input: Write a python function to perform sentiment analysis on a list of tweets and return their sentiment polarity and subjectivity.
  assert sentiment_analysis(["I love playing basketball with my friends!", "I hate wearing masks in public places.", "I'm feeling really happy today!", "I find it hard to concentrate on my studies recently."]) == [{'Polarity': 0.8, 'Subjectivity': 0.9}, {'Polarity': -0.8, 'Subjectivity': 0.9}, {'Polarity': 0.7, 'Subjectivity': 0.8}, {'Polarity': -0.2, 'Subjectivity': 0.5}]
  assert sentiment_analysis(["It's a beautiful day!", "I am so sad right now."]) == [{'Polarity': 0.85, 'Subjectivity': 0.85}, {'Polarity': -0.75, 'Subjectivity': 1.0}]
  assert sentiment_analysis(["I don't know how to feel about this.", "This is amazing!"]) == [{'Polarity': 0.0, 'Subjectivity': 0.5}, {'Polarity': 0.9, 'Subjectivity': 1.0}]
output: from textblob import TextBlob
  
  def sentiment_analysis(tweets):
      results = []
      for tweet in tweets:
          analysis = TextBlob(tweet)
          results.append({'Polarity': analysis.sentiment.polarity, 'Subjectivity': analysis.sentiment.subjectivity})
      return results