Python标准库之csv(1)

Python标准库之csv(1)

1.Python处理csv文件之csv.writer()

import csv

def csv_write(path,data):

    with open(path,'w',encoding='utf-8',newline='') as f:

        writer = csv.writer(f,dialect='excel')

        for row in data:

            writer.writerow(row)

    return True

调用上面的函数

data = [

    ['Name','Height'],

    ['Keys','176cm'],

    ['HongPing','160cm'],

    ['WenChao','176cm']

]

csv_write('test.csv',data)

运行结果

2.Python处理csv文件之csv.reader()

def csv_read(path):

    data = []

    with open(path,'r',encoding='utf-8') as f:

        reader = csv.reader(f,dialect='excel')

        for row in reader:

            data.append(row)

    return data

调用上面的函数

data = csv_read('test.csv')

print(data)

运行结果

[['Name', 'Height'], ['Keys', '176cm'], ['HongPing', '160cm'], ['WenChao', '176cm']]

3.Python处理csv文件之csv.DictWriter()

def csv_dict_write(path,head,data):

    with open(path,'w',encoding='utf-8',newline='') as f:

        writer = csv.DictWriter(f,head)

        writer.writeheader()

        writer.writerows(data)

        return True

调用上面的函数

head = ['Name','Age']

data = [

    {'Name':'Keys', 'Age':28},

    {'Name':'HongPing', 'Age':29},

    {'Name':'WenChao', 'Age':15}

]

csv_dict_write('test2.csv',head,data)

运行结果

4.Python处理csv文件之csv.DictReader()

def csv_dict_read(path):

    with open(path,'r',encoding='utf-8') as f:

        reader = csv.DictReader(f,dialect='excel')

        for row in reader:

            print(row['Name'])

调用上面的函数

csv_dict_read('test2.csv')

运行结果

Keys

HongPing

WenChao