New York Taxi Dataset Analysis:

• This repo is attempting to use New York Taxi Dataset from Google's Big Query to derive some insights.
• All notebooks are using Anaconda Python2

Summary Report of findings: Summary_Report.pdf

Instructions:

1. git clone https://github.com/stephenleo87/nyc-taxi.git
2. pip install -r requirements.txt

Details:

There are 4 Jupyter Notebooks in this repo

1. 01_SQL Query.ipynb

   • All SQL queries are run from Google Cloud's Datalab platform and the data is stored as csv files for use by subsequent notebooks
   • This notebook is included for reference purposes only

2. 02_Fare Prediction.ipynb

   • Attempting to predict the fare amount from the available data such as trip distance, pickup locations, etc
   • TL;DR: Best prediction model achieved RMSE of $3.5

3. 03_Tip Prediction.ipynb

   • Attempting to predict the tip percentage (tip_amount/fare_amount) from the available data such as trip distance, pickup locations, etc
   • TL;DR: Best prediction model could only achieve accuracy of 60% indicating the available dataset is not sufficient to accurately predict tip percentage

4. 04_Destination Prediction.ipynb

   • Attempting to predict the destination location from the available data such as pickup time, pickup location
   • TL;DR: No good prediction model could be found indicating the available dataset is not sufficient to predict dropoff location