Sentiment Analysis Python Project.txt

from textblob import TextBlob
import matplotlib.pyplot as plt

def analyze_sentiment(text):
    blob = TextBlob(text)
    polarity = blob.sentiment.polarity
    if polarity > 0.1:
        return 'Positive'
    elif polarity < -0.1:
        return 'Negative'
    else:
        return 'Neutral'

def analyze_texts(texts):
    results = [analyze_sentiment(text) for text in texts]
    return results

def summary_report(results):
    from collections import Counter
    counts = Counter(results)
    total = sum(counts.values())
    print("Sentiment Summary Report:")
    for sentiment, count in counts.items():
        print(f"{sentiment}: {count} ({count/total:.1%})")
    return counts

def plot_results(counts):
    labels = counts.keys()
    values = counts.values()
    plt.bar(labels, values, color=['green', 'gray', 'red'])
    plt.title("Sentiment Analysis")
    plt.xlabel("Sentiment")
    plt.ylabel("Count")
    plt.show()

# Example usage:
# texts = ["I love this!", "It's okay.", "I hate this."]
# For file input:
# with open('input.txt') as f:
#     texts = f.readlines()

texts = [
    "I love this product!",
    "This is the worst experience ever.",
    "Meh, it's fine.",
    "Absolutely fantastic!",
    "Not good, not bad."
]

results = analyze_texts(texts)
counts = summary_report(results)
plot_results(counts)