fix columns

affinity-data-combined.parquet

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:9fe95d2ceff77b1785c3280f6f8a8dd3ca0c442035049061d1a69ae0c36e0330
-size 909234669
+oid sha256:84ad94bcd9f58af607561ddab91522fd892488bec5cbc337bbd33f11d2127fa4
+size 911748102

combine_data.py

@@ -3,7 +3,7 @@ import numpy as np
 
 def combine_csv_files(csv_file_list):
     # Read and combine all CSV files into a single dataframe
-    combined_df = pd.concat([pd.read_csv(file) for file in csv_file_list], ignore_index=True)
+    combined_df = pd.concat([pd.read_parquet(file) for file in csv_file_list], ignore_index=True)
     
     # Remove duplicate rows
     combined_df = combined_df.drop_duplicates(subset=['seq', 'smiles_can', 'neg_log10_affinity_M'])
@@ -30,6 +30,7 @@ def combine_csv_files(csv_file_list):
     combined_df['affinity_std'] = affinity_std
     combined_df['affinity_norm'] = (combined_df['neg_log10_affinity_M'] - affinity_mean) / affinity_std
     
+    combined_df["affinity_uM"] = combined_df["neg_log10_affinity_M"].apply(lambda x: (10**(-x))*1e6)
     return combined_df
 
 combined_df = combine_csv_files(['glaser.parquet', 'davis-filtered.parquet', 'pdbbind-2020-combined.parquet', 'bindingdb-kd-filtered.parquet', 'bindingdb-ki.parquet', 'bindingdb-ic50.parquet'])