inconsistent env_broad_scale #77

sample_annotator/non_edge.py

@@ -0,0 +1,31 @@
+import sqlite3
+import pandas as pd
+import numpy as np
+import re
+
+def to_csv():
+    db = sqlite3.connect('biosample.db')
+    cursor = db.cursor()
+    cursor.execute("SELECT name FROM sqlite_master WHERE type='table';")
+    tables = cursor.fetchall()
+    for table_name in tables:
+        table_name = table_name[0]
+        table = pd.read_sql_query("SELECT * from %s" % table_name, db)
+        table.to_csv(table_name + '.csv', index_label='index')
+    cursor.close()
+    db.close()
+to_csv()
+
+#tried dumping env_mapping into biosample instead
+map = pd.read_csv('new_env_mapping.csv')
+main = pd.read_csv('harmonized_wide_sel_envs.csv')
+
+main['env_broad_scale'] = main['env_broad_scale'].str.lower()
+main['env_broad_scale'] = main['env_broad_scale'].str.replace('envo:','', regex=True)
+merge_table = main.merge(map, left_on = 'env_broad_scale', right_on = 'label', how='left')
+merge_table['broad_scale_fixed'] = merge_table['env_broad_scale'].astype(str) + ' ' + '['+merge_table['term_id'].astype(str) +']'
+
+#still need to change the 'nan[nan]' string values to NaN (np.nan) values 
+#not sure how
+merge_table['broad_scale_fixed'] = merge_table['broad_scale_fixed'].replace('nan[nan]',np.nan)
+merge_table['broad_scale_fixed'].value_counts()

sql/env_mapping.sql

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+-- SQLITE
+CREATE TABLE new_env_mapping AS
+SELECT distinct
+	subject as term_id,
+	value as label
+from
+	statements s
+where
+	predicate = 'rdfs:label'
+	and subject like 'ENVO:%';

sql/merged_table.sql

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+-- SQLite
+-- before this i created a new table for the mapping called new_env_mapping and
+-- dumpped the harmonized table into envo.db 
+CREATE TABLE merged AS 
+    SELECT * 
+    FROM 
+        harmonized_wide_sel_envs big_table
+    LEFT JOIN new_env_mapping AS map 
+        ON 
+        big_table.env_broad_scale = map.label;