how to remove a back slash from a JSON file
Question:
I want to create a json file like this:
{"946705035":4,"946706692":4 ...}
I am taking a column that only contains Unix Timestamp and group them.
result = data['Last_Modified_Date_unixtimestamp_no_time'].value_counts()
In [21]: result.head()
Out[21]:
1508284800 131
1508716800 106
1508371200 101
1508457600 99
1508630400 96
Name: Last_Modified_Date_unixtimestamp_no_time, dtype: int64
transform to a dict
result = result.to_dict()
result
'''
{1507161600: 1,
1507852800: 1,
1508198400: 64,
1508284800: 131,
...
1535155200: 1,
1535241600: 1}
'''
import json
result = json.dumps(result)
with open('result.json', 'w') as fp:
json.dump(result, fp, indent=4)
result
this is the data structure that I expected
{"946705035":4,"946706692":4}
Answers:
You’re dumping the JSON twice, which causes quotes to be escaped on the second dump. (After the first json.dumps
the result is only a string, so you’re just dumping a string instead of a dict again)
import json
# result = json.dumps(result)
with open('result.json', 'w') as fp:
json.dump(result, fp, indent=4)
Or remove the second dump:
import json
result = json.dumps(result)
with open('result.json', 'w') as fp:
# json.dump(result, fp, indent=4)
print(result, file=fp)
The simplest way to solve the above problem is to play with json.dumps()
and json.loads()
.
import json
result = json.dumps(result)
with open('result.json', 'w') as fp:
json.loads(result, fp)
data_json=df.to_json(orient='records')
parsed=json.loads(data_json)
with open('my_data.json', 'w') as f:
json.dump(parsed, f, indent=4)
First convert the dataframe to dict
response = df.to_dict(orient="records")
And then encode the response to json
json_compatible_data = jsonable_encoder(response)
This should work well.
I want to create a json file like this:
{"946705035":4,"946706692":4 ...}
I am taking a column that only contains Unix Timestamp and group them.
result = data['Last_Modified_Date_unixtimestamp_no_time'].value_counts()
In [21]: result.head()
Out[21]:
1508284800 131
1508716800 106
1508371200 101
1508457600 99
1508630400 96
Name: Last_Modified_Date_unixtimestamp_no_time, dtype: int64
transform to a dict
result = result.to_dict()
result
'''
{1507161600: 1,
1507852800: 1,
1508198400: 64,
1508284800: 131,
...
1535155200: 1,
1535241600: 1}
'''
import json
result = json.dumps(result)
with open('result.json', 'w') as fp:
json.dump(result, fp, indent=4)
result
this is the data structure that I expected
{"946705035":4,"946706692":4}
You’re dumping the JSON twice, which causes quotes to be escaped on the second dump. (After the first json.dumps
the result is only a string, so you’re just dumping a string instead of a dict again)
import json
# result = json.dumps(result)
with open('result.json', 'w') as fp:
json.dump(result, fp, indent=4)
Or remove the second dump:
import json
result = json.dumps(result)
with open('result.json', 'w') as fp:
# json.dump(result, fp, indent=4)
print(result, file=fp)
The simplest way to solve the above problem is to play with json.dumps()
and json.loads()
.
import json
result = json.dumps(result)
with open('result.json', 'w') as fp:
json.loads(result, fp)
data_json=df.to_json(orient='records')
parsed=json.loads(data_json)
with open('my_data.json', 'w') as f:
json.dump(parsed, f, indent=4)
First convert the dataframe to dict
response = df.to_dict(orient="records")
And then encode the response to json
json_compatible_data = jsonable_encoder(response)
This should work well.