For this assignment, you are required to scrape data from e-commerce or other websites such as Lelong, Lazada, Mudah, iProperty, Booking, Expedia etc.
You are required to fork this Jupyter Notebook from my Github here and then scrape the latest 1000 items from one of the website mentioned above. The scraped data should include:
- Product Name/Product Title
- Amount/Price
- Brand
- Comments/Reviews
- Number of views
In addition, you are required to export the scraped data to dataframe format and also save a copy in csv format. Upon successful extracting data to dataframe, you are required to do a data analysis on the data.
Your analysis should provide answers to the following questions:
- What do you think is interesting about this data? Tell a story about some interesting thing you have discovered by looking at the data.
- Visualize your data with matplotlib or with folium library package.
For example, you might consider whether there is a difference in pricings at different times doing the day or city, or whether other factors that influnced the pricings etc. Another thing you might consider is whether there is a relationship between the pricing and number of reviews or comments.
Show your analysis workflow in your Jupyter notebook.
The final submission should be pushed back to your respective Github account.