exploring_stanza_13.py

# What is the sentiment surrounding each character?
def sentiment_descriptor_to_val(descriptor):
    """
    - Parameters: descriptor ("negative", "neutral", or "positive")
    - Returns: -1 for "negative", 0 for "neutral", 1 for "positive"
    """
    if descriptor == "negative":
        return -1
    elif descriptor == "neutral":
        return 0
    else:
        return 1

def character_sentiment(df):
    """
    - Parameters: df (Pandas DataFrame)
    - df must contain "text" and "sentiment_descriptor" columns.
    - Returns: 
    """
    sentiment = df.copy()
    sentiment["sentence_sentiment"] = [
        sentiment_descriptor_to_val(s) for s
        in sentiment["sentence_sentiment"]
    ]
    sentiment = sentiment[["text", "sentence_sentiment"]]
    sentiment = sentiment.groupby("text").sum().reset_index()
    
    return sentiment.sort_values("sentence_sentiment")

sentiment_df = character_sentiment(characters)

print("Characters in the most negative settings.")
display(sentiment_df.head(5))

# Characters in the most negative settings.
#       text        sentence_sentiment
# 6     Ahab        -42
# 508   Queequeg    -24
# 317   Jonah       -18
# 588   Stubb       -11
# 468   Pequod      -10

print("Characters in the most positive settings")
display(sentiment_df.tail(5))

# Characters in the most positive settings
#       text        sentence_sentiment
# 1     Abraham     2
# 424   Monsieur    3
# 218   Gabriel     3
# 401   Mary        4
# 93    Bunger      4