Working with table data is now even more convenient͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏͏ ͏ ͏ ͏ ͏ ͏
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DataSpell 2024.1

Full Line Code Completion, the Ability to Query Data Frames via SQL Cells, Import Data Cells, and dbt Support Improvements

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ML-powered code completion

Our ML team has enhanced the local model that powers ML-assisted full line code completion for Python, resulting in longer suggestions with more context taken into account, all without sending data to the internet and completely free of charge.

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SQL for data frames and CSV files

In DataSpell 2024.1, you can now write SQL to query data frames and CSV files directly in your Jupyter notebooks.

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Import Data cells

We’ve introduced Import Data cells, which are a new cell type in DataSpell. You can easily start working with tabular data by dropping files in them.

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dbt support improvements

The latest update significantly enhances dbt Core support. You can now view graphs directly in DataSpell. We’ve improved code completion for dbt Core projects, and now you can easily run, preview, and test models directly from SQL files.

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