Document

read_json(path_or_buf=None, orient=None, typ='frame', dtype: 'DtypeArg | None' = None, convert_axes=None, convert_dates=True, keep_default_dates: 'bool' = True, numpy: 'bool' = False, precise_float: 'bool' = False, date_unit=None, encoding=None, encoding_errors: 'str | None' = 'strict', lines: 'bool' = False, chunksize: 'int | None' = None, compression: 'CompressionOptions' = 'infer', nrows: 'int | None' = None, storage_options: 'StorageOptions' = None)

Notes

Specific to orient='table' , if a DataFrame with a literal Index name of :None:None:`index` gets written with to_json , the subsequent read operation will incorrectly set the Index name to None . This is because :None:None:`index` is also used by DataFrame.to_json to denote a missing Index name, and the subsequent read_json operation cannot distinguish between the two. The same limitation is encountered with a MultiIndex and any names beginning with 'level_' .

Parameters

path_or_buf : a valid JSON str, path object or file-like object

Any valid string path is acceptable. The string could be a URL. Valid URL schemes include http, ftp, s3, and file. For file URLs, a host is expected. A local file could be: file://localhost/path/to/table.json .

If you want to pass in a path object, pandas accepts any os.PathLike .

By file-like object, we refer to objects with a read() method, such as a file handle (e.g. via builtin open function) or StringIO .

orient : str

Indication of expected JSON string format. Compatible JSON strings can be produced by to_json() with a corresponding orient value. The set of possible orients is:

typ : {'frame', 'series'}, default 'frame'

The type of object to recover.

dtype : bool or dict, default None

If True, infer dtypes; if a dict of column to dtype, then use those; if False, then don't infer dtypes at all, applies only to the data.

For all orient values except 'table' , default is True.

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Not applicable for orient='table' .

convert_axes : bool, default None

Try to convert the axes to the proper dtypes.

For all orient values except 'table' , default is True.

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Not applicable for orient='table' .

convert_dates : bool or list of str, default True

If True then default datelike columns may be converted (depending on keep_default_dates). If False, no dates will be converted. If a list of column names, then those columns will be converted and default datelike columns may also be converted (depending on keep_default_dates).

keep_default_dates : bool, default True

If parsing dates (convert_dates is not False), then try to parse the default datelike columns. A column label is datelike if

it ends with '_at' ,
it ends with '_time' ,
it begins with 'timestamp' ,
it is 'modified' , or
it is 'date' .

numpy : bool, default False

Direct decoding to numpy arrays. Supports numeric data only, but non-numeric column and index labels are supported. Note also that the JSON ordering MUST be the same for each term if numpy=True.

deprecated

precise_float : bool, default False

Set to enable usage of higher precision (strtod) function when decoding string to double values. Default (False) is to use fast but less precise builtin functionality.

date_unit : str, default None

The timestamp unit to detect if converting dates. The default behaviour is to try and detect the correct precision, but if this is not desired then pass one of 's', 'ms', 'us' or 'ns' to force parsing only seconds, milliseconds, microseconds or nanoseconds respectively.

encoding : str, default is 'utf-8'

The encoding to use to decode py3 bytes.

encoding_errors : str, optional, default "strict"

How encoding errors are treated. :None:None:`List of possible values <https://docs.python.org/3/library/codecs.html#error-handlers>` .

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lines : bool, default False

Read the file as a json object per line.

chunksize : int, optional

Return JsonReader object for iteration. See the :None:None:`line-delimited json docs <https://pandas.pydata.org/pandas-docs/stable/user_guide/io.html#line-delimited-json>` for more information on chunksize . This can only be passed if :None:None:`lines=True`. If this is None, the file will be read into memory all at once.

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JsonReader is a context manager.

compression : str or dict, default 'infer'

For on-the-fly decompression of on-disk data. If 'infer' and 'path_or_buf' is path-like, then detect compression from the following extensions: '.gz', '.bz2', '.zip', '.xz', or '.zst' (otherwise no compression). If using 'zip', the ZIP file must contain only one data file to be read in. Set to None for no decompression. Can also be a dict with key 'method' set to one of { 'zip' , 'gzip' , 'bz2' , 'zstd' } and other key-value pairs are forwarded to zipfile.ZipFile , gzip.GzipFile , bz2.BZ2File , or zstandard.ZstdDecompressor , respectively. As an example, the following could be passed for Zstandard decompression using a custom compression dictionary: compression={'method': 'zstd', 'dict_data': my_compression_dict} .

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nrows : int, optional

The number of lines from the line-delimited jsonfile that has to be read. This can only be passed if :None:None:`lines=True`. If this is None, all the rows will be returned.

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storage_options : dict, optional

Extra options that make sense for a particular storage connection, e.g. host, port, username, password, etc. For HTTP(S) URLs the key-value pairs are forwarded to urllib as header options. For other URLs (e.g. starting with "s3://", and "gcs://") the key-value pairs are forwarded to fsspec . Please see fsspec and urllib for more details.

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