MTA

Introduction

This is the first project for the T5 Data Science Bootcamp, which is an exploratory data analysis of the MTA turnstile data set using SQL paired with Python and its libraries Pandas, NumPy, Matplotlib, and seaborn

Analysis for the Electricity Company for the maintenance of lighting in stations The goal of this analysis is to give the electric company more information about the best time to perform lighting maintenance on New York City subway stations using MTA Turnstile data.

And the best time will be determined at the MTA stations for the electricity company to work to maintain the lighting and to perform their work in the best way and in non-peak times.

MTA Turnstile Data:

Data obtained from http://web.mta.info/developers/turnstile.html.

Tools:

• SqLlit
• qlalchemy
• Jupyter Notebook
• Python
• Pandas
• numpy
• Matplotlib
• Seaborn

Deliverables:

Presentation describing our findings and recommendations. EDA Analysis using python