def get_data(number):

    
    ##Necessary imports
    from selenium import webdriver
    from selenium.webdriver import chrome
    from selenium.webdriver import ChromeOptions
    options = ChromeOptions()
    options.add_argument("--headless=new")
    driver = webdriver.Chrome(options=options)
    ## Finding Elements by XPATH
    from selenium.webdriver.common.by import By

    driver.get("https://www.thedailystar.net/tags/road-accident")
    
    """
    Browsing with browser open codes:
    ##Necessary imports
    from selenium import webdriver
    from selenium.webdriver import chrome

    driver = webdriver.Chrome()
    ## Finding Elements by XPATH
    from selenium.webdriver.common.by import By
    driver.get("https://en.prothomalo.com/topic/Road-accident")
   """ 
    import time
    news_list=[]
    news_link=[]
    publish_date=[]
    for i in range(number):
        #time.sleep(5)
        if (i+1)!=0 and (i+1)%10==0:
            last_height = driver.execute_script("return document.body.scrollHeight")
            driver.execute_script(f"window.scrollTo(0, {last_height-950})")
            driver.find_element('xpath',f'/html/body/div[3]/div/div/div/div[2]/main/div/div[2]/div/div[5]/div/div/div[1]/div/div[2]/ul/li/a').click()
            time.sleep(10)
        txt=driver.find_element('xpath',f'/html/body/div[3]/div/div/div/div[2]/main/div/div[2]/div/div[5]/div/div/div[1]/div/div[1]/div[{i+1}]/div[2]/div[2]/div[2]/h3/a')
        publish_date.append(driver.find_element('xpath',f'/html/body/div[3]/div/div/div/div[2]/main/div/div[2]/div/div[5]/div/div/div[1]/div/div[1]/div[{i+1}]/div[2]/div[1]').text)
        news_list.append(txt.text)
        news_link.append(txt.get_attribute("href"))   



    #### Converting the list to a pandas dataframe by converting the list to a dictionary  ###
    dict={'News Title':news_list,'News Link':news_link,'Publish Date':publish_date}
    import pandas as pd
    df=pd.DataFrame(dict)


    ############################################### Description Exctraction #################################################
    from newspaper import Article


    text=[]
    for i in range(len(df)):
        url = df['News Link'][i]
        article = Article(url)
        article.download()
        article.parse()
        
        text.append(article.text)

    df2=df.assign(Description=text)


    for p in range(len(df2)):
        if df2['Publish Date'][p]=="Not available":
            df2.drop([p],inplace=True)
    #df2.reset_index()

    df2.reset_index(drop=True,inplace=True)

    df2["Date + Desc"]=df2['Publish Date'] + ".     News Description:"+ df2['Description']


    
    return df2
    #df3.to_csv('Prothom_Alo_Description.txt',  index=False)