabela_',\n",
    "            record_prefix='var_'\n",
    "                    )\n",
    "        #nivel territorio x tabela\n",
    "\n",
    "        df_nivel = pd.json_normalize(dataT,\n",
    "            record_path=['nivelTerritorial','Administrativo'],\n",
    "            meta=[\"id\"],\n",
    "            meta_prefix='tabela_',\n",
    "            record_prefix='nivel_'\n",
    "            )\n",
    "\n",
    "        if df_categ.empty:\n",
    "            dfm = df_var.merge(df_nivel,left_on='tabela_id',right_on='tabela_id')\n",
    "        else:\n",
    "            df1 = df_categ.merge(df_var, left_on='tabela_id',right_on='tabela_id')\n",
    "            dfm = df1.merge(df_nivel, left_on='tabela_id',right_on='tabela_id')\n",
    "        \n",
    "        options = ['N1','N3','N6'] \n",
    "        df = dfm.loc[dfm['nivel_0'].isin(options)] \n",
    "        #df = df.loc[:,'tabela_id']#,'var_id','tabela_classificacoes.id','categ_id','nivel_0']]\n",
    "        #print(dfm)\n",
    "        #print(\"muda/muda/muda\")\n",
    "        resultado = pd.concat([resultado,df])\n",
    "        resultado = resultado.loc[:,['tabela_id','var_id','tabela_classificacoes.id','categ_id','nivel_0']]\n",
    "        resultado[['tabela_id','var_id','tabela_classificacoes.id','categ_id']] = resultado[['tabela_id','var_id','tabela_classificacoes.id','categ_id']].fillna(-1)\n",
    "        resultado[['tabela_id','var_id','tabela_classificacoes.id','categ_id']] = resultado[['tabela_id','var_id','tabela_classificacoes.id','categ_id']].astype(int)\n",
    "        resultado[['tabela_id','var_id','tabela_classificacoes.id','categ_id']] = resultado[['tabela_id','var_id','tabela_classificacoes.id','categ_id']].astype(str)\n",
    "        resultado[['tabela_id','var_id','tabela_classificacoes.id','categ_id']] = resultado[['tabela_id','var_id','tabela_classificacoes.id','categ_id']].replace('-1', np.nan)\n",
    "        resultado[['tabela_id','var_id','tabela_classificacoes.id','categ_id']] = resultado[['tabela_id','var_id','tabela_classificacoes.id','categ_id']].fillna('').astype(str)\n",
    "\n",
    "    print(\"RESULTADO/RESULTADO/RESULTADO\")    \n",
    "    print(resultado.dtypes)\n",
    "    print(resultado)\n",
    "    print(f\"Request failed with status code {response.status_code}\")"
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