如何通过映射合并两个json数据答案

【问题标题】：how to merge two json data by mapping如何通过映射合并两个json数据
【发布时间】：2022-12-14 04:59:14
【问题描述】：

我有两个 json 数据作为

json_1 = [{'purchasedPerson__id': 2, 'credit': 3000}, {'purchasedPerson__id': 4, 'credit': 5000}]
json_2 = [{'purchasedPerson__id': 1, 'debit': 8526}, {'purchasedPerson__id': 4, 'debit': 2000}]

我想将 json 和所需的输出合并为

json_final = [{'purchasedPerson__id': 2, 'credit': 3000 , 'debit'=0}, 
{'purchasedPerson__id': 4, 'credit': 5000 , 'debit'=2000},
 {'purchasedPerson__id': 1, 'credit'=0, 'debit': 8526}]

如何完成上述方法

【问题讨论】：

标签： python json

【解决方案1】：

json_1 = [{'purchasedPerson__id': 2, 'credit': 3000}, {'purchasedPerson__id': 4, 'credit': 5000}]
json_2 = [{'purchasedPerson__id': 1, 'debit': 8526}, {'purchasedPerson__id': 4, 'debit': 2000}]

# create a dictionary for the merged data
data = {}

# loop through each JSON and add the data to the dictionary
for j in json_1:
    data[j['purchasedPerson__id']] = {'credit': j['credit'], 'debit': 0}

for j in json_2:
    if j['purchasedPerson__id'] in data:
        data[j['purchasedPerson__id']] = {'credit': data[j['purchasedPerson__id']]['credit'], 'debit': j['debit']}
    else:
        data[j['purchasedPerson__id']] = {'credit': 0, 'debit': j['debit']}

# convert the dictionary to a list
json_final = []
for key, value in data.items():
    json_final.append({'purchasedPerson__id': key, 'credit': value['credit'], 'debit': value['debit']})

print(json_final)

【讨论】：

【解决方案2】：

这是pandas可以非常方便的情况。通过转换为数据帧并合并到“purchasedPerson__id”，您将获得所需的输出：

import pandas as pd

json_1 = [{'purchasedPerson__id': 2, 'credit': 3000}, {'purchasedPerson__id': 4, 'credit': 5000}]
json_2 = [{'purchasedPerson__id': 1, 'debit': 8526}, {'purchasedPerson__id': 4, 'debit': 2000}]
df1 = pd.DataFrame(json_1)
df2 = pd.DataFrame(json_2)

df_out = pd.merge(df1, df2, on="purchasedPerson__id", how="outer").fillna(0)
df_out.to_dict(orient="records")

输出：

[{'purchasedPerson__id': 2, 'credit': 3000.0, 'debit': 0.0}, {'purchasedPerson__id': 4, 'credit': 5000.0, 'debit': 2000.0}, {'purchasedPerson__id': 1, 'credit': 0.0, 'debit': 8526.0}]

【讨论】：

我写了几个步骤，这样你就可以一路打印每一个，但它基本上适合一行：pd.merge(pd.DataFrame(json_1), pd.DataFrame(json_2), on="purchasedPerson__id", how="outer").fillna(0).to_dict(orient="records")

【解决方案3】：

# Initialize the final JSON array
json_final = []

# Loop through the first JSON data set
for item in json_1:
    # Initialize the final JSON object for this item
    final_item = {'purchasedPerson__id': item['purchasedPerson__id'], 'credit': item['credit'], 'debit': 0}
    # Loop through the second JSON data set
    for item2 in json_2:
        # If the id matches, update the final item with the debit value
        if item['purchasedPerson__id'] == item2['purchasedPerson__id']:
            final_item['debit'] = item2['debit']
    # Add the final item to the final JSON array
    json_final.append(final_item)

# Loop through the second JSON data set
for item in json_2:
    # Initialize a flag to keep track of whether the item already exists in the final JSON array
    exists = False
    # Loop through the final JSON array
    for final_item in json_final:
        # If the id matches, set the exists flag to True
        if final_item['purchasedPerson__id'] == item['purchasedPerson__id']:
            exists = True
    # If the item does not exist in the final JSON array, add it with credit and debit values of 0
    if not exists:
        json_final.append({'purchasedPerson__id': item['purchasedPerson__id'], 'credit': 0, 'debit': item['debit']})

【讨论】：