如何根據關聯值從文本文件中提取常用行？

Question

我有 3 個文本文件：

列表1.txt：

032_M5, 5
035_M9, 5
036_M4, 3
038_M2, 6
041_M1, 6

列表2.txt：

032_M5, 6
035_M9, 6
036_M4, 5
038_M2, 5
041_M1, 6

清單 3.txt：

032_M5, 6
035_M9, 6
036_M4, 4
038_M2, 5
041_M1, 6

其中所有 3 個文本文件中行的第一部分（即字符串）相同，但第二部分（即數字）發生了變化。

我想從中獲取三個 output 文件：

Output1.txt --> 數字對應字符串的所有行都是不同的。 例子：

036_M4 3, 5, 4

Output2.txt --> 數字對應字符串的所有行都是相同的。 例子：

041_M1, 6

Output3.txt --> 至少兩個數字對應一個字符串的所有行都是相同的（也包括 Output2.txt 的結果）。 例子：

032_M5, 6
035_M9, 6
038_M2, 5
041_M1, 6

然后，我需要 Output3.txt 中編號為 1、編號 2、編號 3、編號 4、編號 5 和編號 6 的行數。

這是我嘗試過的。 它給了我錯誤的 output。

from collections import defaultdict
data = defaultdict(list)
for fileName in ["List1.txt","List2.txt", "List3.txt"]:
    with open(fileName,'r') as file1:
        for line in file1:
            col1,value = line.split(",") 
            data[col1].append(int(value))

with open("Output3.txt","w") as output:
    for (col1),values in data.items():
        if len(values) < 3: continue             
        result = max(x for x in values)                     
        output.write(f"{col1}, {result}\n")

Answer 1

這是一種不使用任何 python 模塊的方法，它完全依賴於本機內置 python 函數：

with open("List1.txt", "r") as list1, open("List2.txt", "r") as list2, open("List3.txt", "r") as list3:
  # Forming association between keywords and numbers.
  data1 = list1.readlines()
  totalKeys = [elem.split(',')[0] for elem in data1]
  numbers1 = [elem.split(',')[1].strip() for elem in data1]
  numbers2 = [elem.split(',')[1].strip() for elem in list2.readlines()]
  numbers3 = [elem.split(',')[1].strip() for elem in list3.readlines()]
  totalValues = list(zip(numbers1,numbers2,numbers3))
  totalDict = dict(zip(totalKeys,totalValues))

  #Outputs
  output1 = []
  output2 = []
  output3 = []
  for key in totalDict.keys():
    #Output1
    if len(set(totalDict[key])) == 3:
      output1.append([key, totalDict[key]])
    #Output2
    if len(set(totalDict[key])) == 1:
      output2.append([key, totalDict[key][0]])
    #Output3
    if len(set(totalDict[key])) <= 2:
      output3.append([key, max(totalDict[key], key=lambda elem: totalDict[key].count(elem))])

  #Output1
  print('Output1:')
  for elem in output1:
    print(elem[0] + ' ' + ", ".join(elem[1]))
  print()

  #Output2
  print('Output2:')
  for elem in output2:
    print(elem[0] + ' ' + " ".join(elem[1]))
  print()

  #Output3
  print('Output3:')
  for elem in output3:
    print(elem[0] + ' ' + " ".join(elem[1]))

上述結果將是：

Output1:
036_M4 3, 5, 4

Output2:
041_M1 6

Output3:
032_M5 6
035_M9 6
038_M2 5
041_M1 6

Answer 2

max給出列表中最大的數字，而不是最常出現的數字。 為此，請使用statistics.mode

from collections import defaultdict
from statistics import mode

data = defaultdict(list)
for fileName in ["List1.txt","List2.txt", "List3.txt"]:
    with open(fileName,'r') as file1:
        for line in file1:
            col1,value = line.split(",") 
            data[col1].append(int(value))

with open("Output1.txt","w") as output:
    for (col1),values in data.items():
        if len(values) < 3: continue
        if values[0] != values[1] != values[2] and values[0] != values[2]:
            output.write(f"{col1}, {values[0]}, {values[1]}, {values[2]}\n")

with open("Output2.txt","w") as output:
    for (col1),values in data.items():
        if len(values) < 3: continue
        if values[0] == values[1] == values[2]:
            output.write(f"{col1}, {values[0]}\n")

with open("Output3.txt","w") as output:
    for (col1),values in data.items():
        if len(values) < 3: continue
        if len(set(values)) >= 2:
            output.write(f"{col1}, {mode(values)}\n")