]> code.communitydata.science - cdsc_reddit.git/blob - top_comment_phrases.py
Add code for running tf-idf at the weekly level.
[cdsc_reddit.git] / top_comment_phrases.py
1 from pyspark.sql import functions as f
2 from pyspark.sql import Window
3 from pyspark.sql import SparkSession
4 import numpy as np
5
6 spark = SparkSession.builder.getOrCreate()
7 df = spark.read.text("/gscratch/comdata/users/nathante/reddit_comment_ngrams_10p_sample/")
8
9 df = df.withColumnRenamed("value","phrase")
10
11 # count phrase occurrances
12 phrases = df.groupby('phrase').count()
13 phrases = phrases.withColumnRenamed('count','phraseCount')
14 phrases = phrases.filter(phrases.phraseCount > 10)
15
16
17 # count overall
18 N = phrases.select(f.sum(phrases.phraseCount).alias("phraseCount")).collect()[0].phraseCount
19
20 print(f'analyzing PMI on a sample of {N} phrases') 
21 logN = np.log(N)
22 phrases = phrases.withColumn("phraseLogProb", f.log(f.col("phraseCount")) - logN)
23
24 # count term occurrances
25 phrases = phrases.withColumn('terms',f.split(f.col('phrase'),' '))
26 terms = phrases.select(['phrase','phraseCount','phraseLogProb',f.explode(phrases.terms).alias('term')])
27
28 win = Window.partitionBy('term')
29 terms = terms.withColumn('termCount',f.sum('phraseCount').over(win))
30 terms = terms.withColumnRenamed('count','termCount')
31 terms = terms.withColumn('termLogProb',f.log(f.col('termCount')) - logN)
32
33 terms = terms.groupBy(terms.phrase, terms.phraseLogProb, terms.phraseCount).sum('termLogProb')
34 terms = terms.withColumnRenamed('sum(termLogProb)','termsLogProb')
35 terms = terms.withColumn("phrasePWMI", f.col('phraseLogProb') - f.col('termsLogProb'))
36
37 # join phrases to term counts
38
39
40 df = terms.select(['phrase','phraseCount','phraseLogProb','phrasePWMI'])
41
42 df = df.sort(['phrasePWMI'],descending=True)
43 df = df.sortWithinPartitions(['phrasePWMI'],descending=True)
44 df.write.parquet("/gscratch/comdata/users/nathante/reddit_comment_ngrams_pwmi.parquet/",mode='overwrite',compression='snappy')
45
46 df = spark.read.parquet("/gscratch/comdata/users/nathante/reddit_comment_ngrams_pwmi.parquet/")
47
48 df.write.csv("/gscratch/comdata/users/nathante/reddit_comment_ngrams_pwmi.csv/",mode='overwrite',compression='none')
49
50 df = spark.read.parquet("/gscratch/comdata/users/nathante/reddit_comment_ngrams_pwmi.parquet")
51 df = df.select('phrase','phraseCount','phraseLogProb','phrasePWMI')
52
53 # 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.
54 #
55 df = df.filter(f.col('phraseCount') > 3500).filter(f.col("phrasePWMI")>3)
56 df = df.toPandas()
57 df.to_feather("/gscratch/comdata/users/nathante/reddit_multiword_expressions.feather")
58 df.to_csv("/gscratch/comdata/users/nathante/reddit_multiword_expressions.csv")

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