Web Scraping - Data Analysis of Women's Shoes
There’s a research online saying that in Britain, women own an average of 24 pairs of shoes. Women love to buy shoes and therefore made women’s footwear a large potential market all over the world.
this project, I working on the potential market of women’s shoes by comparing the brands, pricing, and reviews.
Data Gathering For
Macy’s is one of the largest retailers that provides footwear in store and online. It sells thousands of women’s shoes from many different brands. Therefore, I used Sublime to gather data of my targeted products from Macy’s online shopping website directly.
I successfully gathered 10782 samples with the following information:
- Brand
- Description of the Shoes
- Original pricing
- On-sale pricing, if any
- Number of review
- Rating
- Shoe type
For shoes that are not on sale, I inserted the original price so that I could calculate the sale percentage of each pair of shoes. Some other kind of data cleaning was proceeded as information scraped contains special characters such us dollar sign.
Questions
Some questions were raised before I look into the details of the dataset
- What are the brands with expensive products?
- What the brands with most products on sale?
- Are winter shoes having a higher sale percentage in summer?
- What’s the relationship between number of review and rating?
- What are the popular brands?
With above questions, I used Python in Jupyter Notebook to analyze my dataset with graphs and charts.
Data Analysis
When looking into my dataset, I found that there are 209 brands of shoes. Based on the original price, below is the table showing the top 15 brands with high average pricing. Frye has the most expensive shoes with an average of $246.17 per pair. This may give customers an overview of pricing range of each brand.
However, there might also be some bias since we are not sure that whether the brand is selling all of its products on Macy’s. For instance, if one brand has only one pair of shoes selling on Macy’s website with a high pricing, it doesn’t necessarily mean that shoes from this brand is more expensive than others.
To better help customers to choose the brand with more savings, I’ve analyzed the top 10 brands with the most numbers of shoes on sale. As showing below, Skechers, Clarks, and Olivia Miller are the 3 brands which having more than 100 products that are on sale. Some well-known and popolar brands such as Easy Spirit and DKNY are also having high numbers of on-sale products.
Since I scraped the data during the early summer season, I was also wondering that whether winter shoes are having a higher on-sale percentage. In other words, is it more valuable for women to purchase winter shoes in summer instead of winter? With this question, I selected the products which are currently on sale and made below boxplot with shoe type as my x axis and sale percentage as my y axis.
As we see, boots and booties are having a wide range of sale percentage. Both of their medians and 75% boundaries are high as well comparing to most of the other types of shoes. I also noticed that range of boat shoes is extremely narrow, which is very different than all the other types. This attracted my attention of looking into the data of boat shoes and it turned out that there are only 12 boat shoes selling on Macy’s website.
From below, I would suggest ladies to purchase winter footwear in summer since there will be a bigger on-sale in summer that can save one’s budget.
Once purchase the shoes, customers are able to select a rate from 1 to 5 stars. I converted it to a 0 t 100 scale during scraping. Will more number of reviews (more sells) make the rating higher? The answer is no based on below plot. The correlation coefficient between the two features is 0.076 which also indicates that there’s very weak relationship.
Among all the products which have rating, the average rating of all products is 80.17 and median is 85.15. The 25% - 75% range is from 71.43 to 93.88. Therefore, rating below 71.43 might be considered as a lower quality or less satisfying footwear. This may also help customers to make better decision before clicking on the “add to cart” button.
I arranged the top 15 brands with the largest number of reviews, in other words, they most popular brands. UGG, Crocs, and Adidas are the top 3 brands of popularity. Box plot below shows the range of rate of these 15 brands. As we see, based on my analysis above on rating score, most of these 15 brands are having goods rates with only a few countable numbers of low rates. Therefore, I would consider these brands as popular and having good quality for purchasing.
After all of the above analysis, I wonder what the most popular product is. Therefore, I found that the clogs from Crocs below is our best seller with the largest number of reviews! However, the description says that it is for men and women which might be one of reason that makes it the best seller. As we are only considering the women’s shoes in this project, this is a bias of my finding on below.
Conclusion
My analysis answered the questions with my personal interest as a customer at very beginning of the project. I also wish that my answers provided some useful advice to women on how to choose the brand of footwear and how to purchase footwear with lower expenditure.
The skills I demoed here can be learned through taking Data Science with Machine Learning bootcamp with NYC Data Science Academy.
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