Parsing data with Python should always be discussed after getting a good grip on the nuances of machine learning because both the intricate concepts are interlaced with each other. Click on the link first pythonprogramming.net/downloads/intraQuarter.zip and then go forward with parsing the data.
The data set given in the above link resembles the data set we caught hold of when we first visited the webpages before. The point of interest here is that we don’t need to visit the page even. We just need to have the full HTML source code, that’s it! This system is quite similar to parsing the website without disturbing bandwidth use.
First download this machine learning data file, before we get on with our tutorial to teach you how you can pare data with python. The above mentioned dataset provided in the link mimics exactly the way the data was when we visited the web pages at that point of time, but the interesting thing about this is we need not visit the page even.
We do in fact have the full HTML source code so it will exactly be like parsing the website without the annoying use of the bandwidth. Now the first thing to do when we start is to correspond the date to our data, and then we can pull the actual data.
This is the way we start:
import pandas as pd import os import time from datetime import datetime path ="X:/Backups/intraQuarter"