CSV数据如何解析？导入导出完整教程

import csv

def parse_csv_basic(filepath):
    data = []
    try:
        # newline=''是个小细节，它能防止在Windows系统上写入CSV时出现额外的空行。
        # encoding='utf-8'是处理中文或特殊字符的关键，不然很容易乱码。
        with open(filepath, 'r', newline='', encoding='utf-8') as csvfile:
            reader = csv.reader(csvfile)
            header = next(reader) # 通常第一行是表头
            for row in reader:
                data.append(row)
        print(f"成功读取 {len(data)} 行数据。")
        return header, data
    except FileNotFoundError:
        print(f"错误：文件 '{filepath}' 不存在。")
        return None, None
    except Exception as e:
        print(f"读取CSV时发生错误：{e}")
        return None, None

# 示例调用 (请替换为你的CSV文件路径)
# header, rows = parse_csv_basic('your_data.csv')
# if header and rows:
#     print("表头:", header)
#     print("前5行数据:", rows[:5])

import pandas as pd

def parse_csv_pandas(filepath):
    try:
        # read_csv功能非常强大，能自动推断分隔符、处理引号、跳过空行等
        df = pd.read_csv(filepath, encoding='utf-8')
        print(f"成功使用pandas读取 {len(df)} 行数据。")
        return df
    except FileNotFoundError:
        print(f"错误：文件 '{filepath}' 不存在。")
        return None
    except Exception as e:
        print(f"使用pandas读取CSV时发生错误：{e}")
        return None

# 示例调用 (请替换为你的CSV文件路径)
# df = parse_csv_pandas('your_large_data.csv')
# if df is not None:
#     print(df.head())

import csv

def export_csv_basic(filepath, header, data):
    try:
        with open(filepath, 'w', newline='', encoding='utf-8') as csvfile:
            writer = csv.writer(csvfile)
            writer.writerow(header) # 写入表头
            writer.writerows(data) # 写入所有行
        print(f"数据已成功导出到 '{filepath}'。")
    except Exception as e:
        print(f"导出CSV时发生错误：{e}")

# 示例调用 (假设之前有header和rows数据)
# export_csv_basic('output_data.csv', header, rows)

import pandas as pd

def export_csv_pandas(filepath, dataframe):
    try:
        # index=False 避免将DataFrame的索引也写入CSV
        dataframe.to_csv(filepath, index=False, encoding='utf-8')
        print(f"数据已成功导出到 '{filepath}'。")
    except Exception as e:
        print(f"使用pandas导出CSV时发生错误：{e}")

# 示例调用 (假设之前有df数据)
# export_csv_pandas('output_dataframe.csv', df)