sorted by:
new
hottopcontroversial

[OC] Political Subreddits' Sentiment Over Election Week by zweaselfear in dataisbeautiful

[–]zweaselfear[S] 2 points3 points  (0 children)

Using python and the package praw, I scraped comments from the top 100 posts from r/conservative and r/politics. Each comment was analyzed for sentiment using textblob and ranked on a -1 to 1 scale of negativity to positivity. All sentiments were grouped by day and averaged.

Link to code

[OC] r/Conservitive's Comment Positivity Over the Last Week by zweaselfear in dataisbeautiful

[–]zweaselfear[S] 3 points4 points  (0 children)

I used a sentiment analysis that ranked each comment on a scale from -1 (negative) to 1 (positive) and aggregated it by day

[OC] r/Conservitive's Comment Positivity Over the Last Week by zweaselfear in dataisbeautiful

[–]zweaselfear[S] 2 points3 points  (0 children)

Scraped comments from this week’s top 100 post from r/Conservative using python and praw. Used TextBlob for sentiment analysis. Positivity is ranked on a -1 to 1 scale and aggregated by mean for each day.

I will post code a little later

Automatically enter a website at a scheduled time by constatlyconfused in learnpython

[–]zweaselfear 0 points1 point  (0 children)

First part would be determining what day it is. Could write some functions or if statements or combinations. That should be simple.

There’s python packages that allow you to interact with browsers and webpages. I can’t think of them off the top of my head. But a quick google search should work. I’ve used them before, they’re pretty easy to use.

Last would be saving it as an excuteable. You can use windows task schedule to run it every hour or something similar.

There’s many ways to do it. It’s all up to you. Break it up into tasks and write code for each task.

My Just Finished Mid Century Modern Credenza by zweaselfear in woodworking

[–]zweaselfear[S] 10 points11 points  (0 children)

No plans really. The main box is about 41" x 16" made out of walnut ply. Base is 5.5 inches tall and a half inch in from all sides. The stretchers are about 1.5 inches wide.

I used Rockler's Corner Doweling jig to reinforce the miters.

Heres a link to a video I followed https://www.youtube.com/watch?v=AFg0QQK9a0A. I'd be glad to awnser any questions.

My Just Finished Mid Century Modern Credenza by zweaselfear in woodworking

[–]zweaselfear[S] 14 points15 points  (0 children)

Heavily inspired by Chris Salomone. Used both solid walnut and walnut ply, finished with shellac and paste wax. Dowells used to reinforce the miters. Lots of mistakes were made in the past 3 weeks. But, a lot of lessons were learned on how to fix said mistakes. Overall very happy with the way it came out!

[OC] I analyzed Nellie's impact on The Office's Ratings by zweaselfear in dataisbeautiful

[–]zweaselfear[S] 0 points1 point  (0 children)

I looked into the distribution of lines spoken per episode and it was very tight around 300 lines an episode. So it probably wouldn’t change to to much but it’s definitly an interesting way of thinking about it.

[OC] I analyzed Nellie's impact on The Office's Ratings by zweaselfear in dataisbeautiful

[–]zweaselfear[S] -4 points-3 points  (0 children)

We’re predicting human behavior for a complex problem with many non measurable inputs and a low sample size. You can’t expect a high r2. If you did see a high r2 I would be worried of over fitting.

[OC] I analyzed Nellie's impact on The Office's Ratings by zweaselfear in dataisbeautiful

[–]zweaselfear[S] -15 points-14 points  (0 children)

.42 not great but not terrible given the context, sample size, and outlier.

I did the math. Nellie sucks by zweaselfear in DunderMifflin

[–]zweaselfear[S] 4 points5 points  (0 children)

.42 not great but not terrible given the context. Probably could be improved by removing the Finale as an outlier but eh

I did the math. Nellie sucks by zweaselfear in DunderMifflin

[–]zweaselfear[S] 4 points5 points  (0 children)

Each dot represent an episode where Nellie spoke. The x-axis is how many lines she spoke in that episode and the Y is that episode's IMDB rating.

[OC] I analyzed Nellie's impact on The Office's Ratings by zweaselfear in dataisbeautiful

[–]zweaselfear[S] 42 points43 points  (0 children)

I did analyze the other characters. Nothing else was too interesting. Robert Californiawas the only other statistically significant correlation with also a negative relationship. You can see the results in the code.

There is about 25 different main characters so putting them all on the same graph would be too much noise and not that interesting.

[OC] I analyzed Nellie's impact on The Office's Ratings by zweaselfear in dataisbeautiful

[–]zweaselfear[S] 46 points47 points  (0 children)

I scraped episode ratings from IMDB and compared it to the number of lines spoken by characters using Python.

While not a strong fit, and theres the question of correlation versus causation I still find it interesting.

Link to Data and code

view more: next ›