Bike Sharing Demand Study using Linear Regression

Build a regression model to understand the factors on which the demand for bike sharing systems vary on and help a company optimise its revenue.

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The purpose of this case study is to build a multiple linear regression model for the prediction of demand for shared bikes.

Table of Contents

• Problem Statement
• Soluation Approach
• Repository contents
• Python libraries

Problem Statement

A US bike-sharing provider BoomBikes has recently suffered considerable dips in their revenues due to the ongoing Corona pandemic. The company is finding it very difficult to sustain in the current market scenario. So, it has decided to come up with a mindful business plan to be able to accelerate its revenue as soon as the ongoing lockdown comes to an end, and the economy restores to a healthy state.

In such an attempt, BoomBikes aspires to understand the demand for shared bikes among the people after this ongoing quarantine situation ends across the nation due to Covid-19. They have planned this to prepare themselves to cater to the people's needs once the situation gets better all around and stand out from other service providers and make huge profits.

The company wants to know:

• Which variables are significant in predicting the demand for shared bikes.
• How well those variables describe the bike demands.

Objective: Build a Linear Regression model for the demand of shared bikes with the available independent variables. It will be used by the management to understand how exactly the demands vary with different features.

Soluation Approach

1. Reading and Understanding the Data
2. Data manipulation and cleaning
3. Visualising the Data
4. Data Preparation
5. Splitting the Data into Training and Testing Sets
6. Building model
7. Residual Analysis of the train data
8. Making Predictions Using the Final Model
9. Model Evaluation

Repository contents

File	Description
Python notebook	It contains the complete detailed code along with necessary output to solve the problem
PDF	Answered the asked subjective questions.
ReadMe.md	This file briefs about the project.
day.csv	The bike sharing case study data set.
data_dictionary.txt	Meaning of the variables in the dataset.

Python libraries

1. numpy
2. pandas
3. seaborn
4. matplotlib
5. sklearn
6. statsmodels

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Created by Anupam Maiti - feel free to contact me!