使用python将csv文件转换为元组列表

Question

我将采用4列的csv:品牌,价格,重量和类型.

类型有橙色,苹果,梨,李子.

参数:我需要选择最可能的重量,但选择1个橙子,2个梨子,3个苹果和1个李子,不超过20美元的预算.我不能重复相同水果的品牌(比如选择同一品牌的苹果3次等).

我可以通过Python打开并读取csv文件,但我不确定如何从csv文件创建字典或元组列表？

为了更清楚,这里是数据的概念.

Brand, Price, Weight, Type
brand1, 6.05, 3.2, orange
brand2, 8.05, 5.2, orange
brand3, 6.54, 4.2, orange
brand1, 6.05, 3.2, pear
brand2, 7.05, 3.6, pear
brand3, 7.45, 3.9, pear
brand1, 5.45, 2.7, apple
brand2, 6.05, 3.2, apple
brand3, 6.43, 3.5, apple
brand4, 7.05, 3.9, apple
brand1, 8.05, 4.2, plum
brand2, 3.05, 2.2, plum

这就是我现在所拥有的一切:

import csv
test_file = 'testallpos.csv'
csv_file = csv.DictReader(open(test_file, 'rb'), ["brand"], ["price"], ["weight"], ["type"])

Answer 1

你可以考虑一下:

import csv

def fitem(item):
    item=item.strip()
    try:
        item=float(item)
    except ValueError:
        pass
    return item        

with open('/tmp/test.csv', 'r') as csvin:
    reader=csv.DictReader(csvin)
    data={k.strip():[fitem(v)] for k,v in reader.next().items()}
    for line in reader:
        for k,v in line.items():
            k=k.strip()
            data[k].append(fitem(v))

print data 

打印:

{'Price': [6.05, 8.05, 6.54, 6.05, 7.05, 7.45, 5.45, 6.05, 6.43, 7.05, 8.05, 3.05],
 'Type': ['orange', 'orange', 'orange', 'pear', 'pear', 'pear', 'apple', 'apple', 'apple', 'apple', 'plum', 'plum'], 
 'Brand': ['brand1', 'brand2', 'brand3', 'brand1', 'brand2', 'brand3', 'brand1', 'brand2', 'brand3', 'brand4', 'brand1', 'brand2'], 
 'Weight': [3.2, 5.2, 4.2, 3.2, 3.6, 3.9, 2.7, 3.2, 3.5, 3.9, 4.2, 2.2]}

如果你希望csv文件按字面顺序排列:

import csv
with open('/tmp/test.csv') as f:
    data=[tuple(line) for line in csv.reader(f)]

print data
# [('Brand', ' Price', ' Weight', ' Type'), ('brand1', ' 6.05', ' 3.2', ' orange'), ('brand2', ' 8.05', ' 5.2', ' orange'), ('brand3', ' 6.54', ' 4.2', ' orange'), ('brand1', ' 6.05', ' 3.2', ' pear'), ('brand2', ' 7.05', ' 3.6', ' pear'), ('brand3', ' 7.45', ' 3.9', ' pear'), ('brand1', ' 5.45', ' 2.7', ' apple'), ('brand2', ' 6.05', ' 3.2', ' apple'), ('brand3', ' 6.43', ' 3.5', ' apple'), ('brand4', ' 7.05', ' 3.9', ' apple'), ('brand1', ' 8.05', ' 4.2', ' plum'), ('brand2', ' 3.05', ' 2.2', ' plum')]

Answer 2

import csv
with open("some.csv") as f:
       r = csv.reader(f)
       print filter(None,r)

或使用列表理解

import csv
with open("some.csv") as f:
       r = csv.reader(f)
       print [row for row in r if row]

用于比较

In [3]: N = 100000

In [4]: the_list = [randint(0,3) for _ in range(N)]

In [5]: %timeit filter(None,the_list)
1000 loops, best of 3: 1.91 ms per loop

In [6]: %timeit [i for i in the_list if i]
100 loops, best of 3: 4.01 ms per loop

[编辑] 由于您的实际输出没有空格，您不需要列表理解或过滤器，您可以说list(r)

最终答案没有空行

import csv
with open("some.csv") as f:
       print list(csv.reader(f))

如果你想要听写你可以做

import csv
with open("some.csv") as f:
       reader = list(csv.reader(f))
       print [dict(zip(reader[0],x)) for x in reader]
       #or
       print map(lambda x:dict(zip(reader[0],x)), reader)