This project aims to predict the GDP of a fictional country with certain resources and values and see what are the most correlated variables with the wealth of a country. The project uses the following parameters to predict the GDP:
- Foreign direct investment (FDI)
- Inflation
- Literacy rate
- CO2
- Internet users
- Labor force
- Female % of total population
- ICT development index
- Energy production
- Exchange rate
The main libraries used in this project:
dash: an open-source framework for building data visualization interfaces. Released in 2017 as a Python librarypandas: a fast, powerful, flexible and easy to use open source data analysis and manipulation tool.geopandas: an open source project to make working with geospatial data in python easier.numpy: a Python library adding support for large, multi-dimensional arrays and matrices, along with a large collection of high-level mathematical functions to operate on these arrays.plotly: an open-source module of Python that is used for data visualization and supports various graphs like line charts, scatter plots, bar charts, histograms, area plots, etc.scikit_learn: scikit-learn is a free and open-source machine learning library for the Python programming language.
You can check the live demo via this link: https://dream-land-13d7.onrender.com/ (The initial load might take a minute because of the web host).
The project is deployed on Render; A free web host.
You can check it on https://render.com/
If you have any feedback, please reach out to us at [email protected]