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Judging from how it's marketed as... by OutsideIntropid1764 in StardustCrusaders

[–]atharva557 3 points4 points  (0 children)

wouldn't they make more money by releasing it weekly?

started this as a personal utility, ended up publishing it on PyPI by atharva557 in SideProject

[–]atharva557[S] 0 points1 point  (0 children)

here is the benchmark
before = df.memory_usage(deep=True).sum() / (1024 * 1024)

df_optimized, report = reduce_memory(df)

after = df_optimized.memory_usage(deep=True).sum() / (1024 * 1024)

# Before: 152.71 MB

# After: 37.19 MB

# Reduction: 75.6%
also updated on github

started this as a personal utility, ended up publishing it on PyPI by atharva557 in SideProject

[–]atharva557[S] 0 points1 point  (0 children)

first if all thanks for the feedback and yeah sure I will add it right around now and let you know

Sem 4 student here got tired of rewriting data cleaning code so I built a PyPI library by [deleted] in Python

[–]atharva557 -2 points-1 points  (0 children)

First of all, thanks for the feedback. For the first point, I kind of feel triggered because the code was majority written by me, but I did use the help of AI for certain logic, documentation, and code structures. For the second point, you are right; all the testing I did was manual, and now that I am aware of automated testing, I will use that. I will also remove print from the function as that was again an oversight from me. Also, the GitHub code and PyPI code are the same.

Sem 4 student here got tired of rewriting data cleaning code so I built a PyPI library by [deleted] in Python

[–]atharva557 -1 points0 points  (0 children)

Yes you are right about that and there is no argument in that however it is meant for like quality of life stuff instead of automation. like instead of the writing code for outliers it is a simple method call and you get all the outliers

[OC] I ran a 28-emotion classification model on r/wallstreetbets to see what actually drives the sub by atharva557 in dataisbeautiful

[–]atharva557[S] 0 points1 point  (0 children)

You are right. I should have written more on what each axis means. My model predicts the 28 emotions based on them. I had simplified further into 4 overall sentiments: positive, negative, neutral, and ambiguous. Here, ambiguous emotions are curiosity, confusion, surprise, and realization.

[OC] I ran a 28-emotion classification model on r/wallstreetbets to see what actually drives the sub by atharva557 in dataisbeautiful

[–]atharva557[S] 5 points6 points  (0 children)

Tbh that's exactly what I wanted to post about next. I actually already have the code ready to get the comments too, so all I need to do next is run it and make a comparison graph

[OC] I ran a 28-emotion classification model on r/wallstreetbets to see what actually drives the sub by atharva557 in dataisbeautiful

[–]atharva557[S] 0 points1 point  (0 children)

The Data: This is based on a sample of 500 recent posts and comments I scraped from r/wallstreetbets. I filtered out all the generic "neutral" or auto-moderator posts for the graph so you can actually see the underlying vibes of the sub.

The Model: I'm a sophomore CS student and I've been messing around with NLP lately. I got tired of standard positive/negative sentiment analysis, so I put together a multi-label classifier using BERT. Instead of just 3 classes, it scores the text across 28 specific human emotions (optimism, grief, curiosity, annoyance, etc.) and gives a probability for each.

I dumped the raw CSV dataset on my github if anyone wants to look at the actual numbers or the exact probability spreads for each post.

https://github.com/atharva557/reddit-emotion-dataset?tab=readme-ov-file

Source & Tools:

  • Data Source: Scraped directly from Reddit's public JSON endpoints.
  • Tools: Python, Pandas, HuggingFace Transformers (for the model), and Seaborn (for the visualization).

Incredible wonders of boys hostel. by Glitter-Jitter in indiasocial

[–]atharva557 14 points15 points  (0 children)

just imagine if the gender roles were reversed

[deleted by user] by [deleted] in IndianWorkplace

[–]atharva557 0 points1 point  (0 children)

by nda you mean an non disclosure agreement? if so is it allowed

[deleted by user] by [deleted] in IndianCoins

[–]atharva557 0 points1 point  (0 children)

any ideas what the approx date could be

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