如何用Python从指定CSV文件中提取中性词至TXT文件

Hey there! As a Python newbie, file handling can feel a bit overwhelming at first, but let's break this down into simple, actionable steps to extract those neutral words from your CSV and save them to a TXT file. I'll give you two options—one using a popular library for easy CSV handling, and another using Python's built-in tools if you don't want to install anything extra.

Option 1: Use Pandas (Simpler for CSV Tasks) #

Pandas is a go-to library for working with tabular data like CSVs, and it's super beginner-friendly once you set it up.

Step 1: Install Pandas #

Open your terminal/command prompt and run this command to install the library:

pip install pandas

Step 2: Full Code with Explanations #

Copy this code into a new Python file (e.g., extract_neutral_words.py), then adjust the file paths and threshold to match your needs:

import pandas as pd

# 1. Load the CSV file (replace 'your_review_data.csv' with your actual file name/path)
df = pd.read_csv('your_review_data.csv')

# 2. Define what counts as a "neutral" word
# We'll use words where the sentiment score's absolute value is ≤ 0.01 (adjust this number as needed!)
neutral_words = df[df['Sentiment Score'].abs() <= 0.01]['Word']

# 3. Save the neutral words to a TXT file
# index=False skips row numbers, header=False skips the "Word" column name
neutral_words.to_csv('neutral_words.txt', index=False, header=False)

# Optional: Print a sample to verify
print("Sample neutral words:", neutral_words.head(10).tolist())

Option 2: Use Python's Built-in CSV Module (No External Libraries) #

If you don't want to install pandas, you can use Python's built-in csv module. This is great for keeping things lightweight.

Full Code with Explanations #

import csv

neutral_words = []

# 1. Open and read the CSV file
# Replace 'your_review_data.csv' with your actual file name/path
with open('your_review_data.csv', 'r', newline='', encoding='utf-8') as csv_file:
    # Use DictReader to access columns by name
    reader = csv.DictReader(csv_file)
    
    # Loop through each row in the CSV
    for row in reader:
        # Convert the sentiment score from string to float
        sentiment_score = float(row['Sentiment Score'])
        
        # Check if the word is neutral (adjust the threshold here too!)
        if abs(sentiment_score) <= 0.01:
            neutral_words.append(row['Word'])

# 2. Save the neutral words to a TXT file
with open('neutral_words.txt', 'w', encoding='utf-8') as txt_file:
    # Write each word on a new line
    for word in neutral_words:
        txt_file.write(f"{word}\n")

# Optional: Print a sample to verify
print("Sample neutral words:", neutral_words[:10])

Key Notes for You: #

• File Paths: If your CSV file isn't in the same folder as your Python script, replace the file name with the full path (e.g., 'C:/Users/YourName/Documents/Amazon_Review_Sentiment_Analysis/review_data.csv' for Windows, or '/home/yourname/Documents/Amazon_Review_Sentiment_Analysis/review_data.csv' for macOS/Linux).
• Neutral Threshold: The 0.01 value is a starting point. If you want more words to count as neutral, increase it (e.g., 0.02); if you want stricter neutrality, decrease it (e.g., 0.005).
• Encoding: Using encoding='utf-8' ensures you don't get weird character issues when reading/writing files.

内容的提问来源于stack exchange，提问作者ANiK3T