Trying To Scrape Table Using Pandas From Selenium's Result

I am trying to scrape a table from a Javascript website using Pandas. For this, I used Selenium to first reach my desired page. I am able to print the table in text format (as show

Solution 1:

You can get the table using the following code

import time
from selenium import webdriver
import pandas as pd

chrome_path = r"Path to chrome driver"
driver = webdriver.Chrome(chrome_path)
url = 'http://www.bursamalaysia.com/market/securities/equities/prices/#/?filter=BS02'

page = driver.get(url)
time.sleep(2)

df = pd.read_html(driver.page_source)[0]
print(df.head())

This is the output

No  Code    Name    Rem Last Done   LACP    Chg % Chg   Vol ('00)   Buy Vol ('00)   Buy Sell    Sell Vol ('00)  High    Low
0   1   5284CB  LCTITAN-CB  s   0.025   0.020   0.005   +25.00  406550  19878   0.020   0.025   106630  0.025   0.015
1   2   1201    SUMATEC [S] s   0.050   0.050   -   -   389354  43815   0.050   0.055   187301  0.055   0.050
2   3   5284    LCTITAN [S] s   4.470   4.700   -0.230  -4.89   367335  430 4.470   4.480   34  4.780   4.140
3   4   0176    KRONO [S]   -   0.875   0.805   0.070   +8.70   300473  3770    0.870   0.875   797 0.900   0.775
4   5   5284CE  LCTITAN-CE  s   0.130   0.135   -0.005  -3.70   292379  7214    0.125   0.130   50  0.155   0.100

To get data from all pages you can crawl the remaining pages and use df.append

Solution 2:

Answer:

df = pd.read_html(target[0].get_attribute('outerHTML'))

Result:

Reason for target[0]:

driver.find_elements_by_id('bm_equities_prices_table') returns a list of selenium webelements, in your case, there's only 1 element, hence [0]

Reason for get_attribute('outerHTML'):

we want to get the 'html' of the element. There are 2 types of such get_attribute methods: 'innerHTML' vs 'outerHTML'. We chose the 'outerHTML' becasue we need to include the current element, where the table headers are, I suppose, instead of only the inner contents of the element.

Reason for df[0]

pd.read_html() returns a list of data frames, the first of which is the result we want, hence [0].