I have large pandas tabular dataframe to convert into JSON. The standard .to_json() functions does not make a compact format for JSON. How to get JSON output forma like this, using pandas only ?
{"index": [ 0, 1 ,3 ],
"col1": [ "250", "1" ,"3" ],
"col2": [ "250", "1" ,"3" ]
}
This is a much compact format form of JSON for tabular data. (I can do a loop over the rows.... but)
At times, you may need to convert your pandas dataframe to List. To accomplish this task, ' tolist() ' function can be used.
orient: String value, ('dict', 'list', 'series', 'split', 'records', 'index') Defines which dtype to convert Columns(series into). For example, 'list' would return a dictionary of lists with Key=Column name and Value=List (Converted series). into: class, can pass an actual class or instance.
orient : Indication of expected JSON string format. date_format : None, 'epoch', 'iso'} double_precision : The number of decimal places to use when encoding floating point values. force_ascii : Force encoded string to be ASCII. date_unit : string, default 'ms' (milliseconds)
It seems you need to_dict
first and then dict
to json
:
df = pd.DataFrame({"index": [ 0, 1 ,3 ],
"col1": [ "250", "1" ,"3" ],
"col2": [ "250", "1" ,"3" ]
})
print (df)
col1 col2 index
0 250 250 0
1 1 1 1
2 3 3 3
print (df.to_dict(orient='list'))
{'col1': ['250', '1', '3'], 'col2': ['250', '1', '3'], 'index': [0, 1, 3]}
import json
print (json.dumps(df.to_dict(orient='list')))
{"col1": ["250", "1", "3"], "col2": ["250", "1", "3"], "index": [0, 1, 3]}
Because it is not implemented yet:
print (df.to_json(orient='list'))
ValueError: Invalid value 'list' for option 'orient'
EDIT:
If index is not column, add reset_index
:
df = pd.DataFrame({"col1": [250, 1, 3],
"col2": [250, 1, 3]})
print (df)
col1 col2
0 250 250
1 1 1
2 3 3
print (df.reset_index().to_dict(orient='list'))
{'col1': [250, 1, 3], 'index': [0, 1, 2], 'col2': [250, 1, 3]}
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