pandas.HDFStore.select

HDFStore.select(key, where=None, start=None, stop=None, columns=None, iterator=False, chunksize=None, auto_close=False)

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:

keystr

Object being retrieved from file.

wherelist or None

List of Term (or convertible) objects, optional.

startint or None

Row number to start selection.

stopint, default None

Row number to stop selection.

columnslist or None

A list of columns that if not None, will limit the return columns.

iteratorbool or False

Returns an iterator.

chunksizeint or None

Number or rows to include in iteration, return an iterator.

auto_closebool or False

Should automatically close the store when finished.

Returns:

object

Retrieved object from file.

See also

HDFStore.select_as_coordinates

Returns the selection as an index.

HDFStore.select_column

Returns a single column from the table.

HDFStore.select_as_multiple

Retrieves pandas objects from multiple tables.

Examples

>>> df = pd.DataFrame([[1, 2], [3, 4]], columns=["A", "B"])
>>> store = pd.HDFStore("store.h5", "w")
>>> store.put("data", df)
>>> store.get("data")
>>> print(store.keys())
['/data1', '/data2']
>>> store.select("/data1")
   A  B
0  1  2
1  3  4
>>> store.select("/data1", where="columns == A")
   A
0  1
1  3
>>> store.close()