Update util/preprocessing.py

util/preprocessing.py

@@ -1,28 +1,28 @@
-import difflib
-import pandas as pd
-
-def word_to_market_name(word):
-    markets_df = pd.read_csv('data\market_name_utf8.csv')
-    markets_names = markets_df['시장명']
-
-    scores = dict()
-
-    for m in markets_names:
-        sm = difflib.SequenceMatcher(None, word, m)
-        scores[m] = sm.ratio()  
-
-    sorted_scores = sorted(scores.items(), key=lambda item: item[1], reverse=True)
-    top_3_markets = [market[0] for market in sorted_scores[:3]]
-
-    return top_3_markets
-
-
-
-def check_word(word):
-    markets_df = pd.read_csv('data\market_name_utf8.csv')
-    markets_names = markets_df['시장명']
-
-    for word in markets_names:
-        return True
-
+import difflib
+import pandas as pd
+
+def word_to_market_name(word):
+    markets_df = pd.read_csv('data/market_name_utf8.csv')
+    markets_names = markets_df['시장명']
+
+    scores = dict()
+
+    for m in markets_names:
+        sm = difflib.SequenceMatcher(None, word, m)
+        scores[m] = sm.ratio()  
+
+    sorted_scores = sorted(scores.items(), key=lambda item: item[1], reverse=True)
+    top_3_markets = [market[0] for market in sorted_scores[:3]]
+
+    return top_3_markets
+
+
+
+def check_word(word):
+    markets_df = pd.read_csv('data/market_name_utf8.csv')
+    markets_names = markets_df['시장명']
+
+    for word in markets_names:
+        return True
+
     return False