memedict - KnowYourMeme definitions web scraper: https://www.reddit.com/r/Python/comments/9b6s98/memedict_knowyourmeme_definitions_web_scraper/
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r/Python - memedict - KnowYourMeme definitions web scraper
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Iterating over a df based a unique values of a column in pandas.: https://www.reddit.com/r/Python/comments/9b7re8/iterating_over_a_df_based_a_unique_values_of_a/
reddit
r/Python - Iterating over a df based a unique values of a column in pandas.
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running mongo queries against data in memory: https://stackoverflow.com/questions/48509773/running-mongo-queries-against-data-in-memory
Stack Overflow
running mongo queries against data in memory
I have a mongodb collection against which I need to run many count operations (each with a different query) every hour. When I first set this up, the collection was small, and these count operation...
If you were going to make a timeline, a historical timeline, which library would you use?: https://www.reddit.com/r/Python/comments/9b8cma/if_you_were_going_to_make_a_timeline_a_historical/
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r/Python - If you were going to make a timeline, a historical timeline, which library would you use?
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ActivityWatch (open-source time tracker) Development Update August 2018: https://www.reddit.com/r/Python/comments/9b98h8/activitywatch_opensource_time_tracker_development/
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r/Python - ActivityWatch (open-source time tracker) Development Update August 2018
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Checkout new playground and cheatsheet for learning Python: https://www.reddit.com/r/Python/comments/9bafwi/checkout_new_playground_and_cheatsheet_for/
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r/Python - Checkout new playground and cheatsheet for learning Python
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Splitting coef into arrays applicable for multi class: https://stackoverflow.com/questions/52042843/splitting-coef-into-arrays-applicable-for-multi-class
Stack Overflow
Splitting coef into arrays applicable for multi class
I use this function to plot the best and worst features (coef) for each label.
def plot_coefficients(classifier, feature_names, top_features=20):
coef = classifier.coef_.ravel()
for i i...
def plot_coefficients(classifier, feature_names, top_features=20):
coef = classifier.coef_.ravel()
for i i...