Python中从CSV文件筛选匹配输入值的指定列数据及修正长度判断错误的技术问询

Let’s work through both of your issues step by step to get your code working exactly as you need:

1. Print Only Specified Columns #

Instead of returning the entire matching row(s), you can explicitly select the columns you want using pandas' indexing. You have two straightforward options:

• Use column names (more readable, recommended if you know the exact labels in your CSV):
  result = file.loc[file['Column 2'] == codeNum, ['Column 4', 'Column 5']]
• Use position-based indexing (if you only know column positions—remember pandas uses 0-based indexing, so 3 = 4th column, 4 = 5th column):
  result = file.loc[file['Column 2'] == codeNum, file.columns[[3, 4]]]

Printing result after this will only show the columns you specified, not the entire row.

2. Fix Length Validation & Exact Matching Issues #

Your current code has two key problems here:

• Length check logic: Your condition len(str(codeNum)) >3 and len(str(codeNum)) <15 excludes values with exactly 3 or 15 characters. Since your requirement is 3–15 characters (inclusive), adjust it to >=3 and <=15.
• Substring vs exact match: str.contains() returns any row where your input appears anywhere in Column 2 (e.g., input "100" will match "1000" or "2100"). For precise matches, use exact equality (==) instead.
• Input format preservation: Converting input to int strips leading zeros (e.g., "0100" becomes 100, which changes its length from 4 to 3). If your codes might have leading zeros, keep the input as a string.

Revised Full Code #

Here’s the updated code with all fixes applied:

import pandas as pd

# Load your CSV file
file = pd.read_csv('filename.csv', encoding="ISO-8859-1", engine='python', sep=';')

def codechoice():
    # Keep input as string to preserve leading zeros and accurate length measurement
    codeNum = input("What's the code: ").strip()
    
    # Validate code length (3 to 15 characters inclusive)
    if 3 <= len(codeNum) <= 15:
        # Filter rows where Column 2 exactly matches the input, then select Column 4 and 5
        # Adjust column names to match your actual CSV labels
        result = file.loc[file['Column 2'] == codeNum, ['Column 4', 'Column 5']]
        
        # Handle cases where no matches are found
        if result.empty:
            print("No matching rows found for that code.")
        else:
            print(result)
    else:
        print("Error: Code must be between 3 and 15 characters long.")

codechoice()

Key Changes Breakdown: #

• Input handling: Removed int() conversion to keep the input as a string, ensuring leading zeros stay intact and length is measured correctly.
• Length validation: Updated the condition to include boundary values (3 and 15 characters) as required.
• Exact matching: Replaced str.contains() with direct equality check to avoid unintended substring matches.
• Targeted columns: Used loc to filter rows and select only the columns you want to print.
• User feedback: Added a check for empty results to inform you when no matches exist.

If your Column 2 stores numeric values instead of strings, convert the input to the appropriate type before comparing:

codeNum = int(input("What's the code: ").strip())
# Then use file['Column 2'] == codeNum as before

内容的提问来源于stack exchange，提问作者al berto