pandas.read_feather#
- pandas.read_feather(path, columns=None, use_threads=True, storage_options=None, dtype_backend=<no_default>)[source]#
Load a feather-format object from the file path.
- Parameters:
- pathstr, path object, or file-like object
String, path object (implementing
os.PathLike[str]
), or file-like object implementing a binaryread()
function. 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.feather
.- columnssequence, default None
If not provided, all columns are read.
- use_threadsbool, default True
Whether to parallelize reading using multiple threads.
- storage_optionsdict, 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.request.Request
as header options. For other URLs (e.g. starting with “s3://”, and “gcs://”) the key-value pairs are forwarded tofsspec.open
. Please seefsspec
andurllib
for more details, and for more examples on storage options refer here.- dtype_backend{‘numpy_nullable’, ‘pyarrow’}, default ‘numpy_nullable’
Back-end data type applied to the resultant
DataFrame
(still experimental). Behaviour is as follows:"numpy_nullable"
: returns nullable-dtype-backedDataFrame
(default)."pyarrow"
: returns pyarrow-backed nullableArrowDtype
DataFrame.
Added in version 2.0.
- Returns:
- type of object stored in file
Examples
>>> df = pd.read_feather("path/to/file.feather")