add code for pulling activity time series from parquet.

timeseries/cluster_timeseries.py

@@ -0,0 +1,37 @@
+import pandas as pd
+import numpy as np
+from pyspark.sql import functions as f
+from pyspark.sql import SparkSession
+from choose_clusters import load_clusters, load_densities
+import fire
+from pathlib import Path
+
+def main(term_clusters_path="/gscratch/comdata/output/reddit_clustering/comment_terms_10000.feather",
+         author_clusters_path="/gscratch/comdata/output/reddit_clustering/comment_authors_10000.feather",
+         term_densities_path="/gscratch/comdata/output/reddit_density/comment_terms_10000.feather",
+         author_densities_path="/gscratch/comdata/output/reddit_density/comment_authors_10000.feather",
+         output="data/subreddit_timeseries.parquet"):
+
+
+    clusters = load_clusters(term_clusters_path, author_clusters_path)
+    densities = load_densities(term_densities_path, author_densities_path)
+    
+    spark = SparkSession.builder.getOrCreate()
+    
+    df = spark.read.parquet("/gscratch/comdata/output/reddit_comments_by_subreddit.parquet")
+    
+    df = df.withColumn('week', f.date_trunc('week', f.col("CreatedAt")))
+    
+    # time of unique authors by series by week
+    ts = df.select(['subreddit','week','author']).distinct().groupby(['subreddit','week']).count()
+    
+    ts = ts.repartition('subreddit')
+    spk_clusters = spark.createDataFrame(clusters)
+    
+    ts = ts.join(spk_clusters, on='subreddit', how='inner')
+    spk_densities = spark.createDataFrame(densities)
+    ts = ts.join(spk_densities, on='subreddit', how='inner')
+    ts.write.parquet(output, mode='overwrite')
+
+if __name__ == "__main__":
+    fire.Fire(main)