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DOC: remove okwarning from scale guide (#50004)
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doc/source/user_guide/scale.rst

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@@ -257,7 +257,6 @@ We'll import ``dask.dataframe`` and notice that the API feels similar to pandas.
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We can use Dask's ``read_parquet`` function, but provide a globstring of files to read in.
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.. ipython:: python
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:okwarning:
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import dask.dataframe as dd
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@@ -287,7 +286,6 @@ column names and dtypes. That's because Dask hasn't actually read the data yet.
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Rather than executing immediately, doing operations build up a **task graph**.
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.. ipython:: python
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:okwarning:
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ddf
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ddf["name"]
@@ -346,7 +344,6 @@ known automatically. In this case, since we created the parquet files manually,
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we need to supply the divisions manually.
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.. ipython:: python
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:okwarning:
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N = 12
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starts = [f"20{i:>02d}-01-01" for i in range(N)]
@@ -359,7 +356,6 @@ we need to supply the divisions manually.
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Now we can do things like fast random access with ``.loc``.
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.. ipython:: python
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:okwarning:
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ddf.loc["2002-01-01 12:01":"2002-01-01 12:05"].compute()
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@@ -373,7 +369,6 @@ results will fit in memory, so we can safely call ``compute`` without running
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out of memory. At that point it's just a regular pandas object.
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.. ipython:: python
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:okwarning:
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@savefig dask_resample.png
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ddf[["x", "y"]].resample("1D").mean().cumsum().compute().plot()

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