
hana_ml
) has been released. So, what could be a better way to celebrate World Statistics Day if not looking at one of the new features of that release brought to help you to understand, and therefore help you to trust, the data you have? In this post, we will look at the new feature called the Dataset Report that generates a report from profiling data in SAP HANA table.docker run -p 8888:8888 --detach -v ~:/home/jovyan/work --name hmlsandbox01 -e GRANT_SUDO=yes -e JUPYTER_ENABLE_LAB=yes jupyter/minimal-notebook start-notebook.sh --LabApp.token=''
docker exec hmlsandbox01 pip install hana_ml==2.6.*
--LabApp.token=''
so that Jupyter Lab is not secured, but then it is running on my laptop for my own experiments, so I did it on purpose.docker exec hmlsandbox01 conda install -c conda-forge ipywidgets
docker exec hmlsandbox01 jupyter labextension install @jupyter-widgets/jupyterlab-manager@2.0
docker restart hmlsandbox01
2.6
.import hana_ml
hana_ml.__version__
scriptserver
service included at the time of writing. Without the scriptserver
SAP HANA embedded ML libraries, like PAL and APL cannot run.cchc=hana_ml.dataframe.ConnectionContext(port=443,
address='<uuid>.hana.prod-eu20.hanacloud.ondemand.com',
user='<user_name>',
password='<MySuperSecretPassword>',
encrypt=True)
hdf_mallcustomers=cchc.table('MALL_CUSTOMERS')
hdf_mallcustomers.collect()
from hana_ml.visualizers.dataset_report import DatasetReportBuilder
drb_mall=DatasetReportBuilder()
drb_mall.build(data=hdf_mallcustomers, key='ID')
drb_mall.generate_notebook_iframe_report()
hana_ml
-- especially support for multi-model analytics -- already next week 😉You must be a registered user to add a comment. If you've already registered, sign in. Otherwise, register and sign in.
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