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Report: act_report
Analyzing and Visualizing WeRateDogs
By Michael Obioha
Introduction
WeRateDogs is a Twitter account that rates people'sdogs with a humorous comment about the dog.
These ratings almost always have a denominator of 10. The numerators however are almost always
greater than 10 (11/10, 12/10, 13/10, etc.). In theory the rates should be 1 to 10. However, WeRateDogs
disagree, they admit almost all the dogs deserve a 10 or more than that. This project works through the
data wrangling process, focusing on the gathering, assessing, and cleaning of data. There are
visualizations and observations from the analysis provided as well.
Insights
1. The correlation between the retweet counts, and favorite counts over
time.
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The image above shows that there is a positive correlation. This correlation is important for the owner of
the WeRateDogs Twitter account to understand when determining methods to increase user traffic on
the page. This could be of great use to a team of data analysts or a twitter page owner who wants to
model thei posts based on previous recommended posts with high retweet counts or high favorite
counts
2. The most used Twitter Source
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Clearly from the visualization above we can see that most Twitter users use Twitter for iPhone on the
page. With a value count of 1955 tweets, while twitter Web Client and TweetDeck has a value count of 28
and 11 tweets respectively
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Names are important, even for dogs. The four most popular dog names are Charlie, Oliver, Cooper, and
Lucy. The most most popular dog name is Charlie with 11 counts, the close second most popular names
are Lucy, Oliver and Cooper with all three names having a tie at 10 counts respectively
conclusion
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There is a lot more that can be done with this dataset, a lot more quallity and tidiness issues can be
found and we can clean the data to produce an even better dataset. Take a good look at the dataset and
discover more things to analize.
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