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Apple, a mobile phone brand has multiple i-phone models since its launch and it is adding new models almost every year with both software and hardware updates.

Through different buying portals data is being collected regarding the feedback of the customers and other relevant information like the price and discount received by the customer.

As an analyst we want to explore the data and answer the following questions using the past data:

• Which i-Phone model is highest rated among the customers?
• How many customers rated for the highest rated i-Phone model?
• what is the relation between number of ratings and sale price?
• what is the relation between number of ratings and discount percentage?

• Product data: Product name, Product URL, MRP, Sale price, Discount Percentage, Ram, etc.
• Customer data: Number of ratings, Star ratings, Number of Reviews, etc.

To clean the available data and look for the most liked i-Phone model amongst the customers and analyse any trend in the relation between the highest rated model and it’s pricing.

To check if the discount percentage on the model influences the ratings of the product.

The checkpoints for the assignment are as follows:

1. Perform data cleaning and look for null values if any.

2. Perform EDA

• Select variables using the usual methods
• Sort the data points in decreasing order of the star rating
• Look for the Top 10 Product names with highest star ratings

3. Plot a Bar chart with product names of the top 10 highest rated i-phone models on x-axis and number of ratings on y-axis.

4. Plot a Scatter chart with number of ratings on x-axis and sale price on y-axis along with a trendline to analyse the relation between number of ratings and sale price

5. Plot a Scatter chart with number of ratings on x-axis and discount percentage on y-axis along with a trendline to analyse the relation between number of ratings and discount percentage.