Python：如何通过减少行数来优化列表结果？这个问题已经用zip回答了

如何解决Python：如何通过减少行数来优化列表结果？这个问题已经用zip回答了

我有以下列表：

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

I want to convert it to :

[['Azuay','12'],['Bolívar',['Cañar','7'],['Carchi','1'],['Chimborazo','119'],['Cotopaxi','61'],['Esmeraldas','51'],['galápagos',['Guayas',651'],['Imbabura',['Loja','44'],['Manabí',033'],['Napo','2'],['Orellana','17'],['Pastaza','15'],['Pichincha','242'],['Sucumbíos',['Tungurahua','223'],['Zamora Chinchipe','1']]

我正在使用此代码（在下面进行检查）以获得此结果；但是，我想对其进行优化。

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)

解决方法

这是一种常见的模式，itertools recipes中有一个条目。

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)

您将其用作：

result = grouper(rows,4)

,

您可以使用以下简单的list comprehension：

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

输出：

[['Azuay','12'],['Bolívar',['Cañar','7'],['Carchi','1'],['Chimborazo','119'],['Cotopaxi','61'],['El Oro','185'],['Esmeraldas','51'],['Galápagos',['Guayas',651'],['Imbabura',['Loja','44'],['Los Ríos','237'],['Manabí',033'],['Morona Santiago','0'],['Napo','2'],['Orellana','17'],['Pastaza','15'],['Pichincha','242'],['Santa Elena','274'],['Santo Domingo de los Tsáchilas','116'],['Sucumbíos',['Tungurahua','223'],['Zamora Chinchipe','1']]

,

使用numpy

import numpy as np
rows= ['Azuay','1']
r = np.array(rows).reshape(-1,4).tolist()

输出：

[['Azuay','1']]

,

df <- df %>%
   mutate(
     `TE-iL` = case_when(`HB>TE-iL` == 1 ~ 0),`TE-iL^` = case_when(`HB>TE-iL` == 1 ~ 0)
   )