Final-Project-Statistical-Modelling-with-Python

Project/Goals

The goal of the project was to access data using Citybike's, Yelp, and Foursquare's API, clean and transform data using Python, and load data into a database. Then, perform EDA, using both statistics and visualizations, identify trends and patterns in data using statistical models and interpret those results.

The goal was to predict AVAILABLE BIKES in bike stops in London using Station Numbers, Latitude and Longitude, Average rating of parks, Total rating count, and Number of parks that are 1,000m around the bike station.

Process

1. Explored the structure of the APIs and choose London as the city

2. Gathered data from CityBike, Foursquare, and Yelp

3. Joined and cleaned gathered data

4. Exploratory Data Analysis

5. Regression Model Development

6. Model Evaluation and Interpretation

Results

On average, Foursquare had 107 reviews, while Yelp had an average of 61 reviews.

Challenges

Obtaining comprehensive and reliable data on London parks, including customer reviews, posed a challenge due to data availability constraints.
Not enough time sorting, cleaning and joining the data

Future Goals

To improve the predictive power and accuracy of the regression model

georgeedgar00 / Statistical-Modelling-with-Python