I tried to conduct some exploratory analysis on the title field of the “Shopee - Price Match Guarantee” dataset. I wanted to know how similar the titles are within the same group, so we can have a rough idea of how useful the field would be in determining if two listings belong to the same group.
I used StringDistances.jl for raw string analysis and WordToeknizers.jl for token analysis. Instead of using Jupyter Notebook, I used Pluto.jl to get reactive notebooks with more presentably visual design right out of the box. The experience was a blast. Writing in Julia is not as hard as I expected, and the end result is very clean and blazing fast.
Pluto.jl notebooks are just
.jl scripts. They are directly readable (unlike
.ipynb format used by Jupyter, which is a JSON file) and easily sharable. It also supports HTML and PDF exports natively. You can find my notebook(s) created for this project below. (Note: currently, I have only cleaned and uploaded the token analysis one. I’ll probably also upload the string analysis one later.)
Token Analysis Example