summaries :>

• 

  original data and data after a round of cleaning and moved to dataframe

• 

  web scraping

Inspiration

Sometimes, hypothetically, I run too late for class to read through SparkNotes. So I decided to summarize the summaries.

What it does

Data analysis and cleaning of text retrieved through web scraping of spark notes. Determines words of significance to rank sentences to prepare for summarization.

How I built it

I used jupyter notebooks / Python

Challenges I ran into

I tried to make a chrome extension to auto replace the text with the results of my code - now it just turns sparknotes blue :>. I had issues with the Chrome development security rules about integrating JavaScript and Python isn't supported by Chrome Extensions so it was a bit of a time suck. Using SpaCy with Pycharm Sleep :0

Accomplishments that I'm proud of

Everything really

What I learned

lotsss pinky promise but deadline is rn

What's next for summaries :>

Finish the chrome extension, calculate weights for sentences, decide on a threshold, final summary

Built With

• anaconda
• pandas
• python
• spacy