Walmart Stores Coffee Analysis

This Python demo project is a practical showcase of using SerpApi's Walmart Search Engine Results API plus how extracted data could be used in exploratory data analysis.

This repo covers:

1. Extracting data from Walmart Organic results.
2. Extracting data from all store pages using SerpApi pagination.
3. Extracting data from 500 Walmart stores. SerpApi provides JSON Walmart Stores Locations with 4.460 stores in total.
4. My full process of exploratory data analysis.

There's also a full blog post that also shows data extraction steps: https://serpapi.com/blog/serpapi-demo-project-walmart-coffee-exploratory-data-analysis/#extracting-walmart-data

Kaggle Dataset: https://www.kaggle.com/datasets/dimitryzub/walmart-coffee-listings-from-500-stores

Key Takeaways

1. The most popular coffee seller is Walmart.
2. The most popular coffee type is medium roast.
3. More weight (grams) doesn't equal higher price.
   • A lower gram coffee may cost more than a higher gram coffee.
4. The highest coffee weight is 2835 grams (2.8 kg).
5. "Folgers classic roast ground coffee" has 15k+ reviews which is the maximum value from data set.
6. ~300-500 grams is the most frequent weight.
7. The highest coffee price is $77 (Lavazza perfetto single-serve k-cup)

Data Sources

Walmart. Data was extracted using Walmart Search Engine Results API from SerpApi.

Plots

Most Frequent Weight (~300-500 grams)

Higher weight = higher price?