# dask.dataframe.Series.compute

#### Series.compute(\*\*kwargs)

Compute this dask collection

This turns a lazy Dask collection into its in-memory equivalent.
For example a Dask array turns into a NumPy array and a Dask dataframe
turns into a Pandas dataframe.  The entire dataset must fit into memory
before calling this operation.

* **Parameters:**
  **scheduler**
  : Which scheduler to use like “threads”, “synchronous” or “processes”.
    If not provided, the default is to check the global settings first,
    and then fall back to the collection defaults.

  **optimize_graph**
  : If True [default], the graph is optimized before computation.
    Otherwise the graph is run as is. This can be useful for debugging.

  **kwargs**
  : Extra keywords to forward to the scheduler function.

#### SEE ALSO
[`dask.compute`](../api.html.md#dask.compute)

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