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## Overview
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When working with code and data, you will encounter data and files in a wide
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-variety of formats. JupyterLab provides a unified architecture for working with
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-data. This model applies whether the data is in a file, or is provided by a
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-Kernel as output in a notebook or code console.
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+variety of formats. JupyterLab provides a unified architecture for viewing and editing
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+data. This model applies whether the data is in a file or is provided by a
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+kernel as rich output in a notebook or code console.
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For files, the data format is detected by the extension of the file. A single
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file extension may have multiple editors or viewers registered. For example a
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-Markdown file (`.md`) can be edited in the File Editor, or rendered inline.
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+Markdown file (`.md`) can be edited in the file editor or rendered and displayed
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+as HTML.
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-You can access different editors and viewers for a file, by right-clicking on
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-the filename in the File Browser and using the "Open With..." submenu:
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+You can open different editors and viewers for a file by right-clicking on
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+the filename in the file browser and using the "Open With..." submenu:
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[screenshot]
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-To use these different data formats as output in the Notebook or Code Console,
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+To use these different data formats as output in a notebook or code console,
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you can use the relevant display API for the kernel you are using. For example,
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the IPython kernel provides a `display` function that takes a `dict` of keys
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-(MIME types) and value (MIME data):
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+(MIME types) and values (MIME data):
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```python
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from IPython.display import display
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@@ -32,7 +33,7 @@ console:
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[screenshot]
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-Other Jupyter Kernels offer similar APIs.
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+Other Jupyter kernels offer similar APIs.
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## Markdown
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@@ -47,23 +48,23 @@ Markdown documents can be edited as text files or rendered inline:
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[animation]
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The markdown syntax supported in this mode is the same as that in the Jupyter
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-Notebook (LaTeX equations work). As seen in the animation, edits to the markdown
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-source are immediately reflected in the rendered version:
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+Notebook (LaTeX equations work). As seen in the animation, edits to the Markdown
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+source are immediately reflected in the rendered version.
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## Images
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* File format: `.png`, `.jpeg`, `.gif`
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* MIME type: `image/png`, `image/jpeg`, `image/gif`
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-JupyterLab supports image data as files and output in the above formats.
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+JupyterLab supports image data as files and output in the above formats. In the image file viewer, you can use keyboard shortcuts such as `+` and `-` to zoom the image and `0` to reset the zoom level.
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## HTML
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-* File format: edit as text file
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+* File format: `.html`
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* MIME type: `text/html`
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JupyterLab supports rendered HTML in output. HTML files can be edited as text
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-files in the File Editor.
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+files in the file editor.
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## SVG
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@@ -71,20 +72,20 @@ files in the File Editor.
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* MIME type: `image/svg+xml`
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JupyterLab will render Scalable Vector Graphics (SVG) in files and output. SVG
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-files can slso be edited as text files in the File Editor.
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+files can slso be edited as text files in the file editor.
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## LaTeX
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-* File format: edit as text file
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+* File format: `.tex`
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* MIME type: `text/latex`
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JupyterLab will render LaTeX questions in output, and LaTeX files (`.tex`) can
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-be edited as text files in the File Editor.
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+be edited as text files in the file editor.
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## JSON
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* File format: `.json`
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-* MIME type: `application+json`
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+* MIME type: `application/binary+json`
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JavaScript Object Notation (JSON) files are common in data science.
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@@ -92,7 +93,7 @@ The default viewer for JSON files is a searchable tree view:
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[animation]
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-To edit the JSON as a text file, right-click on the file in the File Browser and
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+To edit the JSON as a text file, right-click on the file in the file browser and
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select the “Editor” item in the “Open With…” submenu:
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[animation]
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@@ -102,16 +103,15 @@ select the “Editor” item in the “Open With…” submenu:
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* File format: `.csv`
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* MIME type: None
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-Files with rows of Comma Separate Values (with a `.csv` extension) are a common
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+Files with rows of Comma-Separated Values (with a `.csv` extension) are a common
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format for tabular data.
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The default viewer for CSV files in JupyterLab is a high performance data grid
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-viewer. To view a CSV file in the interactive Data Grid, double-click on the
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-file in the File Browser:
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+viewer:
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[animation]
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-To edit a CSV file as a text file, right-click on the file in the File Browser
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+To edit a CSV file as a text file, right-click on the file in the file browser
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and select the “Editor” item in the “Open With…” submenu:
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[animation]
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@@ -121,9 +121,9 @@ and select the “Editor” item in the “Open With…” submenu:
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* File format: `.pdf`
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* MIME type: `application/pdf`
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-PDF files (`.pdf` extension) are a common and standard file format for
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+PDF files are a common standard file format for
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documents. To view a PDF file in JupyterLab, double-click on the file in the
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-File Browser:
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+file browser:
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[animation]
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@@ -141,22 +141,22 @@ Vega-Lite:
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* MIME type: `application/vnd.vegalite.v1+json`
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Vega and Vega-Lite are declarative visualization grammars that allow
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-visualizations to be encoded as JSON data. Fro more information see the
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+visualizations to be encoded as JSON data. For more information, see the
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documentation of Vega or Vega-Lite. JupyterLab has built-in rendering support
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for Vega 2.x and Vega-Lite 1.x data. This support works for both files and
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output in the Notebook and Code Console.
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Vega-Lite 1.x files, with a `.vl` or `.vl.json` file extension, can be opened by
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-double-clicking he file in the File Browser:
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+double-clicking the file in the File Browser:
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[animation]
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-The files can also be opened in the JSON viewer or File Editor through the “Open
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-With…” submenu in the File Browser content menu:
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+The files can also be opened in the JSON viewer or file editor through the “Open
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+With…” submenu in the file browser content menu:
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[animation]
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-As with other files in JupyterLab multiple views of a single file remain
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+As with other files in JupyterLab, multiple views of a single file remain
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synchronized, allowing you to interactively edit and render Vega-Lite/Vega
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visualizations:
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@@ -165,7 +165,7 @@ visualizations:
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The same workflow also works for Vega 2.x files, with a `.vg` or `.vg.json` file
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extension.
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-Output support for Vega/Vega-Lite in the Notebook or Code Console is provided
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+Output support for Vega/Vega-Lite in a notebook or code console is provided
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through third party libraries such as Altair (Python), the vegalite R package,
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or Vegas (Scala/Spark).
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@@ -193,4 +193,4 @@ Here is an example of a `.vdom` files being edited and rendered interactively:
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The [nteract/vdom](https://github.com/nteract/vdom) library provides a Python
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API for creating VDOM output that is rendered in nteract and JupyterLab:
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-[screenshot or animation]
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+[screenshot or animation]
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