Read JSON to pandas dataframe - Getting ValueError: Mixing dicts with non-Series may lead to ambiguous ordering - json

Question

I am trying to read in the JSON structure below into pandas dataframe, but it throws out the error message:
ValueError: Mixing dicts with non-Series may lead to ambiguous ordering.
Json data:
'''
{
"Name": "Bob",
"Mobile": 12345678,
"Boolean": true,
"Pets": ["Dog", "cat"],
"Address": {
"Permanent Address": "USA",
"Current Address": "UK"
},
"Favorite Books": {
"Non-fiction": "Outliers",
"Fiction": {"Classic Literature": "The Old Man and the Sea"}
}
}
'''
How do I get this right? I have tried the script below...
'''
j_df = pd.read_json('json_file.json')
j_df
with open(j_file) as jsonfile:
data = json.load(jsonfile)
'''

Answer 1

Read json from file first and pass to json_normalize with DataFrame.explode:
import json
with open('json_file.json') as data_file:
data = json.load(data_file)
df = pd.json_normalize(j).explode('Pets').reset_index(drop=True)
print (df)
Name Mobile Boolean Pets Address.Permanent Address \
0 Bob 12345678 True Dog USA
1 Bob 12345678 True cat USA
Address.Current Address Favorite Books.Non-fiction \
0 UK Outliers
1 UK Outliers
Favorite Books.Fiction.Classic Literature
0 The Old Man and the Sea
1 The Old Man and the Sea
EDIT: For write values to sentence you can select necessary columns, remove duplicates, create numpy array and loop:
for x, y in df[['Name','Favorite Books.Fiction.Classic Literature']].drop_duplicates().to_numpy():
print (f"{x}’s favorite classical iterature book is {y}.")
Bob’s favorite classical iterature book is The Old Man and the Sea.