Question

我是python的新手，我想知道如何用一个单词对文本文件进行分组。例如，说我的文本文件如下所示：

eggs monday $5 john
bread monday $3 harry
bananas wednesday $2 john
milk saturday $4 sally
tomatoes sunday $7 sally

在我的情况下，我想按名称对文件进行分组。因此，对于约翰来说，我希望它像这样显示：

[john,[eggs,monday],[bananas,wednesday]]

哈利和莎莉等等。

所以现在我的代码看起来像这样，我已经能够确定必要的东西（即名称，项目和日期），但我对如何将其分组感到困惑。

def grocery():
    file = open('shopping.txt')

    wholelist = []
    innerlist = [] 

    for line in file:
        lines = line.split()
        name = lines[3]
        item = lines[0]
        day = lines[1]

提前谢谢你。此外，我仅限于使用列表中的列表，因此我不允许使用词典。

Answer 1

如果您只限制使用列表，则可以尝试这样的操作：

a ="""eggs monday $5 john
bread monday $3 harry
bananas wednesday $2 john
milk saturday $4 sally
tomatoes sunday $7 sally"""

sents = [b.split() for b in a.splitlines()]
names = []
for s in sents:
    if s[3] not in names:
        names.append(s[3])
        names.append([])

for name in names:
    for s in sents:
        if name == s[3]:
            names[names.index(name)+1].append([s[0], s[1]])

for no in range(0,len(names),2):
    print [names[no]] + [a for a in names[no+1]]

输出：

['john', ['eggs', 'monday'], ['bananas', 'wednesday']]
['harry', ['bread', 'monday']]
['sally', ['milk', 'saturday'], ['tomatoes', 'sunday']]

Answer 2

如果不限于使用列表和词典，我建议使用PythoN Data AnalysiS library(pandas)表示具有不同字段类型的表格数据。

它会像这样

import pandas as pd
df = pd.read_table('data.txt', names=['item', 'day', 'price', 'name'], 
                    delim_whitespace=True)
for name, group in df.groupby('name'):
    print name, ':'
    print group[['item','day']]

输出

harry :
    item     day
1  bread  monday
john :
      item        day
0     eggs     monday
2  bananas  wednesday
sally :
       item       day
3      milk  saturday
4  tomatoes    sunday

如果您仅限于使用评论中指明的列表，我会使用.index() list对象的方法：

table = [line.strip().split() for line in lines]  # strip the newline char
table = [row for row in table if len(row) > 0]  # remove empty lines
names = []  # for keeping names
groups = [] # for keeping groups associeated to names

for row in table:
    item, day, price, day = row
    try:
        i = names.index(name)
    except ValueError:
        names.append(name)
        i = len(names) - 1
        groups.append([])
    groups[i].append([item, day])

result = list(zip(names, groups))

Answer 3

试试这个

from collections import defaultdict

def grocery():
    wholelist = defaultdict(list)
    with open('shopping.txt') as file:
        for line in file:
            lines = line.split()
            wholelist[lines[3]].append(lines[0:2])
    return wholelist

custom_list = [[key]+val for key,val in grocery().items()]
print (sorted(custom_list,key=lambda data:data[0]))

custom_list具有您想要的格式

Answer 4

with open('shopping.txt') as file:
    d = defaultdict(list)
    for line in file:

        lines = line.split()
        print(lines)
        name = lines[3]
        item = lines[0]
        day = lines[1]
        d[name].append([item, day])

出：

defaultdict(list,
            {'harry': [['bread', 'monday']],
             'john': [['eggs', 'monday'], ['bananas', 'wednesday']],
             'sally': [['milk', 'saturday'], ['tomatoes', 'sunday']]})

通过Python中的单词对文本文件进行分组（仅限于使用列表）

4 个答案: