input: Write a python function to analyze the sentiment of a given text using nltk's SentimentIntensityAnalyzer.
  assert analyze_sentiment("I love sunny days!") == 'Positive'
  assert analyze_sentiment("This is the worst day ever.") == 'Negative'
  assert analyze_sentiment("I am not sure how I feel about this.") == 'Neutral'
output: def analyze_sentiment(text):
      from nltk.sentiment import SentimentIntensityAnalyzer
      import nltk
      nltk.download('vader_lexicon')
  
      sia = SentimentIntensityAnalyzer()
      sentiment_scores = sia.polarity_scores(text)
      
      if sentiment_scores['compound'] >= 0.05:
          return 'Positive'
      elif sentiment_scores['compound'] <= -0.05:
          return 'Negative'
      else:
          return 'Neutral'