pandas.read_hdf#
- pandas.read_hdf(path_or_buf, key=None, mode='r', errors='strict', where=None, start=None, stop=None, columns=None, iterator=False, chunksize=None, **kwargs)[source]#
Read from the store, close it if we opened it.
Retrieve pandas object stored in file, optionally based on where criteria.
Warning
Pandas uses PyTables for reading and writing HDF5 files, which allows serializing object-dtype data with pickle when using the “fixed” format. Loading pickled data received from untrusted sources can be unsafe.
See: https://docs.python.org/3/library/pickle.html for more.
- Parameters
- path_or_bufstr, 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.- keyobject, 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’.- errorsstr, default ‘strict’
Specifies how encoding and decoding errors are to be handled. See the errors argument for
open()
for a full list of options.- wherelist, optional
A list of Term (or convertible) objects.
- startint, optional
Row number to start selection.
- stopint, optional
Row number to stop selection.
- columnslist, optional
A list of columns names to return.
- iteratorbool, optional
Return an iterator object.
- chunksizeint, optional
Number of rows to include in an iteration when using an iterator.
- **kwargs
Additional keyword arguments passed to HDFStore.
- Returns
- itemobject
The selected object. Return type depends on the object stored.
See also
DataFrame.to_hdf
Write a HDF file from a DataFrame.
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')