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# 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.

  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()