CSV数据存取

CSV数据的读取十分地简单

分为两部分

读

读取csv文件可以使用csv模块下的reader(f)以及DictReader(f)

mport csv

with open("text.csv","r") as f:
    f = csv.reader(f)
    for row in f:
        print(row)

结果表示为

['Symbol', 'Price', 'Date', 'Time', 'Change', 'Volume']
['AA', '39.48', '6/11/2007', '9:36am', '-0.18', '181800']
['AIG', '71.38', '6/11/2007', '9:36am', '-0.15', '195500']
['AXP', '62.58', '6/11/2007', '9:36am', '-0.46', '935000']
['BA', '98.31', '6/11/2007', '9:36am', '+0.12', '104800']
['C', '53.08', '6/11/2007', '9:36am', '-0.25', '360900']
['CAT', '78.29', '6/11/2007', '9:36am', '-0.23', '225400']

而使用DictReader()来读取文件方便的一点在于可以使用索引的方式获取信息

import csv

with open("text.csv","r") as f:
    f = csv.DictReader(f)
    for row in f:
        print(row["Symbol"],row["Price"],row["Date"],row["Time"],row["Change"])

其结果边表示为

AA 39.48 6/11/2007 9:36am -0.18
AIG 71.38 6/11/2007 9:36am -0.15
AXP 62.58 6/11/2007 9:36am -0.46
BA 98.31 6/11/2007 9:36am +0.12
C 53.08 6/11/2007 9:36am -0.25
CAT 78.29 6/11/2007 9:36am -0.23

区别：看个人喜好，喜欢哪种用哪种，但是以后应该会接触到根据不同的应用场景选择读取方式的场景。

写

写csv文件的时候需要注意一点

首先要写入csv文件的头部信息

随后再写入尾部信息

分为两种情况

一

headers = ['Symbol','Price','Date','Time','Change','Volume']
rows = [('AA', 39.48, '6/11/2007', '9:36am', -0.18, 181800),
         ('AIG', 71.38, '6/11/2007', '9:36am', -0.15, 195500),
         ('AXP', 62.58, '6/11/2007', '9:36am', -0.46, 935000),
       ]

with open('stocks.csv','w') as f:
    f_csv = csv.writer(f)
    f_csv.writerow(headers)
    f_csv.writerows(rows)

二

当row中时字典时，就可以选择使用DictWriter写入数据

headers = ['Symbol', 'Price', 'Date', 'Time', 'Change', 'Volume']
rows = [{'Symbol':'AA', 'Price':39.48, 'Date':'6/11/2007',
        'Time':'9:36am', 'Change':-0.18, 'Volume':181800},
        {'Symbol':'AIG', 'Price': 71.38, 'Date':'6/11/2007',
        'Time':'9:36am', 'Change':-0.15, 'Volume': 195500},
        {'Symbol':'AXP', 'Price': 62.58, 'Date':'6/11/2007',
        'Time':'9:36am', 'Change':-0.46, 'Volume': 935000},
        ]

with open('stocks.csv','w') as f:
    f_csv = csv.DictWriter(f, headers)
    f_csv.writeheader()
    f_csv.writerows(rows)