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First, we need to preprocess this string to extract relevant features. This can involve cleaning the string, splitting it into components, and then converting those components into a numerical format that can be used by machine learning algorithms. Exploring Cultural Exchange and Identity in the Digital

# Assuming features is the output from the previous function features_df = pd.DataFrame([features]) one_hot = pd.get_dummies(features_df['content_type']) features_df = pd.concat([features_df, one_hot], axis=1) features_df['date'] = features_df['date'].apply(lambda x: x.timestamp() if x else 0)