如何将 function 应用于列表列表中的列表元素？

Question

I have a list of lists. Here is an example of 2 of the lists inside a list:

global_tp_old = [[2, 1, 0.8333595991134644],[2, 1, 0.8530714511871338]]

I want to access a dataframe index where the index is specified in the first element of the above list in a list. At the moment I have tried:

global_tp_new = []
for element in global_tp_old:
   element[:][0] = df_unique[element[:][0]]
   global_tp_new.append(element)

where df_unique is a pandas dataframe produced like this:

['img1.png', 'img2.png', 'img3.png']

I'm trying to match the first element from the list defined above to the number in df_unique .

I should get:

'img3.png'

as it's the 3rd element (0 indexing)

However, I get the incorrect output where it essentially returns the first element every time. It's probably obvious but what do I do to fix this?

Answer 1

List comprehension might be useful to apply a function fun to the first element of each list in a list of lists ( LoL ).

LoL  = [[61, 1, 0.8333595991134644],[44, 1, 0.8530714511871338]]

newL = [fun(l_loc[0]) for l_loc in LoL]

No need to use a Pandas DataFrame.

Answer 2

Remember that your element array is actually a reference into the original list. If you modify the list, you'll modify global_tp_old as well.

Something like this, although you may need to change the dataframe indexing depending on whether you're looking for rows or columns.

global_tp_old = [[2, 1, 0.8333595991134644],[2, 1, 0.8530714511871338]]

global_tp_new = []
for element in global_tp_old:
   element = [df_unique.iloc[element[0]]] + element[1:]
   global_tp_new.append(element)