import csv

# 讀取CSV文件
with open('employees.csv', 'r', encoding='utf-8') as file:
    reader = csv.reader(file)
    for row_num, row in enumerate(reader, 1):
        print(f"第{row_num}行: {row}")

import csv

# 準(zhǔn)備數(shù)據(jù)
sample_data = [
    ['姓名', '年齡', '城市', '職業(yè)'],
    ['張三', '25', '北京', '工程師'],
    ['李四', '30', '上海', '設(shè)計(jì)師'],
    ['王五', '28', '廣州', '產(chǎn)品經(jīng)理']
]

# 寫入CSV文件
with open('employees.csv', 'w', newline='', encoding='utf-8') as file:
    writer = csv.writer(file)
    writer.writerows(sample_data)

print("已創(chuàng)建示例CSV文件 'employees.csv'")

import csv

with open('employees.csv', 'r', encoding='utf-8') as file:
    dict_reader = csv.DictReader(file)
    for row_num, row in enumerate(dict_reader, 1):
        print(f"員工{row_num}:")
        for key, value in row.items():
            print(f"  {key}: {value}")
        print()

import csv

# 準(zhǔn)備字段名稱和數(shù)據(jù)
fieldnames = ['姓名', '年齡', '城市', '職業(yè)']
new_employee = {
    '姓名': '周九',
    '年齡': '29',
    '城市': '武漢',
    '職業(yè)': '前端開發(fā)'
}

# 追加新員工數(shù)據(jù)
with open('employees.csv', 'a', newline='', encoding='utf-8') as file:
    dict_writer = csv.DictWriter(file, fieldnames=fieldnames)
    dict_writer.writerow(new_employee)

print("已使用DictWriter添加新員工")

import csv

# 創(chuàng)建使用分號(hào)分隔的CSV文件
custom_data = [
    ['產(chǎn)品名稱', '價(jià)格', '庫存'],
    ['蘋果', '5.5', '100'],
    ['香蕉', '3.2', '200'],
    ['橙子', '4.8', '150']
]

with open('products.csv', 'w', newline='', encoding='utf-8') as file:
    writer = csv.writer(file, delimiter=';', quoting=csv.QUOTE_MINIMAL)
    writer.writerows(custom_data)

print("已創(chuàng)建使用分號(hào)分隔的CSV文件 'products.csv'")

# 讀取自定義分隔符的CSV文件
with open('products.csv', 'r', encoding='utf-8') as file:
    reader = csv.reader(file, delimiter=';')
    for row_num, row in enumerate(reader, 1):
        print(f"第{row_num}行: {row}")

import csv

# 創(chuàng)建包含特殊字符的CSV數(shù)據(jù)
special_data = [
    ['姓名', '描述'],
    ['張三', '喜歡"Python"編程'],
    ['李四', '愛好: 讀書, 游泳, 旅行'],
    ['王五', '地址: 北京市朝陽區(qū)\n郵編: 100000']
]

with open('special.csv', 'w', newline='', encoding='utf-8') as file:
    writer = csv.writer(file, quoting=csv.QUOTE_ALL)
    writer.writerows(special_data)

print("已創(chuàng)建包含特殊字符的CSV文件 'special.csv'")

# 讀取包含特殊字符的CSV文件
with open('special.csv', 'r', encoding='utf-8') as file:
    reader = csv.reader(file)
    for row_num, row in enumerate(reader, 1):
        print(f"第{row_num}行: {row}")

import csv

def count_employees_by_city(csv_file):
    """統(tǒng)計(jì)不同城市的員工數(shù)量"""
    city_count = {}
    
    with open(csv_file, 'r', encoding='utf-8') as file:
        dict_reader = csv.DictReader(file)
        for row in dict_reader:
            city = row['城市']
            if city in city_count:
                city_count[city] += 1
            else:
                city_count[city] = 1
    
    return city_count

# 示例使用
if __name__ == "__main__":
    # 假設(shè)employees.csv文件已存在
    city_counts = count_employees_by_city('employees.csv')
    print("各城市員工數(shù)量統(tǒng)計(jì):")
    for city, count in city_counts.items():
        print(f"  {city}: {count}人")

import csv
import json

def csv_to_json(csv_file, json_file):
    """將CSV文件轉(zhuǎn)換為JSON文件"""
    data = []
    
    with open(csv_file, 'r', encoding='utf-8') as file:
        dict_reader = csv.DictReader(file)
        for row in dict_reader:
            data.append(row)
    
    with open(json_file, 'w', encoding='utf-8') as file:
        json.dump(data, file, ensure_ascii=False, indent=2)
    
    print(f"已將 {csv_file} 轉(zhuǎn)換為 {json_file}")

# 示例使用
if __name__ == "__main__":
    csv_to_json('employees.csv', 'employees.json')

import csv

def filter_employees_by_age(csv_file, min_age):
    """過濾年齡大于等于指定值的員工"""
    filtered_data = []
    
    with open(csv_file, 'r', encoding='utf-8') as file:
        dict_reader = csv.DictReader(file)
        fieldnames = dict_reader.fieldnames
        
        for row in dict_reader:
            if int(row['年齡']) >= min_age:
                filtered_data.append(row)
    
    # 保存過濾結(jié)果
    output_file = f'employees_age_{min_age}+.csv'
    with open(output_file, 'w', newline='', encoding='utf-8') as file:
        dict_writer = csv.DictWriter(file, fieldnames=fieldnames)
        dict_writer.writeheader()
        dict_writer.writerows(filtered_data)
    
    print(f"已過濾并保存結(jié)果到 {output_file}")
    return filtered_data

# 示例使用
if __name__ == "__main__":
    filtered = filter_employees_by_age('employees.csv', 30)
    print(f"過濾后共有 {len(filtered)} 名員工")

import csv
import os

def merge_csv_files(input_files, output_file):
    """合并多個(gè)CSV文件"""
    if not input_files:
        print("沒有輸入文件")
        return
    
    # 讀取第一個(gè)文件的表頭
    with open(input_files[0], 'r', encoding='utf-8') as file:
        dict_reader = csv.DictReader(file)
        fieldnames = dict_reader.fieldnames
    
    # 合并數(shù)據(jù)
    merged_data = []
    for csv_file in input_files:
        with open(csv_file, 'r', encoding='utf-8') as file:
            dict_reader = csv.DictReader(file)
            for row in dict_reader:
                merged_data.append(row)
    
    # 寫入合并結(jié)果
    with open(output_file, 'w', newline='', encoding='utf-8') as file:
        dict_writer = csv.DictWriter(file, fieldnames=fieldnames)
        dict_writer.writeheader()
        dict_writer.writerows(merged_data)
    
    print(f"已合并 {len(input_files)} 個(gè)CSV文件到 {output_file}")
    print(f"總記錄數(shù): {len(merged_data)}")

# 示例使用
if __name__ == "__main__":
    input_files = ['employees1.csv', 'employees2.csv', 'employees3.csv']
    # 過濾存在的文件
    input_files = [f for f in input_files if os.path.exists(f)]
    if input_files:
        merge_csv_files(input_files, 'merged_employees.csv')
    else:
        print("沒有找到輸入文件")