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python中csv模块和join函数的使用

时间:2018-02-12 15:24:15      阅读:278      评论:0      收藏:0      [点我收藏+]

标签:span   联合   str   函数   des   写入   波特   blog   旧金山   

在看项目的时候恰好又碰到了这两个功能,然后稍微记录一下,关于join函数,是一个经常使用的联合函数,作用就是用自己规定的字符去串联字符串和列表之类的,对于字符串来说,join函数针对的是字符串中的每一个字符元素,但是对于列表来说就是针对列表中的每一个元素,不过在字典中join只会直接串联key而不是value,所以如果要value的话要自己指定一下。

#!/usr/bin/env python
# -*- coding:utf-8 -*-

sep.join(sep)  #第一个sep是自己想要使用的分隔符,第二个是自己想要操作的对象。
>>>str(sep1)
>>>"[‘%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s‘]"
>>>sep1.__str__()
>>>"[‘%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s‘]"
>>>‘‘.join(sep1)
>>>‘%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s
>>>‘‘.join(%s * 10)
>>>‘%s%s%s%s%s%s%s%s%s%s
>>>‘,.join(%s * 10)
>>>‘%,s,%,s,%,s,%,s,%,s,%,s,%,s,%,s,%,s,%,s

关于csv模块,我用的比较多的是利用csv将本地文件导入到数据库当中,所以基本上都是读文件:第一种是使用reader,第二种是使用DictReader

data = csv.reader(open(rC:\Users\欧阳\Desktop\csv专用\test.csv, encoding=utf-8))
rows = [row for row in data]
rows
[[\ufeff179, 阿尔布开克, city0000179, 103, 2, ‘‘, ‘‘, ‘‘, ‘‘], [180, 安克雷奇, city0000180, 105, 2, ‘‘, ‘‘, ‘‘, ‘‘], [181, 亚特兰大, city0000181, 145, 2, ‘‘, ‘‘, ‘‘, ‘‘], [182, 比林斯, city0000182, 127, 2, ‘‘, ‘‘, ‘‘, ‘‘], [183, 波士顿南, city0000183, 102, 2, ‘‘, ‘‘, ‘‘, ‘‘], [184, 波士顿-北, city0000184, 102, 2, ‘‘, ‘‘, ‘‘, ‘‘], [185, 芝加哥, city0000185, 111, 2, ‘‘, ‘‘, ‘‘, ‘‘], [186, 丹佛, city0000186, 125, 2, ‘‘, ‘‘, ‘‘, ‘‘], [187, 西雅图, city0000187, 134, 2, ‘‘, ‘‘, ‘‘, ‘‘], [188, 莱克海瓦萨, city0000188, 147, 2, ‘‘, ‘‘, ‘‘, ‘‘], [189, 迈阿密, city0000189, 140, 2, ‘‘, ‘‘, ‘‘, ‘‘], [190, 休斯顿, city0000190, 114, 2, ‘‘, ‘‘, ‘‘, ‘‘], [191, 马纳萨斯, city0000191, 129, 2, ‘‘, ‘‘, ‘‘, ‘‘], [192, 拉斯维加斯, city0000192, 129, 2, ‘‘, ‘‘, ‘‘, ‘‘], [193, 洛杉矶, city0000193, 120, 2, ‘‘, ‘‘, ‘‘, ‘‘], [194, 迈阿密南部, city0000194, 140, 2, ‘‘, ‘‘, ‘‘, ‘‘], [195, 明尼阿波利斯, city0000195, 112, 2, ‘‘, ‘‘, ‘‘, ‘‘], [196, 纽约, city0000196, 108, 2, ‘‘, ‘‘, ‘‘, ‘‘], [197, 奥兰多, city0000197, 140, 2, ‘‘, ‘‘, ‘‘, ‘‘], [198, 费城, city0000198, 138, 2, ‘‘, ‘‘, ‘‘, ‘‘], [199, 凤凰城, city0000199, 110, 2, ‘‘, ‘‘, ‘‘, ‘‘], [200, 波特兰, city0000200, 133, 2, ‘‘, ‘‘, ‘‘, ‘‘], [201, 盐湖城, city0000201, 119, 2, ‘‘, ‘‘, ‘‘, ‘‘], [202, 旧金山, city0000202, 120, 2, ‘‘, ‘‘, ‘‘, ‘‘], [203, 圣地亚哥, city0000203, 120, 2, ‘‘, ‘‘, ‘‘, ‘‘], [204, 坦帕, city0000204, 140, 2, ‘‘, ‘‘, ‘‘, ‘‘], [205, 卡尔加里, city0000205, 150, 4, ‘‘, ‘‘, ‘‘, ‘‘], [206, 哈利法克斯, city0000206, 151, 4, ‘‘, ‘‘, ‘‘, ‘‘], [207, 蒙特利尔, city0000207, 152, 4, ‘‘, ‘‘, ‘‘, ‘‘], [208, 多伦多, city0000208, 153, 4, ‘‘, ‘‘, ‘‘, ‘‘], [209, 温哥华, city0000209, 154, 4, ‘‘, ‘‘, ‘‘, ‘‘], [210, 达拉斯, city0000210, 114, 2, ‘‘, ‘‘, ‘‘, ‘‘], [211, 贝灵汉, city0000211, 134, 2, ‘‘, ‘‘, ‘‘, ‘‘]]

