pandas.read_hdf

pandas.read_hdf(path_or_buf, key=None, mode='r', **kwargs) [source]

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

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

Parameters:

path_or_buf : string, buffer or path object Path to the file to open, or an open pandas.HDFStore object. Supports any object implementing the __fspath__ protocol. This includes pathlib.Path and py._path.local.LocalPath objects. New in version 0.19.0: support for pathlib, py.path. New in version 0.21.0: support for __fspath__ proptocol. 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’}, optional Mode to use when opening the file. Ignored if path_or_buf is a pandas.HDFStore. Default is ‘r’. 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. 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. **kwargs Additional keyword arguments passed to HDFStore.

Returns:

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

See also

pandas.DataFrame.to_hdf

write a HDF file from a DataFrame

pandas.HDFStore

low-level access to HDF files

Examples

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