https://github.com/jimmymugendi/british-airways-virtual-internship

This repo focuse on websrcappig data from British Airways customer review and analysing the data to unwind new insights.We get to work with the famous BeautifulSoup and requests, as well as pandas for dataframe manipulation and matplotlib for better visualizations of our data,
https://github.com/jimmymugendi/british-airways-virtual-internship

beautifulsoup matplotlib pandas requests

Last synced: about 7 hours ago
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This repo focuse on websrcappig data from British Airways customer review and analysing the data to unwind new insights.We get to work with the famous BeautifulSoup and requests, as well as pandas for dataframe manipulation and matplotlib for better visualizations of our data,

• Host: GitHub
• URL: https://github.com/jimmymugendi/british-airways-virtual-internship
• Owner: Jimmymugendi
• Created: 2024-03-19T16:01:08.000Z (8 months ago)
• Default Branch: main
• Last Pushed: 2024-03-19T16:18:21.000Z (8 months ago)
• Last Synced: 2024-03-19T17:28:33.453Z (8 months ago)
• Topics: beautifulsoup, matplotlib, pandas, requests
• Language: Jupyter Notebook
• Homepage:
• Size: 746 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
Task 1

Web scraping and analysis

This Jupyter notebook includes some code to get you started with web scraping. We will use a package called BeautifulSoup to collect the data from the web. Once you've collected your data and saved it into a local .csv file you should start with your analysis.

Scraping data from Skytrax

If you visit [https://www.airlinequality.com] you can see that there is a lot of data there. For this task, we are only interested in reviews related to British Airways and the Airline itself.

If you navigate to this link: [https://www.airlinequality.com/airline-reviews/british-airways] you will see this data. Now, we can use Python and BeautifulSoup to collect all the links to the reviews and then to collect the text data on each of the individual review links.