如何在C++中读取文件内带逗号分隔的数字并转为整数？

Great question! You don’t need regex for this—there are simpler, more readable ways to handle comma-separated numbers when reading from CSV. Let’s break down two common approaches depending on what tools you’re using:

Basic Python (No External Libraries) #

If you’re using Python’s built-in csv module, you can easily strip the commas from the string value before converting it to an integer. This is straightforward and avoids regex entirely.

Here’s a quick example:

import csv

# Open your CSV file
with open('your_data.csv', 'r') as csv_file:
    csv_reader = csv.reader(csv_file)
    
    # Skip header row if you have one
    next(csv_reader)
    
    for row in csv_reader:
        # Assume the number is in the first column (adjust index as needed)
        number_string = row[0]
        # Remove all commas from the string
        cleaned_string = number_string.replace(',', '')
        # Convert to integer
        number_integer = int(cleaned_string)
        
        # Now you can store or use the integer
        print(number_integer)  # Outputs 1000000 for "1,000,000"

Using Pandas (For Larger Datasets) #

If you’re working with bigger datasets and using pandas, it has a built-in parameter to handle thousands separators directly when reading the CSV. This saves you from manually cleaning each value.

Example:

import pandas as pd

# Read CSV, specifying the thousands separator
df = pd.read_csv('your_data.csv', thousands=',')

# The column containing comma-separated numbers will now be an integer (or float if decimals exist)
# Verify the data type
print(df['your_number_column'].dtype)  # Should show int64 (or similar)

A Quick Note on Regex #

While regex could work here (e.g., re.sub(r',', '', number_string)), it’s overkill for this simple task. The str.replace() method is faster, more readable, and easier to maintain—especially if you’re not comfortable with regex syntax.

内容的提问来源于stack exchange，提问作者wolnio