Can't find table selenium python

Solution 1:

Selecting Balanço Patrimonial Ativo and then to extract the data from the DFs Consolidadas / Balanço Patrimonial Ativo - (Reais Mil) table from the website you need to induce WebDriverWait for the visibility_of_element_located() and using DataFrame from Pandas you can use the following Locator Strategy:

Code Block:

from selenium import webdriver
from selenium.webdriver.chrome.options import Options
from selenium.webdriver.chrome.service import Service
from selenium.webdriver.support.ui import WebDriverWait
from selenium.webdriver.common.by import By
from selenium.webdriver.support import expected_conditions as EC
import pandas as pd

driver.get("https://www.rad.cvm.gov.br/ENETCONSULTA/frmGerenciaPaginaFRE.aspx?NumeroSequencialDocumento=102142&CodigoTipoInstituicao=2")
Select(WebDriverWait(driver, 20).until(EC.visibility_of_element_located((By.CSS_SELECTOR, "select#cmbQuadro")))).select_by_visible_text("Balanço Patrimonial Ativo")
WebDriverWait(driver, 20).until(EC.frame_to_be_available_and_switch_to_it((By.CSS_SELECTOR,"iframe#iFrameFormulariosFilho")))
data = WebDriverWait(driver, 20).until(EC.visibility_of_element_located((By.CSS_SELECTOR, "table#ctl00_cphPopUp_tbDados"))).get_attribute("outerHTML")
df = pd.read_html(data)
print(df)

Console Output:

[                0                              1            2            3
0           Conta                      Descrição   31/12/2020   31/12/2019
1               1                    Ativo Total  987.419.000  926.011.000
2            1.01               Ativo Circulante  142.323.000  112.101.000
3         1.01.01  Caixa e Equivalentes de Caixa   60.856.000   29.714.000
4         1.01.02         Aplicações Financeiras    3.424.000    3.580.000
..            ...                            ...          ...          ...
61     1.02.03.03       Imobilizado em Andamento          NaN          NaN
62        1.02.04                     Intangível   77.678.000   78.489.000
63     1.02.04.01                    Intangíveis          NaN          NaN
64  1.02.04.01.01          Contrato de Concessão          NaN          NaN
65     1.02.04.02                       Goodwill          NaN          NaN

[66 rows x 4 columns]]