遍历工作目录子文件夹提取CSV指定数据的实现问题

Hey there! You’re already halfway there since you can list the folders and files—let’s lock in the nested logic to pull the data you need and assemble that DataFrame. Here’s a straightforward, robust approach:

Step 1: Import Required Tools #

First, grab the libraries we’ll need for file navigation and DataFrame building:

import os
import pandas as pd

Step 2: Prep a Storage List #

We’ll use a list to collect each folder’s data (name, 2nd value, last value) before converting it to a DataFrame—this keeps things clean as we loop:

extracted_data = []

Step 3: Loop Through Subfolders & Extract Values #

We’ll iterate through every subfolder in your current working directory, locate data.csv, pull the required values, and handle edge cases (like missing files or short CSVs) to avoid crashes:

# Get all subfolders in the current working directory
subfolders = [folder for folder in os.listdir('.') if os.path.isdir(folder)]

for folder_name in subfolders:
    # Build the full path to the data.csv file
    csv_file_path = os.path.join(folder_name, 'data.csv')
    
    # Skip if the file doesn't exist
    if not os.path.exists(csv_file_path):
        print(f"Warning: No data.csv found in {folder_name}—skipping.")
        continue
    
    try:
        # Read the CSV (use header=None if your file has no column headers)
        csv_content = pd.read_csv(csv_file_path, header=None)
        
        # Grab the 2nd value (Python uses 0-indexing, so index 1)
        second_value = csv_content.iloc[1, 0] if len(csv_content) >= 2 else "N/A"
        
        # Grab the last value
        last_value = csv_content.iloc[-1, 0] if len(csv_content) >= 1 else "N/A"
        
        # Add the folder's data to our list
        extracted_data.append({
            'Folder Name': folder_name,
            '2nd value': second_value,
            'Last value': last_value
        })
    except Exception as e:
        print(f"Error processing {csv_file_path}: {str(e)}")

Step 4: Assemble the Final DataFrame #

Turn our collected list into the DataFrame format you want:

final_df = pd.DataFrame(extracted_data)
# Reorder columns to match your requested layout
final_df = final_df[['Folder Name', '2nd value', 'Last value']]

# Check the result or save it
print(final_df)
# final_df.to_csv('folder_data_summary.csv', index=False)

Quick Adjustments for Your CSV Structure: #

• If your data.csv has column headers, remove header=None from pd.read_csv() and adjust the index logic (e.g., use csv_content['your_column_name'].iloc[1] instead of csv_content.iloc[1,0]).
• If you need values from a specific column (not the first one), replace the 0 in iloc[1,0] with the column index you need.

内容的提问来源于stack exchange，提问作者user1969717