Python: How to optimize a list result by using less lines? This question is already answered using zip

Question

I have the following list:

rows= ['Azuay', '10,658', '195', '12', 'Bolívar', '2,111', '66', '12', 'Cañar', '2,110', '83', '7', 'Carchi', '3,053', '104', '1', 'Chimborazo', '2,516', '315', '119', 'Cotopaxi', '4,575', '281', '61', 'El Oro', '6,477', '466', '185', 'Esmeraldas', '4,271', '216', '51', 'Galápagos', '227', '1', '1', 'Guayas', '22,263', '1,737', '1,651', 'Imbabura', '4,773', '170', '7', 'Loja', '6,227', '222', '44', 'Los Ríos', '4,017', '342', '237', 'Manabí', '11,284', '1,025', '1,033', 'Morona Santiago', '3,008', '22', '0', 'Napo', '1,440', '74', '2', 'Orellana', '1,956', '53', '17', 'Pastaza', '2,258', '60', '15', 'Pichincha', '59,477', '1,789', '242', 'Santa Elena', '1,738', '368', '274', 'Santo Domingo de los Tsáchilas', '5,293', '361', '116', 'Sucumbíos', '2,763', '92', '2', 'Tungurahua', '5,119', '276', '223', 'Zamora Chinchipe', '1,580', '53', '1']

I want to convert it to :

[['Azuay', '10,658', '195', '12'],  ['Bolívar', '2,111', '66', '12'],  ['Cañar', '2,110', '83', '7'],  ['Carchi', '3,053', '104', '1'],  ['Chimborazo', '2,516', '315', '119'],  ['Cotopaxi', '4,575', '281', '61'],  ['Esmeraldas', '4,271', '216', '51'],  ['Galápagos', '227', '1', '1'],  ['Guayas', '22,263', '1,737', '1,651'],  ['Imbabura', '4,773', '170', '7'],  ['Loja', '6,227', '222', '44'],  ['Manabí', '11,284', '1,025', '1,033'],  ['Napo', '1,440', '74', '2'],  ['Orellana', '1,956', '53', '17'],  ['Pastaza', '2,258', '60', '15'],  ['Pichincha', '59,477', '1,789', '242'],  ['Sucumbíos', '2,763', '92', '2'],  ['Tungurahua', '5,119', '276', '223'],  ['Zamora Chinchipe', '1,580', '53', '1']]

I am using this code (check down below) to obtain this result; however, I want to optimize it.

dict_kv=[]
for i in range(0, len(rows)):
  if (rows[i].strip().isalpha()):  
    dict_kv.append([rows[i],rows[i+1],rows[i+2],rows[i+3]])
    
  
dict_kv.append([rows[92],rows[93],rows[94],rows[95]])  s
      
pprint(dict_kv)

Is it always going to be sequence of 4 items in the sub-sequence (and input data)? — DrSpill, Nov 02 '20 at 03:58

score 4 · Answer 1 · answered Nov 02 '20 at 04:00

This is a common-enough pattern that there is an entry in the itertools recipes for it.

def grouper(iterable, n, fillvalue=None):
    "Collect data into fixed-length chunks or blocks"
    # grouper('ABCDEFG', 3, 'x') --> ABC DEF Gxx"
    args = [iter(iterable)] * n
    return zip_longest(*args, fillvalue=fillvalue)

You would use it as:

result = grouper(rows, 4)

score 2 · Accepted Answer · answered Nov 02 '20 at 04:01

You can use this simple list comprehension:

rows= ['Azuay', '10,658', '195', '12', 'Bolívar', '2,111', '66', '12', 'Cañar', '2,110', '83', '7', 'Carchi', '3,053', '104', '1', 'Chimborazo', '2,516', '315', '119', 'Cotopaxi', '4,575', '281', '61', 'El Oro', '6,477', '466', '185', 'Esmeraldas', '4,271', '216', '51', 'Galápagos', '227', '1', '1', 'Guayas', '22,263', '1,737', '1,651', 'Imbabura', '4,773', '170', '7', 'Loja', '6,227', '222', '44', 'Los Ríos', '4,017', '342', '237', 'Manabí', '11,284', '1,025', '1,033', 'Morona Santiago', '3,008', '22', '0', 'Napo', '1,440', '74', '2', 'Orellana', '1,956', '53', '17', 'Pastaza', '2,258', '60', '15', 'Pichincha', '59,477', '1,789', '242', 'Santa Elena', '1,738', '368', '274', 'Santo Domingo de los Tsáchilas', '5,293', '361', '116', 'Sucumbíos', '2,763', '92', '2', 'Tungurahua', '5,119', '276', '223', 'Zamora Chinchipe', '1,580', '53', '1']
rows = [rows[x:x+4] for x in range(0,len(rows),4)]
print(rows)

