{"push_id":3119592870,"size":1,"distinct_size":1,"ref":"refs/heads/master","head":"18fc7cdb93a85336d98b3273284696b1ae736d98","before":"f50d9cdb55df30ec21e4b88c857392887bee338e","commits":[{"sha":"18fc7cdb93a85336d98b3273284696b1ae736d98","author":{"name":"Steven Greulich","email":"21328311dd43f42d958f3e1536975aad4cdd7a43@gmail.com"},"message":"Commit - Initial analysis of outlier rows of NaN\n\nAuthor: Steven Greulich\nPurpose of commit: The purpose of this commit is for the initial analysis of the 2016, 2017 and 2018 data for what had outlier columns in terms of NaN. As a preliminary review of the datasets, I will only be removing columsn from the 2018 and the 2017 datasets as the 2016 dataset did not appear to have any real outlier columns of missing numbers.","distinct":true,"url":"https://api.github.com/repos/greulist137/Udacity-Data-Science-Term-2---Data-Science-Blog/commits/18fc7cdb93a85336d98b3273284696b1ae736d98"}]}
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