17_rent_data.py

url = requests.get('https://www.rentcafe.com/average-rent-market-trends/us/ca/los-angeles/').text
soup = BeautifulSoup(url,"html.parser")

table = soup.find('table',id="MarketTrendsAverageRentTable")
pr = table.find_all('td')
nh = table.find_all('th')

price = []
neighbourhood = []

for i in range(0, len(pr)):
    price.append(pr[i].text.strip())
    neighbourhood.append(nh[i+2].text.strip())
        
df_rent = pd.DataFrame(data=[neighbourhood, price]).transpose()
df_rent.columns = ['Neighbourhood', nh[1].text]


df_rent[(df_rent['Neighbourhood']=='Harvard Heights') | (df_rent['Neighbourhood']=='Korea Town')]