- dask.dataframe.to_json(df, url_path, orient='records', lines=None, storage_options=None, compute=True, encoding='utf-8', errors='strict', compression=None, compute_kwargs=None, name_function=None, **kwargs)¶
Write dataframe into JSON text files
pandas.DataFrame.to_json(), and most parameters are passed through - see its docstring.
Differences: orient is ‘records’ by default, with lines=True; this produces the kind of JSON output that is most common in big-data applications, and which can be chunked when reading (see
- df: dask.DataFrame
Data to save
- url_path: str, list of str
Location to write to. If a string, and there are more than one partitions in df, should include a glob character to expand into a set of file names, or provide a
name_function=parameter. Supports protocol specifications such as
- encoding, errors:
The text encoding to implement, e.g., “utf-8” and how to respond to errors in the conversion (see
- orient, lines, kwargs
passed to pandas; if not specified, lines=True when orient=’records’, False otherwise.
- storage_options: dict
Passed to backend file-system implementation
- compute: bool
If true, immediately executes. If False, returns a set of delayed objects, which can be computed at a later time.
- compute_kwargsdict, optional
Options to be passed in to the compute method
- compressionstring or None
String like ‘gzip’ or ‘xz’.
- name_functioncallable, default None
Function accepting an integer (partition index) and producing a string to replace the asterisk in the given filename globstring. Should preserve the lexicographic order of partitions.