read_hdf(path_or_buf, key=None, mode: 'str' = 'r', errors: 'str' = 'strict', where=None, start: 'int | None' = None, stop: 'int | None' = None, columns=None, iterator=False, chunksize: 'int | None' = None, **kwargs)

Retrieve pandas object stored in file, optionally based on where criteria.

Parameters

path_or_buf : str, path object, pandas.HDFStore

Any valid string path is acceptable. Only supports the local file system, remote URLs and file-like objects are not supported.

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

Alternatively, pandas accepts an open pandas.HDFStore object.

key : object, optional

The group identifier in the store. Can be omitted if the HDF file contains a single pandas object.

mode : {'r', 'r+', 'a'}, default 'r'

Mode to use when opening the file. Ignored if path_or_buf is a pandas.HDFStore . Default is 'r'.

errors : str, default 'strict'

Specifies how encoding and decoding errors are to be handled. See the errors argument for open for a full list of options.

where : list, optional

A list of Term (or convertible) objects.

start : int, optional

Row number to start selection.

stop : int, optional

Row number to stop selection.

columns : list, optional

A list of columns names to return.

iterator : bool, optional

Return an iterator object.

chunksize : int, optional

Number of rows to include in an iteration when using an iterator.

**kwargs :

Additional keyword arguments passed to HDFStore.

Returns

item : object

The selected object. Return type depends on the object stored.

Read from the store, close it if we opened it.

See Also

DataFrame.to_hdf

Write a HDF file from a DataFrame.

HDFStore

Low-level access to HDF files.

Examples

This example is valid syntax, but we were not able to check execution

>>> df = pd.DataFrame([[1, 1.0, 'a']], columns=['x', 'y', 'z'])  # doctest: +SKIP
... df.to_hdf('./store.h5', 'data')  # doctest: +SKIP
... reread = pd.read_hdf('./store.h5')  # doctest: +SKIP

See :

Back References

The following pages refer to to this document either explicitly or contain code examples using this.

pandas.core.generic.NDFrame.to_hdf pandas.io.pickle.read_pickle

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