python - 如何计算条件列中值的频率？

Question

我有一个包含以下数据的 csv 文件:

TaskId | Attr. 1 | Attr. 2 | Attr. 3
123        23     twothree     xyx
123        23     four         lor
456        23     four         pop
123        23     twothree     xyx
352        34     some         lkj

我想根据任务 ID 生成具有属性和频率的字典(甚至只是打印)。

预期输出:

For task id 123, 
23: 3 times

four: 1 times
twothree: 2 times

xyx: 2 times
lor: 1 time

我尝试了以下方法:

import csv
from collections import Counter
from itertools import imap
from operator import  itemgetter

with open('task.csv') as f:
    data = csv.reader(f)
    for row in data:
      if row[0] == '123':
         cn = Counter(imap(itemgetter(2), row))
         for t in cn.iteritems():
             print("{} appears {} times".format(*t))

但是没有用。在

Counter(imap(itemgetter(2), row)) 

我提供了 data 而不是 row 和条件，它正确显示了特定列的项目频率。但我想要它基于一个条件。如何才能做到这一点？

Answer 1

您可以使用 collections.defaultdict 创建嵌套字典:

from io import StringIO
import csv
from collections import defaultdict

mystr = StringIO("""TaskId,Attr. 1,Attr. 2,Attr. 3
123,23,twothree,xyx
123,23,four,lor
456,23,four,pop
123,23,twothree,xyx
352,34,some,lkj""")

d = defaultdict(lambda: defaultdict(int))

# replace mystr with open('file.csv', 'r')
with mystr as fin:
    for item in csv.DictReader(fin):
        d[int(item['TaskId'])][int(item['Attr. 1'])] += 1
        d[int(item['TaskId'])][item['Attr. 2']] += 1
        d[int(item['TaskId'])][item['Attr. 3']] += 1

print(d)

defaultdict({123: defaultdict(int, {23: 3, 'twothree': 2, 'xyx': 2,
                                    'four': 1, 'lor': 1}),
             352: defaultdict(int, {34: 1, 'some': 1, 'lkj': 1}),
             456: defaultdict(int, {23: 1, 'four': 1, 'pop': 1})})

然后像普通字典一样进行迭代:

for k, v in d.items():
    print('TaskId: {0}'.format(k))
    for a, b in v.items():
        print('{0}: {1} times'.format(a, b))

结果:

TaskId: 123
23: 3 times
twothree: 2 times
xyx: 2 times
four: 1 times
lor: 1 times
TaskId: 456
23: 1 times
four: 1 times
pop: 1 times
TaskId: 352
34: 1 times
some: 1 times
lkj: 1 times