Okay, so check it out, I’m gonna walk you through my little “wwe bangor” project. It wasn’t like, some huge deal or anything, but I learned a few things along the way, and figured I’d share.
It all started ’cause I was messing around with some data I scraped online. Nothing crazy, just some info about wrestling events, and Bangor just happened to be a location in the dataset. I wasn’t planning anything specific, but I figured, “Hey, let’s see what I can do with this.”
First thing I did was fire up my Python environment. I’m a big fan of Pandas, so I loaded the data into a DataFrame. It was kinda messy, with dates all over the place and some missing info. So, I spent a chunk of time just cleaning that up. You know, removing duplicates, filling in missing values where I could, and making sure the dates were in a consistent format.
Next, I wanted to see what kind of events happened in Bangor. I grouped the data by event type and counted how many times each type occurred. Turns out, there were a lot of different kinds of shows – house shows, TV tapings, the whole shebang. It was kinda cool to see the variety.
Then I thought, “Okay, let’s visualize this.” I’m a Matplotlib kinda guy, so I used that to create a few bar charts. One showed the distribution of event types, and another showed the number of events per year. It made it a lot easier to see the trends at a glance.
Now, here’s where I hit a little snag. I wanted to map the venues in Bangor where these events took place. But the data didn’t have exact coordinates, just the city name. So, I had to do some geocoding. I used the geopy library to look up the coordinates for Bangor. It took a little fiddling to get it working right, but eventually, I got the latitude and longitude.
After that, I used Folium to create an interactive map. I dropped markers on the map representing the venues. Each marker had a popup with the venue name and the number of events that took place there. It looked pretty neat!
Finally, I wrote a little script to generate a simple report. It just summarized the key findings – the most common event types, the busiest years, and a link to the interactive map. I saved it as an HTML file so I could easily share it.
Honestly, the whole thing was pretty straightforward. The biggest challenge was just cleaning the data and figuring out the geocoding. But it was a fun little project, and it gave me a chance to practice my data analysis and visualization skills.
What I learned:
- Data cleaning is always the most time-consuming part.
- Geocoding can be a pain, but it’s super useful for mapping.
- Folium is a great library for creating interactive maps.
So yeah, that’s the story of my “wwe bangor” project. Nothing earth-shattering, but hopefully, it gives you some ideas for your own projects!
