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How to compare two json and write to third json differences with pandas and numpy


I am trying to compare two json and then write another json with columns names and with differences as yes or no. I am using pandas and numpy

Input files: And these input files are dynamic, for example this below example file has only two keys, where are ohter files i have may dynamic number of keys. so requirement is to loop all columns and then compare and write to json.

"AlarmName": "test",
"StateValue": "OK"


"AlarmName": "test",
"StateValue": "OK"

Below code I have tried:
import pandas as pd
import numpy as np

with open(r"c:\csv\fut.json", 'r+') as f:
data_b = json.load(f)
with open(r"c:\csv\curr.json", 'r+') as f:
data_a = json.load(f)
df_a = pd.json_normalize(data_a)
df_b = pd.json_normalize(data_b)

_, df_a = df_b.align(df_a, fill_value=np.NaN)
_, df_b = df_a.align(df_b, fill_value=np.NaN)

with open(r"c:\csv\report.json", 'w') as _file:
for col in df_a.columns:
df_temp = pd.DataFrame()
df_temp[col + '_curr'], df_temp[col + '_fut'], df_temp[col + '_diff'] = df_a[col], df_b[col], np.where((df_a[col] == df_b[col]), 'No', 'Yes')
#[df_temp.rename(columns={c:'Missing'}, inplace=True) for c in df_temp.columns if df_temp[c].isnull().all()]
df_temp.fillna('Missing', inplace=True)
with pd.option_context('display.max_colwidth', -1):

Expected output:
"AlarmName_curr": "test",
"AlarmName_fut": "test",
"AlarmName_diff": "No"
"StateValue_curr": "OK",
"StateValue_fut": "OK",
"StateValue_diff": "No"

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