diff --git a/convert-to-parquet/convert-to-parquet.py b/convert-to-parquet/convert-to-parquet.py
index 6fea930b5d231604580041ac755481c2350c6b99..2a8b70c693a9594a428fbc53724239052caf7ff7 100755
--- a/convert-to-parquet/convert-to-parquet.py
+++ b/convert-to-parquet/convert-to-parquet.py
@@ -1,20 +1,16 @@
 from urllib.parse import unquote
 import os
 import re
-import dask.bag as db
-import dask.dataframe as dd
 import argparse
+import pandas as pd
+import gzip
 from pathlib import PurePath
 
 desc = """
 Converts GPFS policy run logs to parquet files for easier aggregation and analysis.\n
 Works with data from /data/user, /data/user/home, /data/project, and /scratch
 The data are parsed and the directory beneath any of those listed above is set as the top-level
-directory ('tld'). The tld is then set as the index for the parquet file to improve aggregation speed
-
-If the full log is split into multiple parts, the full dataset will need to be repartitioned after all of
-the parts are converted to parquet to make sure all entries for each tld are in the same partition. This
-can be done with a separate script
+directory ('tld').
 """
 
 def parse_args():
@@ -108,11 +104,14 @@ def main():
         
     os.makedirs(outdir,exist_ok=True)
     
-    bag = db.read_text(file).map(parse_line)
-    ddf  = bag.to_dataframe(meta=schema).set_index('tld')
+    #bag = db.read_text(file).map(parse_line)
+    with gzip.open(file,'r') as f:
+        dicts = [parse_line(l) for l in f]
+    df  = pd.DataFrame.from_dict(dicts).sort_values('tld')
+    df = df.astype(schema)
 
     outname = file.with_suffix('.parquet').name
-    ddf.to_parquet(outdir.joinpath(outname))
+    df.to_parquet(outdir.joinpath(outname),engine = 'pyarrow')
 
 if __name__ == '__main__':
     main()
\ No newline at end of file