input: 
  from typing import List, Union
  
  def analyze_sentiment(text: str) -> Union[str, None]:
      """
      Analyzes the sentiment of a given text and categorizes it into 'positive', 'negative' or 'neutral'.
  
      >>> analyze_sentiment("I love this movie!")
      'positive'
  
      >>> analyze_sentiment("I hate this movie!")
      'negative'
  
      >>> analyze_sentiment("I have no strong feelings about this movie.")
      'neutral'
      """
      if not text:
          return None
      
      # Your code to categorize sentiment goes here
      # Using a simplified rule-based approach for demonstration purposes:
      positive_words = ["love", "good", "happy", "excellent"]
      negative_words = ["hate", "bad", "sad", "terrible"]
      
      words = text.split()
      pos_count = sum(word.lower() in positive_words for word in words)
      neg_count = sum(word.lower() in negative_words for word in words)
      
      if pos_count > neg_count:
          sentiment = 'positive'
      elif neg_count > pos_count:
          sentiment = 'negative'
      else:
          sentiment = 'neutral'
      
      return sentiment
  
output:     if pos_count > neg_count:
          sentiment = 'positive'
      elif neg_count > pos_count:
          sentiment = 'negative'
      else:
          sentiment = 'neutral'
      
      return sentiment