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github.com/PhantomInsights/subreddit-analyzer
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Functions
22 in github.com/PhantomInsights/subreddit-analyzer
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Functions
22
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Types & classes
0
↓ 1 callers
Function
download_submissions
Keeps downloading submissions using recursion, it downloads them 500 at a time. Parameters ---------- subreddit : str The desired
scripts/subreddit_submissions.py:39
↓ 1 callers
Function
download_submissions
Keeps downloading submissions using recursion, it downloads them 500 at a time. Parameters ---------- subreddit : str The desired
scripts/subreddit_submissions_alt.py:46
↓ 1 callers
Function
get_entities
Get the entities and save them to .csv Parameters ---------- nlp : spacy.nlp A nlp object. corpus : list All the com
scripts/step2.py:69
↓ 1 callers
Function
get_tokens
Get the tokens and save them to .csv Parameters ---------- nlp : spacy.nlp A nlp object. corpus : list All the comme
scripts/step2.py:39
↓ 1 callers
Function
init
Iterates over all the subreddits and creates their csv files.
scripts/subreddit_comments_alt.py:28
↓ 1 callers
Function
init
Iterates over all the subreddits and creates their csv files.
scripts/subreddit_submissions.py:21
↓ 1 callers
Function
init
Iterates over all the subreddits and creates their csv files.
scripts/subreddit_submissions_alt.py:28
↓ 1 callers
Function
init
()
scripts/subreddit_comments.py:21
↓ 1 callers
Function
load_comments
Keeps downloading comments using recursion, it saves them 500 at a time. Parameters ---------- subreddit : str The desired subred
scripts/subreddit_comments_alt.py:43
↓ 1 callers
Function
load_comments
(subreddit, latest_timestamp=None)
scripts/subreddit_comments.py:38
↓ 1 callers
Function
main
Loads the model and processes it. The model used can be installed by running this command on your CMD/Terminal: python -m spacy download es_
scripts/step2.py:12
Function
generate_most_common_entities_word_cloud
Generates a word cloud with the most used entities. Parameters ---------- df : pandas.DataFrame The entities DataFrame.
scripts/step3.py:518
Function
generate_most_common_words_word_cloud
Generates a word cloud with the most used tokens. Parameters ---------- df : pandas.DataFrame The tokens DataFrame.
scripts/step3.py:462
Function
get_insights
Prints several interesting insights. Parameters ---------- df : pandas.DataFrame The submissions DataFrame. df2 : pandas.Dat
scripts/step3.py:83
Function
get_most_common_commenters
Prints the 20 most frequent commenters. Parameters ---------- df : pandas.DataFrame The comments DataFrame.
scripts/step3.py:66
Function
get_most_common_domains
Prints the 20 most frequent domains from submissions. Parameters ---------- df : pandas.DataFrame The submissions DataFrame.
scripts/step3.py:35
Function
get_most_common_submitters
Prints the 20 most frequent submitters. Parameters ---------- df : pandas.DataFrame The submissions DataFrame.
scripts/step3.py:49
Function
plot_comments_by_user
Plots a pie chart with the distribution of comments by user groups. Parameters ---------- df : pandas.DataFrame The comments
scripts/step3.py:390
Function
plot_submissions_and_comments_by_hour
Creates a horizontal bar plot with the percentage of submissions and comments by hour of the day. Parameters ---------- df : pandas.D
scripts/step3.py:203
Function
plot_submissions_and_comments_by_weekday
Creates a vertical bar plot with the percentage of submissions and comments by weekday. Parameters ---------- df : pandas.DataFrame
scripts/step3.py:127
Function
plot_submissions_by_user
Plots a pie chart with the distribution of submissions by user groups. Parameters ---------- df : pandas.DataFrame The submis
scripts/step3.py:324
Function
plot_yearly_submissions_and_comments
Creates 2 line subplots with the counts of submissions and comments by day. Parameters ---------- df : pandas.DataFrame The s
scripts/step3.py:286