mar12_dashboard

Inspiration

We were inspired by the many charts and graphs that we can plot in Python using the libraries. This discovery was made by attending the workshops hosted by BBCS.

What it does

In our project, there is a filter system that allow users to filter the dataset by Species Name, Country and Ecosystem. Our dashboard will then provide detailed insights about the dataset after filtering, and is presented in a visual way. This includes using box plots, pie charts or heatmaps.

How we built it

This code is written in Python. We participated in the BBCS Hackathon where they have provided us with workshops such as "Data Manipulation: Numpy and Pandas" and "Project Deployment: Streamlit". This taught us many valuable skills that helps us to build our final project.

Challenges we ran into

Some challenges we faced were struggling with finding a suitable dataset that can help us with the project. It took us quite a while to be able to do so. It also took us a while to understand how to use the Python libraries that we were taught as we were new to it.

Accomplishments that we're proud of

We are proud of being able to manage our time properly. We are also proud that we could get the hang of using the Python libraries that we were taught, and put it into good use in our project.

What we learned

We have learnt how to use the many important Python libraries needed for data analysis. This includes using Numpy, Pandas, Seaborn, Matplotlib and Streamlit.

What's next for mar12_dashboard

We are looking to improve on how to make the dashboard (featured in our project) to be more visually appealing. We also hope to add more useful features that further enhances interactivity on our dashboard. This includes elements such as a scroll bar in the filter system featured on our project.

Built With

• python