Scraping_Data_from_Websites.py

# coding: utf-8

# ## Import Libraries

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import bs4 as bs
import urllib.request


# ## Store HTML source code in a variable

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src = urllib.request.urlopen('https://www.nytimes.com/').read()


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bsoup = bs.BeautifulSoup(src, 'lxml')


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print(bsoup)


# ## Extract Title of the web page

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print(bsoup.title.text)


# ## Extract URLs

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for link in bsoup.find_all('a'):
    print(link.get('href'))


# ## Extract Paragraphs

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print(bsoup.p)


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print(bsoup.find_all('p'))


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print(bsoup.find('p').get_text())


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ptags = bsoup.find_all('p')
for p in ptags:
    print(p.text)


# ## Extract Table Data

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src = urllib.request.urlopen('http://www.espn.com/nba/statistics/player/_/stat/assists/sort/avgAssists/').read()
bsoup = bs.BeautifulSoup(src, 'lxml')
tbl = bsoup.find('table')


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tbl_rows = tbl.find_all('tr')
for tr in tbl_rows:
    td = tr.find_all('td')
    row = [i.text for i in td]
    print(row)


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type(row)


# ## Extract Table Data using Pandas

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import pandas as pd 
data = pd.read_html("http://www.espn.com/nba/statistics/player/_/stat/assists/sort/avgAssists/")
for df in data:
    print(df)


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