Exploratory Data Analysis (EDA): NYC Taxi Trip Duration

Project Aim:

This project focuses on performing an Exploratory Data Analysis (EDA) on the NYC Taxi Trip Duration dataset from a Kaggle competition. The goal is to understand the factors influencing taxi trip durations in New York City by inspecting, cleaning, and analyzing the provided data. This includes identifying patterns, relationships, and potential outliers within the dataset to gain insights into trip characteristics and their impact on duration.

Tools and Technologies Used:

Python: The primary programming language used for data manipulation and analysis.

pandas: A powerful library for data loading, cleaning, transformation, and analysis.

NumPy: Used for numerical operations and calculations, particularly in the haversine distance function.

Matplotlib: The chosen library for creating visualizations (histograms, boxplots, scatter plots, heatmaps) to explore data distributions and relationships.

Google Colab: The development environment where the analysis was conducted.