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 binary read() 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 to fsspec.open. Please see fsspec and urllib for more details, and for more examples on storage options refer here.

dtype_backend{‘numpy_nullable’, ‘pyarrow’}

Back-end data type applied to the resultant DataFrame (still experimental). If not specified, the default behavior is to not use nullable data types. If specified, the behavior is as follows:

Added in version 2.0.

Returns:
type of object stored in file

DataFrame object stored in the file.

See also

read_csv

Read a comma-separated values (csv) file into a pandas DataFrame.

read_excel

Read an Excel file into a pandas DataFrame.

read_spss

Read an SPSS file into a pandas DataFrame.

read_orc

Load an ORC object into a pandas DataFrame.

read_sas

Read SAS file into a pandas DataFrame.

Examples

>>> df = pd.read_feather("path/to/file.feather")