Alright, so today I’m gonna spill the beans on my little “harbaugh family” project. It’s nothing crazy, just a fun way I decided to mess around with some data and try to visualize family connections. Let’s dive right in.
First off, I started with the basics: gathering the data. I basically just googled around and pieced together info about the Harbaugh family – you know, Jim, John, their dad Jack, and the whole gang. Birthdates, coaching history, that kinda stuff. I dumped it all into a simple spreadsheet. Nothing fancy, just names, relationships, and dates. Think of it as a glorified notepad, but with columns.
Next up, I fired up my trusty Python interpreter. I’m no expert, but I can fumble my way through some code. I used the `pandas` library to load the data from the spreadsheet into a DataFrame. It’s like magic, really. Suddenly, all that messy data is organized and ready to be poked at. Then, I messed around with `matplotlib` and `seaborn` to try and create some basic visualizations. I’m talking bar charts showing their coaching wins, maybe a timeline of their careers. Super basic stuff.
Then I thought, “Hey, how can I make this look even cooler?” That’s when I decided to try using a network graph. I remembered seeing something about `networkx`, so I installed it and started digging through the documentation. It took me a while, and there was a lot of trial and error, but I managed to create a graph where each family member was a node, and the edges showed their relationships. I even got fancy and colored the nodes based on their primary role (coach, player, etc.).
The real challenge was figuring out how to display the graph in a way that made sense. The default layout was just a jumbled mess of lines and circles. So, I played around with different layout algorithms – spring layout, circular layout, you name it. Eventually, I settled on something that looked halfway decent, where the family members were clustered together in a vaguely logical way.
I also spent some time cleaning up the visual aspects. Adding labels to the nodes, adjusting the edge thickness, tweaking the colors. It’s all about making it easy to understand at a glance. You know, make it look presentable!
Finally, I saved the graph as an image and wrote a little blurb explaining what it all meant. It’s not gonna win any awards, but it’s a fun little project that helped me brush up on my data visualization skills.
So, yeah, that’s the story of my “harbaugh family” project. Nothing groundbreaking, but a good way to spend a weekend afternoon. I learned a bunch about `pandas`, `matplotlib`, and `networkx`, and I now have a slightly better understanding of the Harbaugh family. Maybe next time I’ll try to add even more data and make it interactive!
- Gathered data
- Wrangled data with Pandas
- Vizualized it with Matplotlib
- Network Graph with Networkx
Keep hustling!
