Unemployment Analysis using Python:

I have created an Application using Python and its Libraries to implement data science and machine learning concepts and analyse the unemployment rate of different states in the country of India. I have used Python Pandas, Numpy, Matplotlib, and Seaborn Libraries to implement this project.

Technologies:

Language: Python
Platform: Google Colab Python3 Runtime Engine
Libraries: Pandas, Numpy, Matplotlib, and Seaborn
Dataset used: Unemployment_Rate_upto_11_2020.csv (Source: Kaggle)


Installation of Libraries

I have implemented the project using Google Collaboration, which is an open-source, cloud-based platform for the implementation of machine learning and data science projects.
As all the required libraries are already pre-installed in the Google Colab Python3 runtime engine, we do not need to install them separately using the pip command, which we generally do when using a Jupyter notebook on our PC.


How to use:

Just open the Google Collaboratory using your Google account and import the jupyter source file (UNEMPLOYMENT_ANALYSIS_WITH_PYTHON.ipnyb) and the dataset (Unemployment_Rate_upto_11_2020.csv) to Google Collaboratory virtual storage (Google Collaboratory File Upload Method).

Then run the project using the Google Colab Python 3 runtime engine. I have also attached here the html file and corresponding pdf file to see the outcome of the project.




Output: Jupyter Source file (.ipnyb), HTML file, and pdf file attached already.