Parquet file is added. XML TO PARQUET COnverter is added

aspect-based-sentiment-analysis-uzbek.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:e1b826d220907f9ec5ea83897b2e0b9d6af308699dcd6d690a4355942583394a
+size 330250

data/xml_to_parquet.py

@@ -0,0 +1,46 @@
+import xml.etree.ElementTree as ET
+import pandas as pd
+
+
+# Step 1: Parse XML
+def xml_to_list(filepath):
+    tree = ET.parse(filepath)
+    root = tree.getroot()
+
+    data = []
+    for sentence in root.findall("sentence"):
+        sentence_id = sentence.get("ID")
+        text = sentence.find("text").text
+
+        aspect_terms = []
+        for aspect_term in sentence.findall("./aspectTerms/aspectTerm"):
+            aspect_terms.append({
+                "term": aspect_term.get("term"),
+                "polarity": aspect_term.get("polarity"),
+                "from": int(aspect_term.get("from")),
+                "to": int(aspect_term.get("to")),
+            })
+
+        aspect_categories = []
+        for aspect_category in sentence.findall("./aspectCategories/aspectCategory"):
+            aspect_categories.append({
+                "category": aspect_category.get("category"),
+                "polarity": aspect_category.get("polarity"),
+            })
+
+        data.append({
+            "sentence_id": sentence_id,
+            "text": text,
+            "aspect_terms": aspect_terms,
+            "aspect_categories": aspect_categories,
+        })
+    return data
+
+
+xml_data = xml_to_list("absa_uz_all.xml")
+
+# Step 2: Convert to DataFrame
+df = pd.DataFrame(xml_data)
+
+# Step 3: Save as Parquet
+df.to_parquet("../aspect-based-sentiment-analysis-uzbek.parquet", index=False)