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@eigenrobot

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eigenrobot

@eigenrobot

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eigenrobot.substack.com
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    1. Nick HK‏ @nickchk 25 Feb 2020

      I think I finally have to bite the bullet and learn stats in Python for my causal inference book. I know some Python but not for stats. Can I basically do everything with pandas, statsmodels, and matplotlib? What are your favorite materials for learning pandas and matplot?

      11 replies 11 retweets 75 likes
      Show this thread
    2. Nick HK‏ @nickchk 25 Feb 2020

      By "everything" I mean I need to do data manipulation like I would do in dplyr, standard causal-inference estimators mostly with regression (assumedly I might have to branch out in packages for stuff like specialized RDD or matching estimators?), and graphing

      5 replies 0 retweets 3 likes
      Show this thread
    3. Nick HK‏ @nickchk 25 Feb 2020

      If there's a rosetta stone out there showing how to do the same stuff in both pandas and dplyr/Stata that would be amazing

      5 replies 0 retweets 8 likes
      Show this thread
    4. eigenrobot‏ @eigenrobot 25 Feb 2020
      Replying to @nickchk

      yeah pandas for data cleaning probably sklearn for modeling at least in an ML paradigm there are other modules for trad stats but I'm less familiar with those

      1 reply 0 retweets 1 like
    5. eigenrobot‏ @eigenrobot 25 Feb 2020
      Replying to @eigenrobot @nickchk

      Oh for visuals seaborn is lovely

      1 reply 0 retweets 1 like
    6. Nick HK‏ @nickchk 25 Feb 2020
      Replying to @eigenrobot

      Oh right seaborn - for undergrads would it make sense to teach the seaborn interface rather than the mpl one (seaborn is just mpl with a different interface right?)

      1 reply 0 retweets 2 likes
      eigenrobot‏ @eigenrobot 25 Feb 2020
      Replying to @nickchk

      Yeah I think so. Much cleaner and easier to get what you want for 90% of use cases, and documentation is very good

      12:20 PM - 25 Feb 2020
      • 2 Likes
      • JB Duck-Mayr Nick HK
      1 reply 0 retweets 2 likes
        1. New conversation
        2. Nick HK‏ @nickchk 25 Feb 2020
          Replying to @eigenrobot

          Yeah that sounds perfect. Thanks!

          1 reply 0 retweets 1 like
        3. Ian Preston‏ @iPrestonBC 25 Feb 2020
          Replying to @nickchk @eigenrobot

          Seaborn is particularly handy for stats based visualization, and you can always access the underlying MPL layer if you need to (although unless you're making something publication ready you shouldn't need it)

          1 reply 0 retweets 2 likes
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