Update README.md

README.md

@@ -16,4 +16,78 @@ configs:
   data_files:
   - split: train
     path: data/train-*
+license: cc
+language:
+- ml
+- en
+size_categories:
+- 1M<n<10M
 ---
+
+## English Malayalam Names
+
+### Dataset Description
+
+This dataset has 27787044 person names both in English and Malayalam. The source for this dataset is various election roles published by Government.
+
+Derived From: https://huggingface.co/datasets/santhosh/english-malayalam-names 
+
+- **Curated by:** Bajiyo Baiju
+- **License:** CC-BY-SA-4.0
+
+
+## Uses
+
+- English <-> Malayalam name transliteration tasks
+- Named entity recognition
+- Person name recognition
+
+## Dataset Curation
+
+```
+# Assuming 'ml' is the column containing Malayalam names and 'en' is the English names column in your dataset
+from datasets import load_dataset
+
+data = load_dataset("santhosh/english-malayalam-names")
+
+malayalam_names = data['ml'].tolist() 
+english_names = data['en'].tolist()
+
+# Define a function to check if a name contains mostly English characters
+def is_english_name(name):
+    english_char_count = sum(c.isalpha() and c.isascii() for c in name)
+    return english_char_count / len(name) > 0.5  # Adjust the threshold as needed
+
+# Find and count names that are likely to be English in 'ml' column
+english_names_ml_column = [name for name in malayalam_names if is_english_name(name)]
+count_english_names_ml_column = len(english_names_ml_column)
+
+# Find Malayalam words in the 'en' column
+malayalam_words_en_column = [word for word in english_names if not any(c.isascii() for c in word)]
+count_malayalam_words_en_column = len(malayalam_words_en_column)
+
+# Print the results
+print("Count of English-like Names in Malayalam Names Column:", count_english_names_ml_column)
+#print("English-like Names in Malayalam Names Column:", english_names_ml_column)
+
+print("\nCount of Malayalam Words in English Names Column:", count_malayalam_words_en_column)
+print("Malayalam Words in English Names Column:", malayalam_words_en_column)
+
+# Identify English-like names and remove them
+english_names_mask = data['ml'].isin(english_names_ml_column)
+data = data[~english_names_mask]
+
+# Identify Malayalam words and remove them
+malayalam_words_mask = data['en'].isin(malayalam_words_en_column)
+data = data[~malayalam_words_mask]
+
+# Remove empty rows
+data = data[(data['ml'] != '') & (data['en'] != '')]
+
+# Verify the changes
+print("Updated 'ml' column after removing English-like Names:")
+print(data['ml'])
+
+print("\nUpdated 'en' column after removing Malayalam Words:")
+print(data['en'])
+```