使用DataFrame.apply()时出现语法错误，求代码修正方案

Let's break down the problems in your code and fix them step by step.

1. Root Cause of the SyntaxError #

Your lambda line has two critical syntax mistakes:

• Extra closing bracket: scores["compound"]] should be scores["compound"] (the extra ] is invalid).
• Missing else in the ternary condition chain: Python requires else between consecutive if clauses in a ternary expression.

2. Broader Issues in Your Code Structure #

Beyond the syntax error, your code has inefficiencies and logical flaws:

• You're overwriting your DataFrame inside the loop with df = pd.DataFrame(columns=['sentiment']), which erases your original data.
• Looping through the body column as a list is unnecessary—pandas' apply method can handle this directly on the column.
• Applying the lambda to an empty sentiment column doesn't serve any purpose; you need to compute sentiment from the body text and assign it to the new column.

3. Corrected Code #

Here's the cleaned-up, working version (I'll use a named function for readability, though a lambda is also possible):

import pandas as pd  # Don't forget to import pandas!
import nltk
nltk.download('vader_lexicon')
nltk.download('punkt')
from nltk.sentiment.vader import SentimentIntensityAnalyzer

# Initialize VADER once (no need to reinitialize in loops)
sid = SentimentIntensityAnalyzer()

# Define a helper function to calculate sentiment
def determine_sentiment(text):
    sentiment_scores = sid.polarity_scores(text)
    compound_score = sentiment_scores['compound']
    
    if compound_score >= 0.05:
        return 'positive'
    elif compound_score <= -0.05:
        return 'negative'
    else:
        return 'neutral'

# Apply the function to your 'body' column to create the 'sentiment' column
df['sentiment'] = df['body'].apply(determine_sentiment)

If You Prefer Using a Lambda #

If you want to stick with a lambda (though less readable for complex logic), here's the corrected version:

df['sentiment'] = df['body'].apply(
    lambda text: 'positive' if sid.polarity_scores(text)['compound'] >= 0.05 
    else 'negative' if sid.polarity_scores(text)['compound'] <= -0.05 
    else 'neutral'
)

Key Improvements #

• No more loops: Using apply directly on the body column is more efficient and idiomatic pandas.
• Preserves original data: We modify the existing DataFrame instead of creating a new empty one each time.
• Readable logic: The named function makes it easy to adjust sentiment thresholds or add additional logic later.

内容的提问来源于stack exchange，提问作者ASH