Series.to_json(path_or_buf=None, orient=None, date_format=None, double_precision=10, force_ascii=True, date_unit='ms', default_handler=None, lines=False, compression=None, index=True)
[source]
Convert the object to a JSON string.
Note NaN’s and None will be converted to null and datetime objects will be converted to UNIX timestamps.
Parameters: |
path_or_buf : string or file handle, optional File path or object. If not specified, the result is returned as a string. orient : string Indication of expected JSON string format.
date_format : {None, ‘epoch’, ‘iso’} Type of date conversion. ‘epoch’ = epoch milliseconds, ‘iso’ = ISO8601. The default depends on the double_precision : int, default 10 The number of decimal places to use when encoding floating point values. force_ascii : boolean, default True Force encoded string to be ASCII. date_unit : string, default ‘ms’ (milliseconds) The time unit to encode to, governs timestamp and ISO8601 precision. One of ‘s’, ‘ms’, ‘us’, ‘ns’ for second, millisecond, microsecond, and nanosecond respectively. default_handler : callable, default None Handler to call if object cannot otherwise be converted to a suitable format for JSON. Should receive a single argument which is the object to convert and return a serialisable object. lines : boolean, default False If ‘orient’ is ‘records’ write out line delimited json format. Will throw ValueError if incorrect ‘orient’ since others are not list like. New in version 0.19.0. compression : {None, ‘gzip’, ‘bz2’, ‘zip’, ‘xz’} A string representing the compression to use in the output file, only used when the first argument is a filename. New in version 0.21.0. index : boolean, default True Whether to include the index values in the JSON string. Not including the index ( New in version 0.23.0. |
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See also
>>> df = pd.DataFrame([['a', 'b'], ['c', 'd']], ... index=['row 1', 'row 2'], ... columns=['col 1', 'col 2']) >>> df.to_json(orient='split') '{"columns":["col 1","col 2"], "index":["row 1","row 2"], "data":[["a","b"],["c","d"]]}'
Encoding/decoding a Dataframe using 'records'
formatted JSON. Note that index labels are not preserved with this encoding.
>>> df.to_json(orient='records') '[{"col 1":"a","col 2":"b"},{"col 1":"c","col 2":"d"}]'
Encoding/decoding a Dataframe using 'index'
formatted JSON:
>>> df.to_json(orient='index') '{"row 1":{"col 1":"a","col 2":"b"},"row 2":{"col 1":"c","col 2":"d"}}'
Encoding/decoding a Dataframe using 'columns'
formatted JSON:
>>> df.to_json(orient='columns') '{"col 1":{"row 1":"a","row 2":"c"},"col 2":{"row 1":"b","row 2":"d"}}'
Encoding/decoding a Dataframe using 'values'
formatted JSON:
>>> df.to_json(orient='values') '[["a","b"],["c","d"]]'
Encoding with Table Schema
>>> df.to_json(orient='table') '{"schema": {"fields": [{"name": "index", "type": "string"}, {"name": "col 1", "type": "string"}, {"name": "col 2", "type": "string"}], "primaryKey": "index", "pandas_version": "0.20.0"}, "data": [{"index": "row 1", "col 1": "a", "col 2": "b"}, {"index": "row 2", "col 1": "c", "col 2": "d"}]}'
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Licensed under the 3-clause BSD License.
http://pandas.pydata.org/pandas-docs/version/0.23.4/generated/pandas.Series.to_json.html