csv文件 读取保存操作

官方文档：https://docs.python.org/3/library/csv.html

写入

# -*- encoding: utf-8 -*-

import csv
from io import StringIO
from urllib import urlopen

# 按行元组参数写入
def writerCsv1(): f = open("data.csv", "w") writer = csv.writer(f) for i in range(100): writer.writerow((i+1, i+2, i+3)) f.close()

# 按行字典参数写入
def writerCsv2(): f = open("data.csv", "w") writer = csv.DictWriter(f, ["name", "age"]) for i in range(100): dct = {"name":i+1, "age": i+2} writer.writerow(dct) f.close() print("写入成功！")

writerCsv2()
  
 

  
1
  
2
  
3
  
4
  
5
  
6
  
7
  
8
  
9
  
10
  
11
  
12
  
13
  
14
  
15
  
16
  
17
  
18
  
19
  
20
  
21
  
22
  
23
  
24
  
25
 

读取

要读取的文件

# MontyPythonAlbums.csv

Name,Year
Monty Python's Flying Circus,1970
Another Monty Python Record,1971
Monty Python's Previous Record,1972
  
 

  
1
  
2
  
3
  
4
  
5
  
6
 

# 按行读取列表
def readerCsv1(): # 读取网络文件 # url = "http://www.pythonscraping.com/files/MontyPythonAlbums.csv" # data = urlopen(url).read() # 读取本地文件 data = open("MontyPythonAlbums.csv", "r").read().decode('utf-8') print type(data) data_file = StringIO(data) # 字符串转为io对象 csv_reader = csv.reader(data_file) for row in csv_reader: print(row) """ ['Name', 'Year'] ["Monty Python's Flying Circus", '1970'] """

# readerCsv1()

# 按行读取列表
def readerCsv2(): f = open("MontyPythonAlbums.csv", "r") csv_reader = csv.reader(f) for row in csv_reader: print(row) """ ['Name', 'Year'] ["Monty Python's Flying Circus", '1970'] """ f.close()

# readerCsv2()

# 按行读取字典，第一行为key
def readerCsv3(): f = open("MontyPythonAlbums.csv", "r") csv_reader = csv.DictReader(f) for row in csv_reader: print(row) # {'Name': "Monty Python's Flying Circus", 'Year': '1970'} f.close()

# readerCsv3()
  
 

  
1
  
2
  
3
  
4
  
5
  
6
  
7
  
8
  
9
  
10
  
11
  
12
  
13
  
14
  
15
  
16
  
17
  
18
  
19
  
20
  
21
  
22
  
23
  
24
  
25
  
26
  
27
  
28
  
29
  
30
  
31
  
32
  
33
  
34
  
35
  
36
  
37
  
38
  
39
  
40
  
41
  
42
  
43
  
44
  
45
 

文章来源: pengshiyu.blog.csdn.net，作者：彭世瑜，版权归原作者所有，如需转载，请联系作者。

原文链接：pengshiyu.blog.csdn.net/article/details/79917825