/lab-eda-univariate

Primary LanguageJupyter Notebook

Lab - EDA Univariate Analysis: Diving into Amazon UK Product Insights

Objective: Explore the product listing dynamics on Amazon UK to extract actionable business insights. By understanding the distribution, central tendencies, and relationships of various product attributes, businesses can make more informed decisions on product positioning, pricing strategies, and inventory management.

Dataset: This lab utilizes the Amazon UK product dataset which provides information on product categories, brands, prices, ratings, and more from from Amazon UK. You'll need to download it to start working with it.

Part 1: Understanding Product Categories

Business Question: What are the most popular product categories on Amazon UK, and how do they compare in terms of listing frequency?

  1. Frequency Tables:

    • Generate a frequency table for the product category.
    • Which are the top 5 most listed product categories?

  2. Visualizations:

    • Display the distribution of products across different categories using a bar chart. If you face problems understanding the chart, do it for a subset of top categories.
    • For a subset of top categories, visualize their proportions using a pie chart. Does any category dominate the listings?

Part 2: Delving into Product Pricing

Business Question: How are products priced on Amazon UK, and are there specific price points or ranges that are more common?

  1. Measures of Centrality:

    • Calculate the mean, median, and mode for the price of products.
    • What's the average price point of products listed? How does this compare with the most common price point (mode)?

  2. Measures of Dispersion:

    • Determine the variance, standard deviation, range, and interquartile range for product price.
    • How varied are the product prices? Are there any indicators of a significant spread in prices?

  3. Visualizations:

    • Is there a specific price range where most products fall? Plot a histogram to visualize the distribution of product prices. If its hard to read these diagrams, think why this is, and explain how it could be solved..
    • Are there products that are priced significantly higher than the rest? Use a box plot to showcase the spread and potential outliers in product pricing.

Part 3: Unpacking Product Ratings

Business Question: How do customers rate products on Amazon UK, and are there any patterns or tendencies in the ratings?

  1. Measures of Centrality:

    • Calculate the mean, median, and mode for the rating of products.
    • How do customers generally rate products? Is there a common trend?

  2. Measures of Dispersion:

    • Determine the variance, standard deviation, and interquartile range for product rating.
    • Are the ratings consistent, or is there a wide variation in customer feedback?

  3. Shape of the Distribution:

    • Calculate the skewness and kurtosis for the rating column.
    • Are the ratings normally distributed, or do they lean towards higher or lower values?

  4. Visualizations:

    • Plot a histogram to visualize the distribution of product ratings. Is there a specific rating that is more common?

Submission: Submit a Jupyter Notebook which contains code and a business-centric report summarizing your findings.