The data presented is from WeRateDogs twitter account. It is about rating dogs based on their pictures. The dataset provided is composed of three datasets: the twitter archive, the image predictions and the additional data provided from the twitter API. The twitter archive contains data about tweets posted by the WeRateDogs twitter account. The data frame involves metadata about the tweet (id, timestamp, url & source), the text of the tweet, the reply and retweet status, the ratings and the dog stages (puppo, doggo, pupper and floofer) given by WeRateDogs. The image predictions table contains predictions made by a neural network based on the pictures of the dogs provided in the tweets. The additional data provided by the API contains the favorite count and retweet count for each tweet.
The data was gathered from different sources (manually downloaded, from API..). Then, we assessed the data and cleaned it to obtain one single tidy table. The cleaned data was used in the exploratory part, provided with extracted insights and visualization.
This repo presents the following files:
twitter_archive_master.csv: The twitter archive table.image-predictions.tsv: contains the predictions of the NN.twitter_archive_master.csv: the twitter archive dataset stored after wrangling, used in the analysis.tweet_json.txt: the additional data provided by twitter's APIwrangle_act.ipynb: the notebook that contains the code for data gathering, wrangling and analysis.wrangle_report.html: report of the data cleaning processact_report.html: report of the insights extracted from the analysis.