在列表中組合兩個字符串

Question

['2016-01-01 00:00:00', '0',
 '2016-01-01 08:00:00', '268705.0',
 '2016-01-01 16:00:00', '0',
 '2016-01-02 00:00:00', '0',
 '2016-01-02 08:00:00', '0.0',
 '2016-01-02 16:00:00', '0.0',
 '2016-01-03 00:00:00' ...
 ... etc for 1 year]

我基本上把日期和能量生產作為一個int之后。 我想讓它看起來像

['2016-01-01 00:00:00;0',
 '2016-01-01 08:00:00;268705.0',
 ... etc]

又名['date;energy']

有小費嗎？ 我是新手，需要這個來完成我的課程......

Answer 1

使用zip（）和list-slicing從索引0開始壓縮每個第2個元素，每個第2個元素從索引1開始：

data = ['2016-01-01 00:00:00', '0',
        '2016-01-01 08:00:00', '268705.0',
        '2016-01-01 16:00:00', '0',
        '2016-01-02 00:00:00', '0',
        '2016-01-02 08:00:00', '0.0',
        '2016-01-02 16:00:00', '0.0',
        '2016-01-03 00:00:00', "18.05",]

new_data = list(zip(data[0::2],data[1::2]))

print(new_data)

combined = ["{};{}".format(a,b) for a,b in new_data]

print(combined)

輸出：

# new_data (I would vouch to use that further on)
[('2016-01-01 00:00:00', '0'), ('2016-01-01 08:00:00', '268705.0'), 
 ('2016-01-01 16:00:00', '0'), ('2016-01-02 00:00:00', '0'), 
 ('2016-01-02 08:00:00', '0.0'), ('2016-01-02 16:00:00', '0.0'), 
 ('2016-01-03 00:00:00', '18.05')]

# combined
['2016-01-01 00:00:00;0', '2016-01-01 08:00:00;268705.0', '2016-01-01 16:00:00;0',
 '2016-01-02 00:00:00;0', '2016-01-02 08:00:00;0.0', '2016-01-02 16:00:00;0.0', 
 '2016-01-03 00:00:00;18.05']

---

如果我是你，我不會將它們組合在一起，而是使用元組進一步工作。 Fe如果你想每天總結能量：

new_data = sorted((zip(data[0::2],data[1::2])))

from itertools import groupby 

# x[0][0:10] uses the 1st element of each tuple (the datetime) and slices only the date
# from it. That is used to group all data.
k = groupby(new_data, lambda x:x[0][0:10])

summs = []
for date,tups in k:
    summs.append( (date,sum(float(x[1]) for x in tups)) )

print(summs)

輸出：

[('2016-01-01', 268705.0), ('2016-01-02', 0.0), ('2016-01-03', 18.05)]

Answer 2

用一個zip來生成所需值的壓縮列表，然后用join了加入列表;

>>> a=['2016-01-01 00:00:00', '0', '2016-01-01 08:00:00', '268705.0', '2016-01-01 16:00:00', '0']
>>> [';'.join(i) for i in zip(a[::2],a[1::2])]
['2016-01-01 00:00:00;0', '2016-01-01 08:00:00;268705.0', '2016-01-01 16:00:00;0']
>>>