Data Analysis Projects

Welcome to the Data Analysis Projects repository! This collection features various data analysis projects using Python, designed for learning and improving data analysis skills.

Table of Contents

• Introduction
• Projects
• Installation
• Usage

Introduction

This repository highlights different data analysis projects utilizing Python, with a focus on ARIMA time series analysis and supply chain optimization.

Each project includes thorough analysis, implementation, and visualization using popular Python libraries.

Projects

1. ARIMA Time Series Analysis

• This project delves into ARIMA (AutoRegressive Integrated Moving Average) models for time series forecasting. It covers model fitting, diagnostics, and predictions using real-world datasets.
• Libraries Used: pandas, numpy, matplotlib, statsmodels
• File: arima.ipynb

2. Sales Conversions

• The project Presents an analysis of lead conversion data collected from a travel booking company. The dataset includes various attributes related to leads, their sources, assigned agents, enquiry destinations, and the outcomes of these leads.
• Libraries Used: pandas, numpy, matplotlibsqlite3
• File: conversions.ipynb

3. Olympics Dataset Analysis

• Provides a comprehensive analysis of the Summer and Winter Olympic athletes and their results from 1896 to 2022.
• Libraries Used: pandas, numpy, matplotlib, sqlite3, os
• File: clean_data.ipynb

and many more to come...

Installation

To run the projects locally, follow these steps:

1. Clone the repository:

   git clone https://github.com/dakshbhatnagar/projects.git
   cd projects

2. Navigate to your folder of choice:

   cd Your_Folder_Of_Choice

3. Install the required Python libraries:

   pip install -r requirements.txt

Usage

Navigate to each project directory and open the Jupyter Notebook files to view detailed analysis, code, and visualizations.

Happy Exploring!!