Alright, let's talk about this "missing renoir paintings" thing. So, I stumbled upon this dataset online, right? Sounded interesting, a bit mysterious, and I was itching for a project. Figured, why not try and see what I could dig up?
First thing I did was grab the data. It was a CSV file, nothing fancy. I used pandas in Python to load it up. Quick `*_csv()`, and boom, I had a dataframe staring back at me. The data itself was pretty straightforward – columns like "title," "artist," "year," "style," you know, the usual art stuff.
Next up, data cleaning. Always gotta do this, right? Checked for missing values. Found a few in the "year" column. Decided to fill those with the mean year from the dataset. Not perfect, but better than leaving them blank. Also, some of the titles had weird characters, so I cleaned those up using some regex. Pain in the butt, but necessary.
Then came the fun part: exploring the data. I wanted to get a feel for what I was dealing with. I started with some basic visualizations. A histogram of the years the paintings were created, a bar chart of the number of paintings per style. You know, the kind of stuff you do to get a sense of the landscape. Saw that Impressionism was a big one, no surprise there.
After that, I started digging deeper into the "missing" aspect. Now, the dataset didn't explicitly say which paintings were missing. So, I had to get creative. I figured maybe I could use the "style" and "year" to try and infer something. Like, if there were a gap in the number of Impressionist paintings from a particular year range, maybe something was up.
I grouped the data by style and year, and then counted the number of paintings in each group. Then, I looked for years where the count was significantly lower than the average for that style. It was a bit of a hacky approach, I admit, but it was worth a shot.
I also tried searching online for reports of stolen or missing Renoir paintings. Found a few articles about thefts from museums and private collections. I then cross-referenced the titles in those articles with the titles in my dataset. Unfortunately, no direct matches. Bummer.
Finally, I decided to try a more visual approach. I used the Matplotlib library to plot the data points on a scatter plot, with the x-axis representing the year and the y-axis representing some kind of style category. I was hoping to see some kind of pattern or cluster that would stand out. Didn't really find anything conclusive, though.
In the end, I didn't find any definitive "missing" Renoir paintings using just this dataset. But, it was a fun exercise in data exploration and visualization. It also made me realize that sometimes, the most interesting part of a project is the journey itself, even if you don't find exactly what you're looking for.
Here's a quick rundown of the tools I used:
- Python
- Pandas
- Matplotlib
- Regular Expressions
So, yeah, that's my take on the "missing renoir paintings" project. Nothing earth-shattering, but it was a good way to spend an afternoon. Maybe someone else can take it further!
