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Update how-to-create-data-assets.md
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articles/machine-learning/how-to-create-data-assets.md

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@@ -291,7 +291,7 @@ mltable = from_delta_lake(delta_table_path, timestamp_as_of="2021-01-01T00:00:00
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df = mltable.to_pandas_dataframe()
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print(df.to_string())
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```
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Please find more details about [MLTable Python functions here](https://learn.microsoft.com/python/api/mltable/mltable.mltable?view=azure-ml-py#functions).
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Please find more details about [MLTable Python functions here](/python/api/mltable/mltable).
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In your Python code, you materialize the MLTable artifact into a Pandas dataframe using:

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