Python将具有相同id但不同值的术语附加到列表中？答案

【问题标题】：Python append terms that had same id but different values to a list?Python将具有相同id但不同值的术语附加到列表中？
【发布时间】：2020-07-30 18:36:22
【问题描述】：

我有 csv 文件，其中包含一般概念和相应的医学术语或短语。我怎样才能写一个循环，以便我可以将所有短语分组到它们对应的概念？我对python不是很有经验，所以我不确定如何编写循环。

id   concept           phrase
--------------------------------
1    general_history   H&P
1    general_history   history and physical
1    general_history   history physical
2    clinic_history    clinic history physical
2    clinic_history    outpatient h p
3    discharge         discharge summary
3    discharge         DCS

对于相同的概念术语（或相同的 ID），我如何将短语附加到列表中以获得如下内容：

var = [[general_history, ['history and physical', history physical]], 
       [clinic_history, ['clinic history physical', 'outpatient h p']], 
       [discharge, ['discharge summary', 'DCS']]]

【问题讨论】：

标签： python for-loop nested-loops

【解决方案1】：

使用 for 循环和 defaultdict 来累积术语。

import csv
from collections import defaultdict
var = defaultdict(list)
records = ...  # read csv with csv.DictReader
for row in records:
    concept = row.get('concept', None)
    if concept is None: continue
    phrase = row.get('phrase', None)
    if phrase is None: continue
    var[concept].append(phrase)
print(var)

【讨论】：

【解决方案2】：

假设您已经可以解析 csv，以下是您可以按概念进行排序的方法

from collections import defaultdict

concepts = defaultdict(list)

""" parse csv """

for row in csv:
    id, concept, phrase = row
    concepts[concept].append(phrase)

var = [[k, concepts[k]] for k in concepts.keys()]

var 会保存这样的内容：

[['general_history', ['history and physical', 'history physical']...]

如果您维护该字典的键，甚至可能有用的是，var 看起来像这样：

{
  "general_history": [
    "history and physical",
    "history physical",
  ],
 ...
}

【讨论】：

【解决方案3】：

如果您使用的是 pandas，请尝试过滤。它应该看起来像这样：

new_dataframe = dataframe[dataframe['id'] == id]

然后，连接数据帧，

final_df = pd.concat([new_dataframe1, new_dataframe2], axis = 0)

你也可以尝试对概念做同样的事情。

【讨论】：

【解决方案4】：

希望这能解决您的问题：

# a quick way to to transfer the data into python
csv_string = """id, concept, phrase
1, general_history, H&P
1, general_history, history and physical
1, general_history, history physical
2, clinic_history, clinic history physical
2, clinic_history, outpatient h p
3, discharge, discharge summary
3, discharge, DCS"""

# formats the data as shown in the original question
csv=[[x.strip() for x in line.split(", ")]  for line in csv_string.split("\n")]

# makes a dictionary with an empty list that will hold all data points
id_dict = {line[0]:[] for line in csv[1:]}

# iterates and adds all possible combinations of id's and phrases
for line in csv[1:]:
    current_id = line[0]
    phrases = line[2]
    id_dict[current_id].append(phrases)

# makes the data into a list of lists containing only unique phrases
[[current_id, list(set(phrases))] for current_id, phrases in id_dict.items()]

【讨论】：