Analysing-Web-Statistics

Problem Statement :

We have dataset (web_taffic.tsv) which contains :

• Hour
• Number of users visited our website in the given hour.

We will be predicting the hour at which we will cross 100,000 hits/hour on our website.

**100,000 hits/hour = 100,000 users visited our website in 1 hour.

Pre-Requisites :

For Mac user:

Create a project directory and open a terminal instance in project directory. Run following commands to setup environment and pre-requisites.

• Get source code : git clone https://github.com/x-coderx/Analysing-Web-Statistics.git
• Install Python : brew install python@3.9
• Create your virtual environment : python3.9 -m venv venv
• Activating your virtual environment : source venv/bin/activate
• Install Requirements : python3.9 -m pip install -r requirements.txt
• Finally, run "analyze_webstats.py"

For Windows user:

Create a project directory and open a cmd instance in project directory. Run following commands to setup environment and pre-requisites.

• Get source code : git clone https://github.com/x-coderx/Analysing-Web-Statistics.git
• Download latest python version from : https://www.python.org/ftp/python/3.12.1/python-3.12.1-macos11.pkg and install.
• Create your virtual environment : python -m venv venv
• Activating your virtual environment : venv\scripts\activate
• Install Requirements : python -m pip install -r requirements.txt
• Finally, run "analyze_webstats.py"

Idea :

Idea is to use curve-fitting and Logistic Regression on our data in order to predict the hour at which we will cross 100,000 hits/hour on our website.