和值蟒蛇

Question

我有一个列表：

l = [['a', 10, 30], ['b', 34, 89], ['c', 40, 60],['d',30,20]] 

其中每个子列表中的第一个产品的名称和另外两个号码都标记（SUB1和SUB2）

嵌套表可以是动态的，即嵌套列表的数量可以根据功能而改变。

我所寻找的是找到

average of subj 1 i.e (10+34+40+30)/4 and 
similarly sub2 (30+89+60+20)/4 

also average marks of a: (10+30)/2 
average marks of b: (34+89)/2 and so on. 

我想：

c = 0 
for i in range(0,len(list_marks1)): 
    c += list_marks1[i][1] 
sub_1avg = float(c)/len(list_marks1) 
d = 0 
for i in range(0,len(list_marks1)): 
    d += list_marks1[i][2] 
sub_2avg = float(d)/len(list_marks1) 

，但这是不正确的。

有没有最佳的方法来做到这一点？由于我的嵌套列表中的主题数量也可以改变。

Answer 1

你可以只使用sum和发电机的表达：

>>> l= [['a', 10, 30], ['b', 34, 89], ['c', 40, 60],['d',30,20]] 
>>> length = float(len(l)) # in Python 3 you don't need the "float" 
>>> sum(subl[1] for subl in l)/length 
28.5 
>>> sum(subl[2] for subl in l)/length 
49.75 

甚至做一个列表解析里：

>>> [sum(subl[subj] for subl in l)/length for subj in range(1, 3)] 
[28.5, 49.75] 

同样，对于平均一个子列表：

>>> length = float(len(l[0])) - 1 
>>> [sum(subl[1:])/length for subl in l] 
[20.0, 61.5, 50.0, 25.0] 

当你有python 3.4或更新版本时，你可以替换sum/length与statistics.mean：

>>> from statistics import mean 
>>> [mean(subl[subj] for subl in l) for subj in range(1, 3)] 
[28.5, 49.75] 

>>> [mean(subl[1:]) for subl in l] 
[20, 61.5, 50, 25] 

---

你问到的最好办法，所以我也许应该提到，有专用表格数据包。例如，如果您有pandas它使用DataFrame和mean更简单：

>>> import pandas as pd 

>>> df = pd.DataFrame(l, columns=['name', 'x', 'y']) 
>>> df[['x', 'y']].mean(axis=0) 
x 28.50 
y 49.75 
dtype: float64 

>>> df[['x', 'y']].mean(axis=1) 
0 20.0 
1 61.5 
2 50.0 
3 25.0 
dtype: float64 

Answer 2

一个fucnitonal方法：

l= [['a', 10, 30], ['b', 34, 89], ['c', 40, 60],['d',30,20]] 
map(lambda x: sum(x)/float(len(x)), zip(*l)[1:]) 
[28.5, 49.75] 

这种方式适用于任何子列表长度

Answer 3

l= [['a', 10, 30], ['b', 34, 89], ['c', 40, 60],['d',30,20]] 
sub1_avg = sum(n for _,n, _ in l)/float(len(l)) 
sub2_avg = sum(n for _,_, n in l)/float(len(l)) 
student_avgs = [{x[0]: sum(x[1:])//float((len(x)-1))} for x in l] 
print "Sub1 avg - {}\nSub2 avg - {}\nstudent avg - {}".format(sub1_avg, sub2_avg, student_avgs) 

样本输出工作

Sub1 avg - 28.5 
Sub2 avg - 49.75 
student avg - [{'a': 20.0}, {'b': 61.0}, {'c': 50.0}, {'d': 25.0}]