Please see attachment The CNN Money’s Market Movers website...

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Please see attachment
The CNN Money’s Market Movers website (https://money.cnn.com/data/hotstocks/ ) tracks the most active stocks on a real time basis. Specifically, the most active, the top gainers and top losers are listed at any instance in time. You will first write Python scripts that collect the list of most actives, gainers and losers from the above website. Next, your programs should take the ticker symbols and names of these companies (and categories) and build a csv file (called stocks.csv) with data about each stock from the website:

finalprojectfall2019-1-snwz0gs0.pdf

Prasun Kumar · Accepted Answer

INSY5336_KiaThompson
  
    
INSY 5336 - Python Programming¶
Fall 2019 - Final Term Project¶
By Kia Thompson¶
Install the additional modules used
	BeautifulSoup - used to parse the web page
	requests - used to download the web page
In [1]:
    
#Make sure the necessary modules are installed 
!pip install BeautifulSoup4
!pip install requests

Requirement already satisfied: BeautifulSoup4 in c:\programdata\anaconda3\lib\site-packages (4.6.3)
Requirement already satisfied: requests in c:\programdata\anaconda3\lib\site-packages (2.21.0)
Requirement already satisfied: chardet=3.0.2 in c:\programdata\anaconda3\lib\site-packages (from requests) (3.0.4)
Requirement already satisfied: idna=2.5 in c:\programdata\anaconda3\lib\site-packages (from requests) (2.8)
Requirement already satisfied: certifi>=2017.4.17 in c:\programdata\anaconda3\lib\site-packages (from requests) (2018.11.29)
Requirement already satisfied: urllib3=1.21.1 in c:\programdata\anaconda3\lib\site-packages (from requests) (1.24.1)
The required modules, namely, requests, BeautifulSoup and CSV are imported
In [2]:
    
#Importing the necessary modules 
import requests
from bs4 import BeautifulSoup
import csv
    
Part 1
Python script to collect the list of most actives, gainers and losers from the CNN  Money’s Market Movers website
The web page (CNN website) is downloaded using requests library.
Running the web page through Beautiful Soup gives us a BeautifulSoup object, which represents the document as a nested data structure (hereby referred to as soup).
In [3]:
    
#Lets read the CNN website and make a soup 
url = "https://money.cnn.com/data/hotstocks/"
r  = requests.get(url)
data = r.text
soup = BeautifulSoup(data)
    
Here the assumption is that the 3 tables of 'Most Active', 'Top Gainers' and 'Top Losers' will always be in the same order on the CNN web page
In [4]:
    
#Assuming the 3 tables are in this order
tables = ['Most Active', 'Top Gainers', 'Top Losers']
flag = 0
    
A lot is happening in this cell.
	3 dictionaries are initiated. In case of re-run, the dictionaries must be emptied and filled again.

Please see attachment The CNN Money’s Market Movers website (https://money.cnn.com/data/hotstocks/ ) tracks the most active stocks on a real time basis. Specifically, the most active, the top gainers...

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