Pacific-Data-Analytics - Datathon 2024 🚧

Project: Climate and risk Variables Visualization and Their Impact on Agriculture in the Colombian Pacific Region

Members:

• Juan Andrés Ruiz Muñoz - 4th semester - Data and Artificial Intelligence Engineering
• Martín García Chagueza - 4th semester - Data and Artificial Intelligence Engineering
• Laura Sofía Hoyos Espinosa - 4th semester - Mechanical Engineering
• David Melo Valbuena - 4th semester - Data and Artificial Intelligence Engineering

Description

Our project focuses on analyzing and visualizing climate variables and their potential impact on agriculture in the Colombian Pacific region. We aim to provide comprehensive insights into how factors like temperature, atmospheric pressure, precipitation, environmental crimes, and climatic emergencies affect the agricultural sector. Utilizing open data platforms through APIs, we encourage citizen participation and enable informed decision-making.

Requirements

• Python
• request (Library, you can install with "pip install request")
• pandas (Library, you can install with "pip install pandas")
• Jupyter Notebook (Library, you can install with "pip install notebook")
• Power BI desktop (For data visualization, you can install in: https://www.microsoft.com/es-ES/download/details.aspx?id=58494&msockid=2ce454667cc26ccf3a6840c47d6d6d83).

Environment setup

• Git clone:

  git clone /~https://github.com/JuanRuizIng/Pacific-Data-Analytics.git
  

• In "Temperatura", "Presión Atmosférica" and "Precipitaciones" folder: run only the code 😃

• In "Delitos Ambientales" folder: Execute all

• In "Emergencias" folder execute all in this order:

  1. emergenciasAPI_limpieza.ipynb
  2. emergenciasExcel_limpieza.ipynb
  3. dashboardEmergencias_limpieza.ipynb

Results

When you run the code, it will automatically clean up the code and make a csv file which you can load into your Power BI. Note: if you load it once and want to update the file, you just have to repeat the process of running the code and click on the "Refresh" (in Spanish is: "Actualizar modelo") option in the Power BI tables. How can load the csv into your Power BI: https://www.youtube.com/watch?v=Hgs5pRdf68U How to refresh the csv into your Power BI: https://learn.microsoft.com/en-us/power-bi/connect-data/refresh-desktop-file-local-drive

See the dashboard!

https://app.powerbi.com/view?r=eyJrIjoiMTM1MWQ2YmQtMDU0ZS00ZjA0LTgyY2UtY2I2NjY5NTYwM2EzIiwidCI6IjY5M2NiZWEwLTRlZjktNDI1NC04OTc3LTc2ZTA1Y2I1ZjU1NiIsImMiOjR9

How can improve?

In this team we convince ourselves to improve with each passing day. For that, what could we be missing?

• Data connection through a database: It's crucial for real-time data visualization.
• Virtual enviroment creation: Essential for users with limited disk space.

These improvements will be applied very soon with the impressive learnings we will have in databases and ETL for big data analysis.

You dream, we will provide the data!

Thanks for all team! We will see in the next Datathon!