6-1 如何读写csv数据

>>> from urllib import urlretrieve
>>> urlretrieve('http://table.finance.yahoo.com/table.csv?s=000001.sz',r'C:\视频\python高效实践技巧笔记\6数据编码与处理相关话题\pingan.csv',’pingan.csv’)

Urlretrieve模块第一个参数是url，第二个参数是要将打开的文件保存的文件。

对CSV文件读写使用CSV接口的reader()和writer()函数

因这个网址已经打不开了，所以在网上下载一个CSV文件直接操作

一、打开并读一个csv文件

>>> help(csv.reader)
Help on built-in function reader in module _csv:

reader(...)
    csv_reader = reader(iterable [, dialect='excel']
                            [optional keyword args])
        for row in csv_reader:
            process(row)

    The "iterable" argument can be any object that returns a line
    of input for each iteration, such as a file object or a list.  The
    optional "dialect" parameter is discussed below.  The function
    also accepts optional keyword arguments which override settings
    provided by the dialect.

    The returned object is an iterator.  Each iteration returns a row
of the CSV file (which can span multiple input lines).

help(csv.reader)

参数是一个打开文件的文件对象，返回的是一个迭代器。

>>> import csv
>>>
>>> rf = open(r"C:\视频\python高效实践技巧笔记\6数据编码与处理相关话题\bank-data.csv",'rb')     #注意打开csv文件需要使用二进制打开方式
>>> reader = csv.reader(rf)
>>> reader.next()       #csv.reader()返回的是迭代器，查看需要使用next()方法
['id', 'age', 'sex', 'region', 'income', 'married', 'children', 'car', 'save_act', 'current_act', 'mortgage', 'pep']
>>> reader.next()
['ID12101', '', 'FEMALE', 'INNER_CITY', '17546.0', 'NO', '', 'NO', 'NO', 'NO', 'NO', 'YES']

查看reader()返回迭代对象的方法

>>> help(reader)
Help on reader object:

class reader(__builtin__.object)
 |  CSV reader
 |
 |  Reader objects are responsible for reading and parsing tabular data
 |  in CSV format.
 |
 |  Methods defined here:
 |
 |  __iter__(...)
 |      x.__iter__() <==> iter(x)
 |
 |  next(...)
 |      x.next() -> the next value, or raise StopIteration
 |
 |  ----------------------------------------------------------------------
 |  Data descriptors defined here:
 |
 |  dialect
 |
 |  line_num

help(reader)

二、打开并写一个文件

>>> writer = csv.writer(wf)

>>> help(csv.writer)
Help on built-in function writer in module _csv:

writer(...)
    csv_writer = csv.writer(fileobj [, dialect='excel']
                                [optional keyword args])
        for row in sequence:
            csv_writer.writerow(row)

        [or]

        csv_writer = csv.writer(fileobj [, dialect='excel']
                                [optional keyword args])
        csv_writer.writerows(rows)

    The "fileobj" argument can be any object that supports the file API.

help(csv.writer)

同reader()一样，参数是一个打开文件的对象，返回值是一个迭代器，打开文件的方式 需要使用二进制方式

>>> wf = open(r'C:\视频\python高效实践技巧笔记\6数据编码与处理相关话题\bank-databak.csv','wb')
>>> writer = csv.writer(wf)
>>> writer.writerow(['id', 'age', 'sex', 'region', 'income', 'married', 'children', 'car', 'save_act', 'current_act', 'mortgage', 'pep'])
>>> writer.writerow(reader.next())
>>> writer.writerow(reader.next())
>>> wf.flush()         #和c语言的flush()作用相同，及时将文件缓冲区内容输出到文件上。

查看writer()返回的迭代器的方法主要是writerow()写行

>>> help(writer)
Help on writer object:

class writer(__builtin__.object)
 |  CSV writer
 |
 |  Writer objects are responsible for generating tabular data
 |  in CSV format from sequence input.
 |
 |  Methods defined here:
 |
 |  writerow(...)
 |      writerow(sequence)
 |
 |      Construct and write a CSV record from a sequence of fields.  Non-string
 |      elements will be converted to string.
 |
 |  writerows(...)
 |      writerows(sequence of sequences)
 |
 |      Construct and write a series of sequences to a csv file.  Non-string
 |      elements will be converted to string.
 |
 |  ----------------------------------------------------------------------
 |  Data descriptors defined here:
 |
 |  dialect

help(writer)

Bank-data.csv是一份收入情况,现编写脚本,将文件中年龄在30-40之间,收入大于10000的另存到一个bank-databak.csv文件中.现编写脚本如下:

# -*- coding: cp936 -*-
import csv
with open(r'C:\视频\python高效实践技巧笔记\6数据编码与处理相关话题\bank-data.csv','rb') as rf:
    reader = csv.reader(rf)
    with open(r'C:\视频\python高效实践技巧笔记\6数据编码与处理相关话题\bank-databak.csv','wb') as wf:
        writer = csv.writer(wf)
        header = reader.next()    #将文件的头读出
        writer.writerow(header)   #将文件的头写入文件

        for row in reader:        #迭代执行判断,文件中第一个字段代表age第4个字段代表收入
#文件中读出的是字符,所以在比较时要将字符转成int或float.
#python中判断数字区间可以用数学中的表达方式,与C语言不同.
            if (30< int(row[1])<40 and float(row[4])>10000.0):
                writer.writerow(row)   #将合适的数据写入新的csv文件中
print("end")

结果:

Ps:

注意字符串日期的比较的大小比较也可以使用如下红框的方式，、