Array with multiple columns formatting-CodePudding

I have multiple arrays and I would like to combine them together so when I call a row, the 1st value of each array is shown. How can I do this?

array1 = ['happy','sad','tired']
array2 = ['oranges', 'apples', 'grapes']
array3 = ['monkeys','elephants','tigers']

array = [array1,array2,array3]

output:['happy','sad','tired'],['oranges','apples','grapes']etc...

wanted output: ['happy','oranges','monkeys'],['sad','apples','elephants']etc...

CodePudding user response：

One way that you could do it is with zip() and list comprehension to add the elements to their own list within the largest list object

output = [[item1,item2,item3] for item1,item2,item3 in zip(array1, array2, array3)]
print(output)

though this assumes that the lists are of equal length.

CodePudding user response：

All you need to do is take the transpose of the array you obtained in line 4.

array1 = ['happy','sad','tired']
array2 = ['oranges', 'apples', 'grapes']
array3 = ['monkeys','elephants','tigers']

array = [array1, array2, array3]
# take the transpose
transpose_array = list(map(lambda x:list(x), zip(*array)))

print(transpose_array)

Here, using zip(*array) simply gives the transpose of the array as a list of tuples. Therefore here I use a lambda function to convert each tuple to a list so that we obtained a list of tuples.

CodePudding user response：

Is there a reason you don't want to use numpy? That would make things very simple.

import numpy as np
array1 = ['happy','sad','tired']
array2 = ['oranges', 'apples', 'grapes']
array3 = ['monkeys','elephants','tigers']

array = np.array([array1,array2,array3]).reshape(3, -1)

Then you can access either rows or columns with indexing:

# column
array[:, 0]
# Out[224]: array(['happy', 'oranges', 'monkeys'], dtype='<U9')

# row
array[0, :]
# Out[224]: array(['happy', 'sad', 'tired'], dtype='<U9')