# -*- coding: utf-8 -*-
import csv
with open('E:/iris.csv') as csvfile:
reader = csv.DictReader(csvfile, fieldnames=None) # fieldnames默认为None,如果所读csv文件没有表头，则需要指定
list_1 = [e for e in reader] # 每行数据作为一个dict存入链表中
csvfile.close()
print list_1[0]

 list_1 = list()
for e in reader:
 list_1.append(your_func(e)) # your_func为每条数据的处理函数 

 # 数据
data = [
{'Petal.Length': '1.4', 'Sepal.Length': '5.1', 'Petal.Width': '0.2', 'Sepal.Width': '3.5', 'Species': 'setosa'},
{'Petal.Length': '1.4', 'Sepal.Length': '4.9', 'Petal.Width': '0.2', 'Sepal.Width': '3', 'Species': 'setosa'},
{'Petal.Length': '1.3', 'Sepal.Length': '4.7', 'Petal.Width': '0.2', 'Sepal.Width': '3.2', 'Species': 'setosa'},
{'Petal.Length': '1.5', 'Sepal.Length': '4.6', 'Petal.Width': '0.2', 'Sepal.Width': '3.1', 'Species': 'setosa'}
]
# 表头
header = ['Petal.Length', 'Sepal.Length', 'Petal.Width', 'Sepal.Width', 'Species']
print len(data)
with open('E:/dst.csv', 'wb') as dstfile: #写入方式选择wb，否则有空行
 writer = csv.DictWriter(dstfile, fieldnames=header)
 writer.writeheader() # 写入表头
 writer.writerows(data) # 批量写入
dstfile.close()

 # 读取csv文件为DataFrame
import pandas as pd
dframe = pd.DataFrame.from_csv('E:/iris.csv')

import csv
import pandas as pd
with open('E:/iris.csv') as csvfile:
 reader = csv.DictReader(csvfile, fieldnames=None) # fieldnames默认为None,如果所读csv文件没有表头，则需要指定
 list_1 = [e for e in reader] # 每行数据作为一个dict存入链表中
csvfile.close()
dfrme = pd.DataFrame.from_records(list_1) 

import pandas as pd
import zipfile
z_file = zipfile.ZipFile('E:/dst.zip')
dframe = pd.read_csv(z_file.open('dst.csv'))
z_file.close()
print dframe 

dfrme.to_csv('E:/dst.csv', index=False) # 不要每行的编号 

import pandas as pd
# `path`为文件路径或文件句柄，`header`文件第一行是否是表头，`delimiter`每个字段的分隔符，`dtype`数据读入后的存储类型。
frame = pd.read_table(path, header=None, index_col=False, delimiter='\t', dtype=str)