Azure-docs: 'Derive column by example' date values needs correction

[ArvidBaa]

In the section 'Derive column by example' (https://docs.microsoft.com/en-us/azure/machine-learning/service/how-to-transform-data#derive-column-by-example), there are a number of prints of the dataset to show the derivation process. In the third of these prints, the dates are listed as

    DATE            date_timerange
30  11/1/2015 22:54     Jan 1, 2015 10PM-12AM
31  11/1/2015 23:54     Jan 1, 2015 10PM-12AM
32  11/1/2015 23:59     Jan 1, 2015 10PM-12AM
33  11/2/2015 0:54      Feb 1, 2015 12AM-2AM

and so on, but I can only assume that this is incorrect and that it should be

    DATE            date_timerange
30  1/1/2015 22:54      Jan 1, 2015 10PM-12AM
31  1/1/2015 23:54      Jan 1, 2015 10PM-12AM
32  1/1/2015 23:59      Jan 1, 2015 10PM-12AM
33  1/2/2015 0:54       Feb 1, 2015 12AM-2AM

and so on. This is also consistent with the fourth print, that looks like this (with the date_timerange column being updated thanks to a new example being added)

    DATE            date_timerange
30  1/1/2015 22:54      Jan 1, 2015 10PM-12AM
31  1/1/2015 23:54      Jan 1, 2015 10PM-12AM
32  1/1/2015 23:59      Jan 1, 2015 10PM-12AM
33  1/2/2015 0:54       Jan 2, 2015 12AM-2AM

---

Document Details

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• ID: afb5d26e-d773-37bb-805d-af8f80f12a65
• Version Independent ID: b47607fc-5bc6-5b7a-d513-367b8187bc9b
• Content: Transform data with Azure Machine Learning Data Prep SDK - Python
• Content Source: articles/machine-learning/service/how-to-transform-data.md
• Service: machine-learning
• GitHub Login: @cforbe
• Microsoft Alias: cforbe

[YutongTie-MSFT]

@ArvidBaa Thanks for the feedback! We are currently investigating and will update you shortly.

[cforbe]

Thank you for catching that! It's being updated

[YutongTie-MSFT]

@cforbe Thanks for the quick action.

@ArvidBaa We will now proceed to close this thread. If there are further questions regarding this matter, please respond here and @YutongTie-MSFT and we will gladly continue the discussion.

[rungsoso]

builder = dflow_derive.builders.derive_column_by_example(source_columns=['DATE'], new_column_name='date_timerange')
builder.add_example(source_data=dflow_derive.iloc[1], example_value='Jan 1, 2015 12AM-2AM')
builder.preview(count=5)

---

AttributeError Traceback (most recent call last)
in
1 builder = dflow_derive.builders.derive_column_by_example(source_columns=['DATE'], new_column_name='date_timerange')
----> 2 builder.add_example(source_data=dflow_derive.iloc[1], example_value='Jan 1, 2015 12AM-2AM')
3 builder.preview(count=5)

AttributeError: 'Dataflow' object has no attribute 'iloc'

[TessFerrandez]

builder = dflow.builders.derive_column_by_example(source_columns=['DATE'], new_column_name='date_timerange')
builder.add_example(source_data=dflow.iloc[1], example_value='Jan 1, 2015 12AM-2AM')
builder.preview(count=5)

Should be

df = dflow.head(5)
builder = dflow.builders.derive_column_by_example(source_columns=['DATE'], new_column_name='date_timerange')
builder.add_example(source_data=df.iloc[1], example_value='Jan 1, 2015 12AM-2AM')
builder.preview(count=5)

to avoid the AttributeError: 'Dataflow' object has no attribute 'iloc'

[TessFerrandez]

builder = dflow_derive.builders.derive_column_by_example(source_columns=['DATE'], new_column_name='date_timerange')
builder.add_example(source_data=dflow_derive.iloc[1], example_value='Jan 1, 2015 12AM-2AM')
builder.preview(count=5)

AttributeError Traceback (most recent call last)
in
1 builder = dflow_derive.builders.derive_column_by_example(source_columns=['DATE'], new_column_name='date_timerange')
----> 2 builder.add_example(source_data=dflow_derive.iloc[1], example_value='Jan 1, 2015 12AM-2AM')
3 builder.preview(count=5)

AttributeError: 'Dataflow' object has no attribute 'iloc'

[TessFerrandez]

or rather

df = dflow.to_pandas_dataframe()

[YutongTie-MSFT]

@cforbe FYI