sentiment_analyzer_tweets.py

def getSentiment(df, measurement="compound"):
    """
    Given a DF of tweets, analyzes the tweets and returns a new DF
    of sentiment scores based on the given measurement.
    Accepted sentiment measurements: ["pos", "neg", "neu", "compound"]
    """

    # Sentiment Analyzer
    sia = SentimentIntensityAnalyzer()

    # Getting the sentiment score
    df['sentiment'] = df['tweet'].apply(lambda x: sia.polarity_scores(x)[measurement])

    # Creating a DF with the average sentiment score each day
    sent_df = df.groupby('date')['sentiment'].mean().reset_index()
    
    # Converting the dates to datetime
    sent_df['date'] = sent_df['date'].apply(lambda x: datetime.strptime(x, "%Y-%m-%d"))
    
    return sent_df