DataSpell 2023.1

個別の環境とNotebookの生産性ブースターがある複数のプロジェクトをサポート
4月 4, 2023
新バージョン

機能

  • Multiple Projects With Separate Environments
    • Manage multiple separate projects - DataSpell now enables you to organize your work into multiple, completely separate projects, each of which has its own virtual environment or Python interpreter.
    • Workspace with attached directories - Alternatively, you can continue to use a single workspace with attached directories. The environment or interpreter configured for the workspace is inherited by the directories and projects you attach to the workspace by default.
  • Jupyter Notebook Productivity Boosters
    • Jupyter Notebook to Python script - Switching back and forth between Jupyter Notebooks and Python scripts is a common workflow in data science. You can now convert a Jupyter Notebook (.ipynb file) to a Python script (.py file) and vice versa in just a few clicks.
    • Cell execution start time and duration - Since Jupyter Notebook cells are often executed out of order and some run for a long time, both the last time a code cell was executed and the duration of the execution are now displayed directly below the cell.
    • Jupyter Notebook code completion - The ineffective code completion provided by Jupyter Notebooks has been disabled. Instead, use the new and improved DataFrame column name completion, autocompletion for dynamic classes, path completion for remote Jupyter servers, and more.
    • Markdown user experience - Several improvements are available for Markdown cells in Jupyter Notebooks and Markdown files, including an intention action to correct the formatting of tables, the Fill Paragraph editor action to break up long texts, and a Smart Keys settings page for Markdown files.
  • DataFrame Enhancements
    • CSV to pandas DataFrame - Creating a pandas DataFrame from the data in a CSV file is a common data science task. Drag and drop a CSV (.csv file) into a Jupyter Notebook and a pandas DataFrame will be automatically created from the contents of the file.
    • Change default rows displayed - DataSpell now displays the contents of pandas DataFrames in tabular form. To browse large DataFrame tables more comfortably, update the number of rows displayed per page to your preferred page size using the Change Default dialog.
  • User Experience
    • Python packages tool window - The Python Packages tool window is the quickest way to manage packages and preview package documentation for a particular environment or Python interpreter.
    • Debug console in the Jupyter Notebook debugger - The interactive debug console can now be used to send commands to the Jupyter Debugger and view outputs and error messages while debugging Jupyter Notebook cells.
    • Enhanced interpreter widget - You can now add a new Python interpreter directly from the interpreter widget in DataSpell's status bar. Open the widget, select the relevant directory, and then a popup will open with an option to add a new interpreter.
  • New UI
    • New UI - Added a new UI designed to reduce visual complexity, provide easy access to essential features, and progressively disclose complex functionality. The new UI has a simplified main toolbar, a new tool window layout, an updated icon set, new light and dark color themes, and more.
DataSpell 2023.1
Manage multiple separate projects

DataSpell（英語版）

プロフェッショナルなデータサイエンティスト向けのIDE

見積もりの依頼 購入

DataSpell（英語版）は、次の製品にも含まれています。

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