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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 : str, path object, pandas.HDFStore or file-like object -
Any valid string path is acceptable. 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.h5.If you want to pass in a path object, pandas accepts any
os.PathLike.Alternatively, pandas accepts an open
pandas.HDFStoreobject.By file-like object, we refer to objects with a
read()method, such as a file handler (e.g. via builtinopenfunction) orStringIO.New in version 0.19.0: support for pathlib, py.path.
New in version 0.21.0: support for __fspath__ protocol.
-
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
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') -
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https://pandas.pydata.org/pandas-docs/version/0.25.0/reference/api/pandas.read_hdf.html