Shopify-App-Store-Data-Science

Data on Shopify App Stores, Ratings, and Reviews from Kaggle used to generate exploratory data analysis question, determine which figures and tables to use to answer these.

Objective:

The objective of this data science project is to take the data relating to the Shopify App Store and determine why certain applications are the most/least popular based on category, features, ratings, and reviews and what makes them the most/least successful. My goal from this is to develop my skills with pandas, NumPy and matplotlib by analysing the data, and creating graphs to visualize the data.

Exploratory Data Analysis Questions (EDA)

A data map was created using the CSV files that are under data to understand the relationships between each set of data and how to connect them. This is created in a powerpoint; the remaining slides are used to describe the information that is being presented in each of the different columns.

Categories Data:

1. How many categories of apps are there? How many apps per categories (pie graph)
2. How many different features are there and what are the main features of apps in certain categories? (Benefits)
3. What category has the highest number of reviews? Does this relate to the number of features provided?
4. What is the average rating per category

Apps Data:

1. What is the average rating per app?
2. What are the benefits listed for the app and how do they relate to the bad reviews? Good reviews?
3. What kinds of apps are the most popular? least popular?
4. Why are certain apps the most popular? Why are certain apps the least popular?

Features Data:

1. What features have the highest rating?
2. What features are the most useful (Based on reviews)

Pricing Data:

1. How do the ratings and prices correlate? (Higher prices, lower ratings, etc.)
2. What is the average price for apps in certain categories
3. Price plans?