Python处理CSV文件：采购订单数据统计需求求助

Hey there! Let's get your code sorted to handle all four of your tasks. I spotted a couple of small issues in your current code (like a misnamed variable home_runs that doesn’t relate to your data, and you might be grabbing the wrong column for purchase amounts), so let’s rebuild it properly.

First, let’s assume your purchases.csv has a header row (like Order ID,Amount) and each subsequent row has the order details, with the purchase amount in the second column (index 1). If your CSV doesn’t have a header, we can adjust that too—just remove one line we’ll mention later.

Here’s the complete working code:

import csv

# Initialize all tracking variables to 0
total_entries = 0
total_amount = 0
high_value_count = 0
high_value_total = 0

with open('purchases.csv') as csvfile:
    readCSV = csv.reader(csvfile, delimiter=',')
    # Skip the header row (delete this line if your CSV has no header)
    next(readCSV)
    
    for row in readCSV:
        # Convert amount from string to float, clean up extra spaces
        try:
            amount = float(row[1].strip())
        except ValueError:
            # Skip rows with invalid amount values to avoid crashes
            continue
        
        # Update overall purchase stats
        total_entries += 1
        total_amount += amount
        
        # Track high-value purchases (over $1800)
        if amount > 1800:
            high_value_count += 1
            high_value_total += amount

# Calculate averages (handle edge cases where there's no data)
average_purchase = round(total_amount / total_entries, 3) if total_entries > 0 else 0.0
high_value_average = round(high_value_total / high_value_count, 3) if high_value_count > 0 else 0.0

# Print results in your required format
print(f"Total Number of Purchases: {total_entries}")
print(f"Amount of Average Purchase: {average_purchase}")
print(f"Number of Purchase Orders over $1,800: {high_value_count}")
print(f"Amount of Average Purchases over $1,800: {high_value_average}")

Let’s break down what this code does: #

• Variable Setup: We start with all counters and totals set to 0 so we can increment them as we process each row.
• Header Handling: The next(readCSV) line skips the first header row so it doesn’t get counted as a purchase entry. Remove this line if your CSV has no header.
• Data Cleaning & Conversion: We convert the amount column from a string to a float (since CSVs read all data as strings) and use strip() to remove extra spaces. The try/except block skips any rows with invalid amount values to prevent errors.
• Stat Tracking: For each valid row, we update the total entry count and total purchase amount. We also check if the amount is over 1800 and update the high-value counters accordingly.
• Average Calculation: We use round() to get three decimal places, and add checks to avoid division by zero (in case there are no purchases or no high-value purchases).
• Formatted Output: We print each stat exactly as your required format specifies.

Notes on your original code: #

• You had home_runs in your loop—this was probably a copy-paste error, and should have referenced your purchase data list.
• You were adding row[0] to your list, which is likely the order ID, not the purchase amount. We switched to row[1] for the amount (adjust this index if your amount is in a different column).
• Your original code only tried to count total entries; we’ve expanded it to track all four required metrics.

内容的提问来源于stack exchange，提问作者coderchick2016