Wrangle WeRateDogs Twitter data to create interesting and trustworthy analyses and visualizations
For this project, there are 3 datasets that are combined and wrangled.
The WeRateDogs Twitter archive contains basic tweet data for all 5000+ of their tweets, but not everything. One column the archive does contain though: each tweet's text, which I used to extract rating, dog name, and dog "stage" (i.e. doggo, floofer, pupper, and puppo) to make this Twitter archive "enhanced." Of the 5000+ tweets, I have filtered for tweets with ratings only (there are 2356).
Retweet count and favorite count are not included in the twitter archive. This additional data can be gathered using the Twitter's API.
A table full of image predictions (the top three only) alongside each tweet ID, image URL, and the image number that corresponded to the most confident prediction (numbered 1 to 4 since tweets can have up to four images).