input: Write a python function to recommend movies with a rating of 4 or higher from provided movie and rating dataframes.
  ```python
  assert recommend_movies(movies_df, ratings_df).equals(expected_output_df)
  assert recommend_movies(another_movies_df, another_ratings_df).equals(another_expected_output_df)
  assert recommend_movies(empty_movies_df, empty_ratings_df).equals(pd.DataFrame())
output: def recommend_movies(movies_df, ratings_df):
      # Merge movies and ratings on movie_id
      merged_df = pd.merge(movies_df, ratings_df, on='movie_id')
      
      # Filter movies with ratings 4 or higher
      recommended_df = merged_df[merged_df['rating'] >= 4]
      
      # Drop duplicates to get unique movies
      recommended_df = recommended_df.drop_duplicates(subset='movie_id')
      
      # Return the recommended movies DataFrame
      return recommended_df[['movie_id', 'title', 'rating']]