Project Overview

The dataset includes information about individual rides made in a bike-sharing system covering the New York City. In the dataset, we have 14 features and several observations (running to millions).

I investigated and analysed features that might have high tendency in the prediction of trip duration(target variable).

I focused on the factors that influence most trip duration. I began by checking the distribution of trip duration together with other features that are important for the presentation.

Afterward, I proceeded to check the relationship of some features with the target variable. I use scatter plots to visualise the relationship, then a heatmap for correlation coefficient values, and bar chart to plot features relationship using the correlation coefficient.

I concluded by relating the trip duration with some categorical and numerical features using pointplot.