There are 3 data sources in this WeRateDogs project. WeRateDogs is a Twitter account that rates people's dogs with a humorous comment about the dog. The first dataset is The WeRateDogs Twitter archive, which I uploaded a csv file called 'twitter-archive-enhanced.csv'. I'll need its tweet IDs later. Then I used requests module to get tweet image predictions data using url 'https://d17h27t6h515a5.cloudfront.net/topher/2017/August/599fd2ad_image-predictions/image-predictions.tsv'. The last dataset I gathered was additional data from Twitter API. To use Twitter API, I created my first Twitter account and applied for a developer account. Luckily, I passed the application! With a developer account, I created a project and got token and secret, which I used for authentication. Then I was able to use tweepy module to query Twitter's API for JSON data for each tweet ID in the The WeRateDogs Twitter archive. The data I extracted via API was tweet_id, favorite_count and retweet_count. I mainly used seaborn and matplotlib modules for my analysis, and it covered one-variable distribution, two-variable correlation etc.