X-Git-Url: https://code.communitydata.science/cdsc_reddit.git/blobdiff_plain/529b7f051133df6cccd3fbf360f8b196bf5b5996..ed0e1a82357219ea70e6dfc3396d074af157086f:/top_comment_phrases.py diff --git a/top_comment_phrases.py b/top_comment_phrases.py index 707ceaa..031cba5 100644 --- a/top_comment_phrases.py +++ b/top_comment_phrases.py @@ -8,18 +8,19 @@ df = spark.read.text("/gscratch/comdata/users/nathante/reddit_comment_ngrams_10p df = df.withColumnRenamed("value","phrase") +# count phrase occurrances +phrases = df.groupby('phrase').count() +phrases = phrases.withColumnRenamed('count','phraseCount') +phrases = phrases.filter(phrases.phraseCount > 10) + # count overall -N = df.count() +N = phrases.select(f.sum(phrases.phraseCount).alias("phraseCount")).collect()[0].phraseCount + print(f'analyzing PMI on a sample of {N} phrases') logN = np.log(N) - -# count phrase occurrances -phrases = df.groupby('phrase').count() -phrases = phrases.withColumnRenamed('count','phraseCount') phrases = phrases.withColumn("phraseLogProb", f.log(f.col("phraseCount")) - logN) - # count term occurrances phrases = phrases.withColumn('terms',f.split(f.col('phrase'),' ')) terms = phrases.select(['phrase','phraseCount','phraseLogProb',f.explode(phrases.terms).alias('term')]) @@ -38,8 +39,20 @@ terms = terms.withColumn("phrasePWMI", f.col('phraseLogProb') - f.col('termsLogP df = terms.select(['phrase','phraseCount','phraseLogProb','phrasePWMI']) -df = df.repartition('phrasePWMI') df = df.sort(['phrasePWMI'],descending=True) df = df.sortWithinPartitions(['phrasePWMI'],descending=True) df.write.parquet("/gscratch/comdata/users/nathante/reddit_comment_ngrams_pwmi.parquet/",mode='overwrite',compression='snappy') + +df = spark.read.parquet("/gscratch/comdata/users/nathante/reddit_comment_ngrams_pwmi.parquet/") + df.write.csv("/gscratch/comdata/users/nathante/reddit_comment_ngrams_pwmi.csv/",mode='overwrite',compression='none') + +df = spark.read.parquet("/gscratch/comdata/users/nathante/reddit_comment_ngrams_pwmi.parquet") +df = df.select('phrase','phraseCount','phraseLogProb','phrasePWMI') + +# choosing phrases occurring at least 3500 times in the 10% sample (35000 times) and then with a PWMI of at least 3 yeids about 65000 expressions. +# +df = df.filter(f.col('phraseCount') > 3500).filter(f.col("phrasePWMI")>3) +df = df.toPandas() +df.to_feather("/gscratch/comdata/users/nathante/reddit_multiword_expressions.feather") +df.to_csv("/gscratch/comdata/users/nathante/reddit_multiword_expressions.csv")