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dataset-creation-utilities/create-year-lists.py

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+import pandas as pd
+import numpy as np
+from tqdm import tqdm
+
+df = pd.read_feather("hupd_metadata_2022-02-22.feather", columns=['application_number', 'filing_date'])
+assert df['filing_date'].dt.year.isnull().sum() == 2
+df['year'] = df['filing_date'].dt.year.fillna(2018.0).astype(int)
+years = df['year'].value_counts()
+print(years)
+for year in tqdm(years.index):
+    df_year_numbers = df['application_number'][df['year'] == year]
+    df_year_numbers.to_frame().to_csv(f'lists/{year}.txt', sep=' ', index=False, header=False)
+    print(f'saved {year}')

dataset-creation-utilities/move-files.sh

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+# Move
+mkdir years
+for year in 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018  # 2004 
+do
+	mkdir years/${year}
+	cat lists/$year.txt | xargs -i mv distilled/{}.json years/${year}
+done
+
+# Create tars
+tar cfz 2004.tar.gz 2004
+tar cfz 2005.tar.gz 2005
+tar cfz 2006.tar.gz 2006
+tar cfz 2007.tar.gz 2007
+tar cfz 2008.tar.gz 2008
+tar cfz 2009.tar.gz 2009
+tar cfz 2010.tar.gz 2010
+tar cfz 2011.tar.gz 2011
+tar cfz 2012.tar.gz 2012
+tar cfz 2013.tar.gz 2013
+tar cfz 2014.tar.gz 2014
+tar cfz 2015.tar.gz 2015
+tar cfz 2016.tar.gz 2016
+tar cfz 2017.tar.gz 2017
+tar cfz 2018.tar.gz 2018