Output:

[['Azuay', '10,658', '195', '12'], ['Bolívar', '2,111', '66', '12'], ['Cañar', '2,110', '83', '7'], ['Carchi', '3,053', '104', '1'], ['Chimborazo', '2,516', '315', '119'], ['Cotopaxi', '4,575', '281', '61'], ['El Oro', '6,477', '466', '185'], ['Esmeraldas', '4,271', '216', '51'], ['Galápagos', '227', '1', '1'], ['Guayas', '22,263', '1,737', '1,651'], ['Imbabura', '4,773', '170', '7'], ['Loja', '6,227', '222', '44'], ['Los Ríos', '4,017', '342', '237'], ['Manabí', '11,284', '1,025', '1,033'], ['Morona Santiago', '3,008', '22', '0'], ['Napo', '1,440', '74', '2'], ['Orellana', '1,956', '53', '17'], ['Pastaza', '2,258', '60', '15'], ['Pichincha', '59,477', '1,789', '242'], ['Santa Elena', '1,738', '368', '274'], ['Santo Domingo de los Tsáchilas', '5,293', '361', '116'], ['Sucumbíos', '2,763', '92', '2'], ['Tungurahua', '5,119', '276', '223'], ['Zamora Chinchipe', '1,580', '53', '1']]

score 0 · Answer 3 · answered Nov 02 '20 at 04:04

Using numpy

import numpy as np
rows= ['Azuay', '10,658', '195', '12', 'Bolívar', '2,111', '66', '12', 'Cañar', '2,110', '83', '7', 'Carchi', '3,053', '104', '1', 'Chimborazo', '2,516', '315', '119', 'Cotopaxi', '4,575', '281', '61', 'El Oro', '6,477', '466', '185', 'Esmeraldas', '4,271', '216', '51', 'Galápagos', '227', '1', '1', 'Guayas', '22,263', '1,737', '1,651', 'Imbabura', '4,773', '170', '7', 'Loja', '6,227', '222', '44', 'Los Ríos', '4,017', '342', '237', 'Manabí', '11,284', '1,025', '1,033', 'Morona Santiago', '3,008', '22', '0', 'Napo', '1,440', '74', '2', 'Orellana', '1,956', '53', '17', 'Pastaza', '2,258', '60', '15', 'Pichincha', '59,477', '1,789', '242', 'Santa Elena', '1,738', '368', '274', 'Santo Domingo de los Tsáchilas', '5,293', '361', '116', 'Sucumbíos', '2,763', '92', '2', 'Tungurahua', '5,119', '276', '223', 'Zamora Chinchipe', '1,580', '53', '1']
r = np.array(rows).reshape(-1,4).tolist()

Output:

[['Azuay', '10,658', '195', '12'],
 ['Bolívar', '2,111', '66', '12'],
 ['Cañar', '2,110', '83', '7'],
 ['Carchi', '3,053', '104', '1'],
 ['Chimborazo', '2,516', '315', '119'],
 ['Cotopaxi', '4,575', '281', '61'],
 ['El Oro', '6,477', '466', '185'],
 ['Esmeraldas', '4,271', '216', '51'],
 ['Galápagos', '227', '1', '1'],
 ['Guayas', '22,263', '1,737', '1,651'],
 ['Imbabura', '4,773', '170', '7'],
 ['Loja', '6,227', '222', '44'],
 ['Los Ríos', '4,017', '342', '237'],
 ['Manabí', '11,284', '1,025', '1,033'],
 ['Morona Santiago', '3,008', '22', '0'],
 ['Napo', '1,440', '74', '2'],
 ['Orellana', '1,956', '53', '17'],
 ['Pastaza', '2,258', '60', '15'],
 ['Pichincha', '59,477', '1,789', '242'],
 ['Santa Elena', '1,738', '368', '274'],
 ['Santo Domingo de los Tsáchilas', '5,293', '361', '116'],
 ['Sucumbíos', '2,763', '92', '2'],
 ['Tungurahua', '5,119', '276', '223'],
 ['Zamora Chinchipe', '1,580', '53', '1']]

score 0 · Answer 4 · answered Nov 02 '20 at 21:00

0

dict_kv = [list(x) for x in zip(*[iter(rows)]*4)] # to split rows into chunks of 4
    print("The final result of rows, which is renamed to dict_kv, is:")
    pprint(dict_kv)

answered Nov 02 '20 at 21:00

Rox

37
7

I obtained this answer for SoloLearn and it works. Thanks for your answers. I think that all may be work well too. – Rox Nov 02 '20 at 21:03

Python: How to optimize a list result by using less lines? This question is already answered using zip

4 Answers4