Extract columns of numpy array consisting of lists

Question

I have a variable var

When I print it in jupyter, it gives:

var

#array([list([9166855000000.0, 13353516.0]),
#       list([7818836000000.0, 11389833.0]),
#       list([20269756000000.0, 29527304.0]),
#       list([66886956000000.0, 97435384.0]),
#       list([58686560000000.0, 85489730.0]),
#       list([50809440000000.0, 74014984.0])], dtype=object)

or

print(var)

[list([9166855000000.0, 13353516.0]) 
 list([7818836000000.0, 11389833.0])
 list([20269756000000.0, 29527304.0])
 list([66886956000000.0, 97435384.0]) 
 list([58686560000000.0, 85489730.0])
 list([50809440000000.0, 74014984.0])]

The type is:

print(type(var))

#<class 'numpy.ndarray'>

How can I devide the second elements of the sublists by the first ones?

I want to get the following values as an array or list:

13353516.0/9166855000000.0
...
74014984.0/50809440000000.0

The 1d object dtype array is effectively a list of lists. If the lists are all the same length you could use np.stack(var) (or vstack) to make a 2d array. Otherwise you'll need to use a list comprehension to iterate through the lists, and select the desired value. — hpaulj
– hpaulj, Commented Dec 10, 2022 at 17:11

isCzech · Accepted Answer · 2022-12-11 19:48:24Z

If I generate the structure like this:

import numpy as np

var = np.empty([6,], dtype=object)

ll = [list([9166855000000.0, 13353516.0]),
       list([7818836000000.0, 11389833.0]),
       list([20269756000000.0, 29527304.0]),
       list([66886956000000.0, 97435384.0]),
       list([58686560000000.0, 85489730.0]),
       list([50809440000000.0, 74014984.0])]

for i, l in enumerate(ll):
    var[i] = l

then var contains a 1D array (of lists)

array([list([9166855000000.0, 13353516.0]),
       list([7818836000000.0, 11389833.0]),
       list([20269756000000.0, 29527304.0]),
       list([66886956000000.0, 97435384.0]),
       list([58686560000000.0, 85489730.0]),
       list([50809440000000.0, 74014984.0])], dtype=object)

and the solution might be:

[var[i][1] / var[i][0] for i in range(len(var))]

returning a list:

[1.4567172710815215e-06,
 1.4567172146851526e-06,
 1.4567172885554222e-06,
 1.456717270853229e-06,
 1.4567173472086283e-06,
 1.4567171769655403e-06]

Or, indeed, a more elegant solution would be using @hpaulj's suggestion and @DmitriChubarov's solution:

var = np.stack(var)

var[:,1] / var[:,0]

returning an array:

array([1.45671727e-06, 1.45671721e-06, 1.45671729e-06, 1.45671727e-06,
       1.45671735e-06, 1.45671718e-06])

Dima Chubarov · Accepted Answer · 2022-12-10 12:14:56Z

0

The solution seems to be rather straightforward

var[:,1] / var[:,0]

would output

array([1.4567172710815215e-06, 1.4567172146851526e-06,
       1.4567172885554222e-06, 1.456717270853229e-06,
       1.4567173472086283e-06, 1.4567171769655403e-06], dtype=object)

To reproduce define var as follows:

import numpy as np
var = np.array([list([9166855000000.0, 13353516.0]),
       list([7818836000000.0, 11389833.0]),
       list([20269756000000.0, 29527304.0]),
       list([66886956000000.0, 97435384.0]),
       list([58686560000000.0, 85489730.0]),
       list([50809440000000.0, 74014984.0])], dtype=object)

answered Dec 10, 2022 at 12:14

Dima Chubarov

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3 Comments

hpaulj Over a year ago

J don't think yiu var duplicates his. His is 1d, your's 2d

len Over a year ago

Hello Dima indeed in your example var is 2d. And when I print your var with print(var) it is different as given in my question:

[[9166855000000.0 13353516.0]  [7818836000000.0 11389833.0]  [20269756000000.0 29527304.0]  [66886956000000.0 97435384.0]  [58686560000000.0 85489730.0]  [50809440000000.0 74014984.0]]

. print(np.shape(var)) is for your var (6, 2) and in my case I get print(np.shape(var)) (6,).

Dima Chubarov Over a year ago

@len could you provide an example that generates a structure of shape (6,) as you are having?

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