GDSC-128-APPLICATION-TASK

Task: Data Visualization and Classification

Project: Predicting the chance of an employee of leaving a firm

Dataset: https://www.kaggle.com/manasdalakoti/univai-hack-data

Installation

First, you will need to install git, if you don't have it already.

Next, clone this repository by opening a terminal and typing the following commands:

• $ cd $HOME (or any other development directory you prefer)

• $ git clone https://github.com/Karssido/GDSC-128-APPLICATION-TASK

• $ cd Task-1 (Data Visualization and Classification).ipynb

Python & Required Libraries

Of course, you obviously need Python. Python 2 is already preinstalled on most systems nowadays, and sometimes even Python 3. You can check which version(s) you have by typing the following commands:

• $ python --version # for Python 2

• $ python3 --version # for Python 3

Any Python 3 version should be fine, preferably ≥3.5. If you don't have Python 3, I recommend installing it (Python ≥2.6 should work, but it is deprecated so Python 3 is preferable).

Libraries that are required are mentioned as follows:

• Numpy

• Pandas

• Matplotlib

• Seaborn

• HvPlot

Starting Jupyter

In a terminal or command window, navigate to the top-level project directory GDSC-128-APPLICATION-TASK/ (that contains this README) and run one of the following commands:

• ipython notebook Task-1 (Data Visualization and Classification).ipynb

or

• jupyter notebook Task-1 (Data Visualization and Classification).ipynb

or open with Jupyter Lab

• jupyter lab

This will open the Jupyter Notebook software and project file in your browser.