str 仅给出一个元素作为输出，但对象解决了问题

Question

我必须编写一个Python代码，有一个函数，它接收一个元组作为参数，其中元组的所有元素都是numpy数组。该代码的输出将为我提供来自该元组的独特爱好。但是如果我使用 dtype = str 来创建一个新数组，它只需要元素的第一个字母，但如果我使用 dtype = object 那么它可以解决问题

def analyzeHobbies(* participants): #(* arguments) is used for variable number of parameters
  length = len(participants)
  total = 0
  for i in range(length):
    total = total+ len(participants[i])
  new = np.zeros (total, dtype = object)
  count = 0
  for j in range(length):
    for k in range(len(participants[j])):
      
      new[count] = participants[j][k]
      count += 1
  unique1 = np.zeros (total, dtype = object)
  unique1[0] = new[0]
  for h in range(1,total):
    if new[h] not in unique1:
      unique1[h] = new[h]
    else:
         unique1[h] = "0"

  count = 0
  for l in range(len(unique1)):
   if unique1[l]!= "0":
    count = count+1
  
  final = np.zeros (count, dtype = object)
  index = 0 
  for m in range(len(unique1)):
    if unique1[m] != "0":
      final[index] = unique1[m] 
      index = index+1

  print(f"""Unique Activities in the Town:
{final}""") 
  print("Statistics:")
  for n in range(count):
    count1 = 0  
    for o in range(len(new)):
      if final[n] == new[o]:
        count1 = count1+1
    print(f"{count1}participant(s) like(s){final[n]} ")

print("///  Task 04: Get Those Hobbies  ///")
participant_1 = np.array( ["Hiking", "Reading", "Photography", "Cooking"])
participant_2 = np.array( ["Reading", "Hiking", "Painting"])
participant_3 = np.array( ["Hiking", "Cooking", "Photography"])
print(f'Task 4:')
analyzeHobbies(participant_1, participant_2, participant_3) #

这应该打印出来

Unique Activities in the Town:
['Photography', 'Painting', 'Cooking', 'Reading', 'Hiking']

Statistics:
2 participant(s) like(s) Photography.
1 participant(s) like(s) Painting.
2 participant(s) like(s) Cooking.
2 participant(s) like(s) Reading.
3 participant(s) like(s) Hiking.

我就是这样做的。不使用对象可以解决这个问题吗？

Answer 1

处理此问题的最佳方法是跳过 numpy 并使用

collections.Counter

，它正是针对这种情况创建的。

import collections
import numpy as np

def analyzeHobbies(* participants):
    unique = collections.Counter()
    for p in participants:
        unique.update(p)

    print("Unique Activities in the Town:")
    print(list(unique.keys())) 
    print("Statistics:")
    for k,v in unique.items():
        print(f"{v} participant(s) like(s) {k}")

print("///  Task 04: Get Those Hobbies  ///")
participant_1 = np.array( ["Hiking", "Reading", "Photography", "Cooking"])
participant_2 = np.array( ["Reading", "Hiking", "Painting"])
participant_3 = np.array( ["Hiking", "Cooking", "Photography"])
print(f'Task 4:')
analyzeHobbies(participant_1, participant_2, participant_3) #

输出：

///  Task 04: Get Those Hobbies  ///
Task 4:
Unique Activities in the Town:
['Hiking', 'Reading', 'Photography', 'Cooking', 'Painting']
Statistics:
3 participant(s) like(s) Hiking 
2 participant(s) like(s) Reading 
2 participant(s) like(s) Photography 
2 participant(s) like(s) Cooking 
1 participant(s) like(s) Painting