changes for archiving.

[cdsc_reddit.git] / similarities / top_subreddits_by_comments.py

diff --git a/similarities/top_subreddits_by_comments.py b/similarities/top_subreddits_by_comments.py
index ff9293c209f1f86ecdd0c34a4f282c2cae8eb08c..74ffb8d715e4f2fc6259e95382452fa631b3ec7c 100644 (file)
--- a/similarities/top_subreddits_by_comments.py
+++ b/similarities/top_subreddits_by_comments.py
@@ -1,23 +1,27 @@
 from pyspark.sql import functions as f
 from pyspark.sql import SparkSession
 from pyspark.sql import Window
+from datetime import datetime
+from pathlib import Path
 
 spark = SparkSession.builder.getOrCreate()
 conf = spark.sparkContext.getConf()
 
-submissions = spark.read.parquet("/gscratch/comdata/output/reddit_submissions_by_subreddit.parquet")
+submissions = spark.read.parquet("../../data/reddit_submissions_by_subreddit.parquet")
 
-prop_nsfw = submissions.select(['subreddit','over_18']).groupby('subreddit').agg(f.mean(f.col('over_18').astype('double')).alias('prop_nsfw'))
+submissions = submissions.filter(f.col("CreatedAt") <= datetime(2020,4,13))
 
-df = spark.read.parquet("/gscratch/comdata/output/reddit_comments_by_subreddit.parquet")
+prop_nsfw = submissions.select(['subreddit','over_18']).groupby('subreddit').agg(f.mean(f.col('over_18').astype('double')).alias('prop_nsfw'))
 
+df = spark.read.parquet("../../data/reddit_comments_by_subreddit.parquet")
+df = df.filter(f.col("CreatedAt") <= datetime(2020,4,13))
 # remove /u/ pages
 df = df.filter(~df.subreddit.like("u_%"))
 
 df = df.groupBy('subreddit').agg(f.count('id').alias("n_comments"))
 
 df = df.join(prop_nsfw,on='subreddit')
-#df = df.filter(df.prop_nsfw < 0.5)
+df = df.filter(df.prop_nsfw < 0.5)
 
 win = Window.orderBy(f.col('n_comments').desc())
 df = df.withColumn('comments_rank', f.rank().over(win))
@@ -26,4 +30,6 @@ df = df.toPandas()
 
 df = df.sort_values("n_comments")
 
-df.to_csv('/gscratch/comdata/output/reddit_similarity/subreddits_by_num_comments_nsfw.csv', index=False)
+outpath = Path("../../data/reddit_similarity/subreddits_by_num_comments_nonsfw.csv")
+outpath.parent.mkdir(exist_ok=True, parents=True)
+df.to_csv(str(outpath), index=False)