pandas.DataFrame.to_json

DataFrame.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