pandas.Series.to_json
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Series.to_json(path_or_buf=None, orient=None, date_format='epoch', double_precision=10, force_ascii=True, date_unit='ms', default_handler=None, lines=False) 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 : the path or buffer to write the result string
if this is None, return a StringIO of the converted string
orient : string
- Series
- default is ‘index’
- allowed values are: {‘split’,’records’,’index’}
- DataFrame
- default is ‘columns’
- allowed values are: {‘split’,’records’,’index’,’columns’,’values’}
- The format of the JSON string
- split : dict like {index -> [index], columns -> [columns], data -> [values]}
- records : list like [{column -> value}, ... , {column -> value}]
- index : dict like {index -> {column -> value}}
- columns : dict like {column -> {index -> value}}
- values : just the values array
date_format : {‘epoch’, ‘iso’}
Type of date conversion. epoch = epoch milliseconds, iso` = ISO8601, default is epoch.
double_precision : The number of decimal places to use when encoding
floating point values, default 10.
force_ascii : force encoded string to be ASCII, default True.
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, defalut 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.
Returns: same type as input object with filtered info axis
- Series