Update Naija-Lexicons.py

Naija-Lexicons.py

@@ -36,7 +36,7 @@ _CITATION = """\
       Emezue, Chris Chinenye  and
       Abdullahi, Saheed Salahudeen  and
       Aremu, Anuoluwapo  and
-      Jorge, Al{\'\i}pio  and
+      Jorge, Al{\"\i}pio  and
       Brazdil, Pavel",
     booktitle = "Proceedings of the Thirteenth Language Resources and Evaluation Conference",
     month = jun,
@@ -54,7 +54,7 @@ import pandas as pd
 
 import datasets
 
-LANGUAGES = ['hausa', 'igbo', 'yoruba']
+LANGUAGES = ["hausa", "igbo", "yoruba"]
 
 class NaijaLexiconsConfig(datasets.BuilderConfig):
     """BuilderConfig for NaijaLexicons"""
@@ -106,8 +106,8 @@ class NaijaLexicons(datasets.GeneratorBasedBuilder):
                 description=textwrap.dedent(
                     f"""{_DESCRIPTION}"""
                 ),
-                text_features={"word": "word", 'machine': 'machine', 'human': 'human', 'emotion_intensity_score': 'emotion_intensity_score'},
-                label_classes=['positive', 'negative', 'surprise', 'fear', 'anticipation', 'anger', 'joy', 'trust', 'disgust', 'sadness'],
+                text_features={"word": "word", "machine": "machine", "human": "human", "emotion_intensity_score": "emotion_intensity_score"},
+                label_classes=["positive", "negative", "surprise", "fear", "anticipation", "anger", "joy", "trust", "disgust", "sadness"],
                 label_column="label",
                 manual_sentiment_url=f"https://raw.githubusercontent.com/hausanlp/NaijaSenti/main/data/lexicons/manual-sentiment/huggingface/{lang}.csv",
                 translated_sentiment_url=f"https://raw.githubusercontent.com/hausanlp/NaijaSenti/main/data/lexicons/translated-sentiment/huggingface/{lang}.csv",
@@ -135,28 +135,28 @@ class NaijaLexicons(datasets.GeneratorBasedBuilder):
         translated_emotion_path = dl_manager.download_and_extract(self.config.translated_emotion_url)
         
         return [
-            datasets.SplitGenerator(name='manual_sentiment', gen_kwargs={"filepath": manual_sentiment_path}),
-            datasets.SplitGenerator(name='translated_sentiment', gen_kwargs={"filepath": translated_sentiment_path}),
-            datasets.SplitGenerator(name='translated_emotion', gen_kwargs={"filepath": translated_emotion_path})
+            datasets.SplitGenerator(name="manual_sentiment", gen_kwargs={"filepath": manual_sentiment_path}),
+            datasets.SplitGenerator(name="translated_sentiment", gen_kwargs={"filepath": translated_sentiment_path}),
+            datasets.SplitGenerator(name="translated_emotion", gen_kwargs={"filepath": translated_emotion_path})
         ]
 
     def _generate_examples(self, filepath):
         df = pd.read_csv(filepath)
 
-        print('-'*100)
+        print("-"*100)
         print(df.head())
-        print('-'*100)
+        print("-"*100)
 
-        if self.config.name == 'translated-sentiment':
+        if self.config.name == "translated-sentiment":
             for id_, row in df.iterrows():
                 word = row["word"]
-                machine = row['machine']
-                human = row['human']
+                machine = row["machine"]
+                human = row["human"]
                 label = row["label"]
 
-                yield id_, {"word": word, 'machine': machine, 'human': human, "label": label}
+                yield id_, {"word": word, "machine": machine, "human": human, "label": label}
 
-        elif self.config.name == 'manual-sentiment':
+        elif self.config.name == "manual-sentiment":
             for id_, row in df.iterrows():
                 word = row["word"]
                 label = row["label"]
@@ -166,9 +166,9 @@ class NaijaLexicons(datasets.GeneratorBasedBuilder):
         else:
             for id_, row in df.iterrows():
                 word = row["word"]
-                machine = row['machine']
-                human = row['human']
+                machine = row["machine"]
+                human = row["human"]
                 label = row["label"]
-                emotion_intensity_score = row['emotion_intensity_score']
+                emotion_intensity_score = row["emotion_intensity_score"]
 
-                yield id_, {"word": word, 'machine': machine, 'human': human, "label": label, 'emotion_intensity_score': emotion_intensity_score}
+                yield id_, {"word": word, "machine": machine, "human": human, "label": label, "emotion_intensity_score": emotion_intensity_score}