Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Mini-Project 3: Text Mining #66

Open
wants to merge 6 commits into
base: master
Choose a base branch
from
Open

Conversation

YehEmily
Copy link

Here's my work for MP3: a doge-style poem generator!

(For your reference: http://knowyourmeme.com/memes/doge)

(Also, I'm so sorry this is late; I missed all of Mini-Project 3 because I was in the hospital, and I decided to finish it after Mini-Project 4, so that I wouldn't get any more behind... Thank you for your patience and understanding, and I'm sorry for any inconveniences this might have caused!)


This change is Review on Reviewable

(Sorry this is late; I missed all of Mini-Project 3 because I was in the hospital, and I decided to finish it after Mini-Project 4, so that I wouldn't get any more behind... Thank you for your patience and understanding, and again, I'm sorry this is super late!)
@jenwei
Copy link

jenwei commented Mar 21, 2016

Reviewed 3 of 3 files at r1.
Review status: all files reviewed at latest revision, 4 unresolved discussions.


doge_poetry.py, line 29 [r1] (raw file):
This looks fine, but this all seems quite specific to project gutenberg, so if you ever revisit this, you could potentially take all the code here and create a clean_gutenberg_text function, and once the text is cleaned up, take that input and use get_word_list.


doge_poetry.py, line 66 [r1] (raw file):
Nice use of a negative index here to search from the back!


doge_poetry.py, line 84 [r1] (raw file):
Great notes here about why you chose the randint ranges you did.


MP3_Reflection.pdf, line 0 [r1] (raw file):
Awesome writeup. Seems like you put a lot of thought into it, had a lot of fun, and learned quite a bit too. Those poems were quite entertaining.

Nice that you tied in what you learned from the Word Frequency toolbox and applied it here.

The stanza issue is definitely tricky, but in your situation, hardcoding a skeleton seems like a fine idea.


Comments from the review on Reviewable.io

I kept forgetting to include comments that might help someone understand my code... here's the final version!
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
None yet
Projects
None yet
Development

Successfully merging this pull request may close these issues.

2 participants