 

reader = csv.DictReader(open(rC:\Users\欧阳\Desktop\csv专用\test.csv, encoding=utf-8))
column = [row for row in reader]
column
[OrderedDict([(\ufeff179, 180), (阿尔布开克, 安克雷奇), (city0000179, city0000180), (103, 105), (2, 2), (‘‘, ‘‘)]), OrderedDict([(\ufeff179, 181), (阿尔布开克, 亚特兰大), (city0000179, city0000181), (103, 145), (2, 2), (‘‘, ‘‘)]), OrderedDict([(\ufeff179, 182), (阿尔布开克, 比林斯), (city0000179, city0000182), (103, 127), (2, 2), (‘‘, ‘‘)]), OrderedDict([(\ufeff179, 183), (阿尔布开克, 波士顿南), (city0000179, city0000183), (103, 102), (2, 2), (‘‘, ‘‘)]), OrderedDict([(\ufeff179, 184), (阿尔布开克, 波士顿-北), (city0000179, city0000184), (103, 102), (2, 2), (‘‘, ‘‘)]), OrderedDict([(\ufeff179, 185), (阿尔布开克, 芝加哥), (city0000179, city0000185), (103, 111), (2, 2), (‘‘, ‘‘)]), OrderedDict([(\ufeff179, 186), (阿尔布开克, 丹佛), (city0000179, city0000186), (103, 125), (2, 2), (‘‘, ‘‘)]), OrderedDict([(\ufeff179, 187), (阿尔布开克, 西雅图), (city0000179, city0000187), (103, 134), (2, 2), (‘‘, ‘‘)]), OrderedDict([(\ufeff179, 188), (阿尔布开克, 莱克海瓦萨), (city0000179, city0000188), (103, 147), (2, 2), (‘‘, ‘‘)]), OrderedDict([(\ufeff179, 189), (阿尔布开克, 迈阿密), (city0000179, city0000189), (103, 140), (2, 2), (‘‘, ‘‘)]), OrderedDict([(\ufeff179, 190), (阿尔布开克, 休斯顿), (city0000179, city0000190), (103, 114), (2, 2), (‘‘, ‘‘)]), OrderedDict([(\ufeff179, 191), (阿尔布开克, 马纳萨斯), (city0000179, city0000191), (103, 129), (2, 2), (‘‘, ‘‘)]), OrderedDict([(\ufeff179, 192), (阿尔布开克, 拉斯维加斯), (city0000179, city0000192), (103, 129), (2, 2), (‘‘, ‘‘)]), OrderedDict([(\ufeff179, 193), (阿尔布开克, 洛杉矶), (city0000179, city0000193), (103, 120), (2, 2), (‘‘, ‘‘)]), OrderedDict([(\ufeff179, 194), (阿尔布开克, 迈阿密南部), (city0000179, city0000194), (103, 140), (2, 2), (‘‘, ‘‘)]), OrderedDict([(\ufeff179, 195), (阿尔布开克, 明尼阿波利斯), (city0000179, city0000195), (103, 112), (2, 2), (‘‘, ‘‘)]), OrderedDict([(\ufeff179, 196), (阿尔布开克, 纽约), (city0000179, city0000196), (103, 108), (2, 2), (‘‘, ‘‘)]), OrderedDict([(\ufeff179, 197), (阿尔布开克, 