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# pandas.HDFStore.create_table_index

HDFStore.create_table_index(key, columns=None, optlevel=None, kind=None)

  Create a pytables index on the table.

  Indexes are automatically created on indexable axes and `data_columns` during `append`/`put` when `index=True` (the default). This method lets you add or rebuild indexes after the fact, which is highly encouraged because it greatly speeds up `select` calls that filter on the indexed dimension.

  Parameters:
    key str

      Object stored in the file to index.

    columns None, bool, or listlike[str]

      Indicate which columns to create an index on.

      - False : Do not create any indexes.

      - True : Create indexes on all columns.

      - None : Create indexes on all columns.

      - listlike : Create indexes on the given columns.

    optlevel int or None, default None

      Optimization level, if None, pytables defaults to 6.

    kind str or None, default None

      Kind of index, if None, pytables defaults to “medium”.

  Raises:
    TypeError

      If the node is not a table.

  See also

  `HDFStore.append`

    Append data to an existing table; columns are indexed automatically by default.

  `HDFStore.select`

    Filter on indexed columns for fast retrieval.

  Examples

      >>> df = pd.DataFrame([[1, 2], [3, 4]], columns=["A", "B"])
      >>> store = pd.HDFStore("store.h5", "w")
      >>> store.append("data", df, format="table", index=False)
      >>> store.create_table_index("data", columns=["A"])
      >>> store.close()