This project was generated with Python, DS Libraries and Jupyter Notebooks
This is a python data science project where I was required to analyze financial inclusion the above named countries and give my expert opinion depending on various variables using univariate, bivariata and multivariate statistics
The research problem is to figure out how we can predict which individuals are most likely to have or use a bank account.
You must have python and Jupyter notebooks to analyze, peruse and see the analysis.
- Clone this project from https://github.com/cnyakundi/financial_inclusion
- Python
- Jupyter Notebooks
- Google Collab
- Pandas
- Numpy and
- Matplotlib among others.
For any difficulties accessing the code, comments, concerns, ideas or any form of questions. Kindly contact me at cypriannyakundi@gmail.com
MIT License
Copyright (c) 2020 Cyprian Nyakundi
Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.