I'm Soufiane from Morocco. I'm an industrial engineering student and a machine learning and data science enthusiast. I also build web apps both frontend and backend.
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In this project I did some data exploration analysis Covid Data using SQL and Python. Then I used Tableau for further analysis and Data Visualization.
Here is demo of the final resualts I got in this project
- Python
- Tableau
- MySQL
- Excel
- SQL
To use this project, you just need to have RDBMS ( MySQL, SQL Server, ...) installed in your computer for data exploration. In my case I worked with my MySQL. To import the data to your database, this depends on you RDBMS. But in case you have troube, you could also use python for this purpose. It is fast and work with most RDBMS.
This is an example of how to do it with MySQL. You could find the complete code in the CovidData.ipynb file. As you can see I've done some preprocessing before exporting the data to MySQL.
from sqlalchemy import create_engine
import MySQLdb
con = create_engine("mysql+mysqldb://student:student@localhost/CovidData")
vaccinationData.to_sql(con=con, name='Vaccination', if_exists='replace')
Once you are done with data exploration, you could import the data into Tableau fo data visualization.
Contributions are what make the open source community such an amazing place to learn, inspire, and create. Any contributions you make are greatly appreciated.
If you have a suggestion that would make this better, please fork the repo and create a pull request. You can also simply open an issue with the tag "enhancement". Don't forget to give the project a star! Thanks again!
- Fork the Project
- Create your Feature Branch (
git checkout -b feature/AmazingFeature) - Commit your Changes (
git commit -m 'Add some AmazingFeature') - Push to the Branch (
git push origin feature/AmazingFeature) - Open a Pull Request
Distributed under the MIT License. See LICENSE.txt for more information.
- 📫 How to reach me:
If you found this project helpful, feel free to leave a star in GitHub, and share thig project.
Thank you for making it till the end of this README! See you later!
Here is a list of some of the resources I found helpful and would like to give credit to.