奥兰多), (city0000179, city0000197), (103, 140), (2, 2), (‘‘, ‘‘)]), OrderedDict([(\ufeff179, 198), (阿尔布开克, 费城), (city0000179, city0000198), (103, 138), (2, 2), (‘‘, ‘‘)]), OrderedDict([(\ufeff179, 199), (阿尔布开克, 凤凰城), (city0000179, city0000199), (103, 110), (2, 2), (‘‘, ‘‘)]), OrderedDict([(\ufeff179, 200), (阿尔布开克, 波特兰), (city0000179, city0000200), (103, 133), (2, 2), (‘‘, ‘‘)]), OrderedDict([(\ufeff179, 201), (阿尔布开克, 盐湖城), (city0000179, city0000201), (103, 119), (2, 2), (‘‘, ‘‘)]), OrderedDict([(\ufeff179, 202), (阿尔布开克, 旧金山), (city0000179, city0000202), (103, 120), (2, 2), (‘‘, ‘‘)]), OrderedDict([(\ufeff179, 203), (阿尔布开克, 圣地亚哥), (city0000179, city0000203), (103, 120), (2, 2), (‘‘, ‘‘)]), OrderedDict([(\ufeff179, 204), (阿尔布开克, 坦帕), (city0000179, city0000204), (103, 140), (2, 2), (‘‘, ‘‘)]), OrderedDict([(\ufeff179, 205), (阿尔布开克, 卡尔加里), (city0000179, city0000205), (103, 150), (2, 4), (‘‘, ‘‘)]), OrderedDict([(\ufeff179, 206), (阿尔布开克, 哈利法克斯), (city0000179, city0000206), (103, 151), (2, 4), (‘‘, ‘‘)]), OrderedDict([(\ufeff179, 207), (阿尔布开克, 蒙特利尔), (city0000179, city0000207), (103, 152), (2, 4), (‘‘, ‘‘)]), OrderedDict([(\ufeff179, 208), (阿尔布开克, 多伦多), (city0000179, city0000208), (103, 153), (2, 4), (‘‘, ‘‘)]), OrderedDict([(\ufeff179, 209), (阿尔布开克, 温哥华), (city0000179, city0000209), (103, 154), (2, 4), (‘‘, ‘‘)]), OrderedDict([(\ufeff179, 210), (阿尔布开克, 达拉斯), (city0000179, city0000210), (103, 114), (2, 2), (‘‘, ‘‘)]), OrderedDict([(\ufeff179, 211), (阿尔布开克, 贝灵汉), (city0000179, city0000211), (103, 134), (2, 2), (‘‘, ‘‘)])]

写和读也差不多,三个步骤,显示打开文件,然后调用csv的writer方法,然后把数据写进去就可以了。

datas = [[name, age], [Bob, 14], [Tom, 23], [Jerry, 18]]
with open(test.csv, w, newline=‘‘) as f:
    writer = csv.writer(f)
    for row in datas:
        writer.writerow(row)
        #还可使用writerrows写入多行
        

 

python中csv模块和join函数的使用

标签:span   联合   str   函数   des   写入   波特   blog   旧金山   

原文地址:https://www.cnblogs.com/zzy0306/p/8444403.html

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