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Fix code in documentation (#1315) (#1324)
The code would throw an error because of the `sum` being left in. When replaced with `result["sum"].mean().compute()` it computes the mean correctly: ```python >>> import dask.datasets >>> dask.config.set({"dataframe.convert-string": False}) <dask.config.set object at 0x7feccbf70a10> >>> from dask_sql import Context >>> df = dask.datasets.timeseries() >>> c = Context() >>> c.create_table("timeseries", df) >>> result = c.sql(""" ... SELECT name, SUM(x) as "sum" FROM timeseries GROUP BY name ... """) >>> result["sum"].mean().compute() 7.956598887824248 ``` Also eager string converting needs to be turned off in order to silence the following error: ```python >>> result = c.sql(""" ... SELECT name, SUM(x) as "sum" FROM timeseries GROUP BY name ... """) Traceback (most recent call last): File "/home/fila/miniconda3/envs/dask-sql/lib/python3.11/site-packages/dask_sql/mappings.py", line 118, in python_to_sql_type return DaskTypeMap(_PYTHON_TO_SQL[python_type]) ~~~~~~~~~~~~~~^^^^^^^^^^^^^ KeyError: string[pyarrow] During handling of the above exception, another exception occurred: Traceback (most recent call last): File "<stdin>", line 1, in <module> File "/home/fila/miniconda3/envs/dask-sql/lib/python3.11/site-packages/dask_sql/context.py", line 517, in sql rel, _ = self._get_ral(sql) ^^^^^^^^^^^^^^^^^^ File "/home/fila/miniconda3/envs/dask-sql/lib/python3.11/site-packages/dask_sql/context.py", line 826, in _get_ral schemas = self._prepare_schemas() ^^^^^^^^^^^^^^^^^^^^^^^ File "/home/fila/miniconda3/envs/dask-sql/lib/python3.11/site-packages/dask_sql/context.py", line 773, in _prepare_schemas column_type_mapping = list( ^^^^^ File "/home/fila/miniconda3/envs/dask-sql/lib/python3.11/site-packages/dask_sql/mappings.py", line 120, in python_to_sql_type raise NotImplementedError( NotImplementedError: The python type string is not implemented (yet) ``` Co-authored-by: Charles Blackmon-Luca <[email protected]>
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docs/source/index.rst

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@@ -52,7 +52,7 @@ For this example, we use some data loaded from disk and query it with a SQL comm
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result.compute()
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# ...or use it for another computation
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result.sum.mean().compute()
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result["sum"].mean().compute()
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.. group-tab:: GPU
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@@ -82,7 +82,7 @@ For this example, we use some data loaded from disk and query it with a SQL comm
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result.compute()
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# ...or use it for another computation
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result.sum.mean().compute()
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result["sum"].mean().compute()
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.. toctree::

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