转换并求和 pandas 数据框列内嵌套列表中的元素

Question

我有一个像这样的 df 列：col1[[0.73, 0.43, 0.5, 0.0], [0.39, 0.5], [0.37], [0.38, 0.51, 0.0, 0.2]][[0.53, 0.33, 0.2, 0.0], [0.79, 0.5], [0.96], [0.88, 0.21, 0.0, 0.0]]子列表可以是任意大小。我试图将子列表中的数字转换为浮点数（它们是字符串），然后创建一个对每个子列表求和的列，然后除以子列表中的项目数所以第 1 行的总和：(.73 + .43 + .5 + 0) / 4 =.415(.39 + .5) / 2 = .445(.37) / 1 = .37(.38 + .51 + 0.0 + .2) / 4 = .272对于第 2 行：(.53 + .33 + .2 + 0) / 4 = .265(.79 + .5) / 2 = .645(.96) / 1 = .96(.88 + .21 + 0.0 + 0.0) / 4 = .272结果：new_col[[.415],[.445],[.37],[.272]][[.265],[.645],[.96],[.272]]我尝试过很多东西：#something like this where it creates a column of the number of elements in each sublist and then uses that to divide the sum of each number# this didn't work - just grabbed the first lists sizedf1['words_in_company_name'] = df1['children_org_name_sublists'].str.len()#this doesn't really work - i mean it shows the numbers per list, just not sure where to go from herefor i in df1.func_scores:    length = []    for j in i:        print(j)A

Answer 1

只要做apply与np.mean

df['new_col'] = df.col.apply(lambda x : [[np.mean(y)] for y in x ])

df

Out[17]: 

                                                 col                               new_col

0  [[0.73, 0.43, 0.5, 0.0], [0.39, 0.5], [0.37], ...  [[0.415], [0.445], [0.37], [0.2725]]

1  [[0.53, 0.33, 0.2, 0.0], [0.79, 0.5], [0.96], ...  [[0.265], [0.645], [0.96], [0.2725]]