Iris Flower Data Visualization

Inspiration

I was inspired by the need to practice and apply my data visualization skills on real-world datasets to better understand patterns and insights.

What it does

The project creates a simple scatter plot that visualizes the relationship between sepal length and width for three different species of iris flowers.

How we built it

I used Python, along with the Seaborn and Matplotlib libraries, to load the Iris dataset and create the visualization in a Jupyter notebook.

Challenges we ran into

One challenge was deciding which specific features of the dataset to visualize in a way that made the differences between the species clear.

Accomplishments that we're proud of

I'm proud of how the final visualization effectively showcases the differences between species in a clean, easy-to-understand format.

What we learned

I learned how small design choices in data visualization can have a big impact on clarity and how to effectively use Seaborn for such tasks.

What's next for Iris Flower Data Visualization

Next, I plan to explore more advanced visualizations and possibly add interactivity to make the project more engaging.

Built With

• google-colab
• python
• seaborn