Hello, I am in a big data class. My group is interested in doing our final project based on mental health\/depression. Although, ‘big data’ will not be feasible because we are running these on our local PCs, we still need to perform big data analysis with map\/reduce programs. We have been using PySpark for all of our assignments and they have been very complex assignments. Such as a friend recommendation program where you rank 10 recommendations from a very large text file that was in the format of <unique_id><list of friends>. This assignment, we had to perform multiple for loops\/if statements inside of our PySpark map\/reduce program which made it quite complex.<\/p>\n
Now, we have found this dataset https:\/\/www.kaggle.com\/datasets\/anthonytherrien\/depression-dataset<\/a> that we want to use, but we don’t believe we can “wow” the professor with complex enough functions to make conclusions. Is this maybe not a good type of dataset for big data applications? We originally thought to make a depression “score” based on the given features and justify those based on how frequent\/similar each unique person is. <\/p>\n Any ideas or datasets that you know about that would be just complex enough would be a big help. Thanks!<\/p>\n<\/div>\n submitted by \/u\/idkwhatsgoingon4582 <\/a>
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