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| import pandas as pd | |
| # Load feature dataset | |
| df = pd.read_csv("features_tweets.csv") | |
| if "label" in df.columns: | |
| df = df.drop(columns=["label"]) | |
| # ---------------------------- | |
| # Binary Labeling Function | |
| # ---------------------------- | |
| # 1 β Code-mixed (contains both English + Pidgin) | |
| # 0 β Not code-mixed (mostly English) | |
| def assign_binary_label(row): | |
| return 1 if row["code_mixed_score"] == 1 else 0 | |
| # Apply labeling | |
| df["label"] = df.apply(assign_binary_label, axis=1) | |
| # ---------------------------- | |
| # Save labeled dataset | |
| # ---------------------------- | |
| df.to_csv("binary_labeled_tweets.csv", index=False) | |
| print("Binary labeling complete β ") | |
| print(df["label"].value_counts()) | |
| print(df.head()) |