get_noaa_taxa.py script check

scripts/get_noaa_taxa.py

@@ -0,0 +1,40 @@
+
+import csv
+import os
+import pandas as pd
+import glob
+import sys
+import numpy as np
+import re
+
+data_path = 'notebooks/cleaned_data/odp_all_paleontology/range_tables/'
+full_path = os.path.join(os.path.split(os.getcwd())[0], data_path)
+raw_csvs = glob.glob(f"{full_path}/**/*.txt", recursive=True)
+
+non_taxa_fields = ['Data', 'Age', 'From', '(oldest)', 'To', '(youngest)', 'Zone', '(bottom)', '(top)',
+                'Leg', 'Site', 'H', 'Cor', 'T', 'Sc', 'Top(cm)', 'Depth', '(mbsf)',
+                'Scientist', 'Fossil', 'Group', 'Group', 'Abundance', 'Group', 'Preservation',
+                'Comment']
+
+
+taxa_list = []
+taxon_group_list = []
+for file in raw_csvs:
+    df = pd.read_csv(file, delimiter="\t")
+    col_headers = list(df.columns.values)
+    taxon_group = (os.path.splitext(os.path.split(file)[1])[0]).lower()
+    for col in col_headers:
+        column_split = col.split()
+        non_taxa_bool = any(column in column_split for column in non_taxa_fields)
+        if non_taxa_bool:
+            next
+        elif col in taxa_list:
+            next
+        else:
+            taxa_list.append(col)
+            taxon_group_list.append(taxon_group)
+data = list(zip(taxa_list, taxon_group_list))
+taxa_df = pd.DataFrame(data, columns=['verbatim_name', 'taxon_group'])
+taxa_df['genera'] = taxa_df['verbatim_name'].str.extract('^([A-Z][a-z]+) [a-z]+')
+taxa_df.head()
+taxa_df.to_csv('noaa_taxa.csv', index=False)