Line notebook: Amazon.com : Amazon Basics Classic Notebook, 240 Pages, Hardcover

Содержание

Use notebooks | Databricks on AWS

A notebook is a collection of runnable cells (commands). When you use a notebook, you are primarily developing and running cells.

All notebook tasks are supported by UI actions, but you can also perform many tasks using keyboard shortcuts. Toggle the shortcut display by clicking the icon.

Develop notebooks

This section describes how to develop notebook cells and navigate around a notebook.

Add a cell

To add a cell, mouse over a cell at the top or bottom and click the icon, or access the notebook cell menu at the far right, click , and select Add Cell Above or Add Cell Below.

Delete a cell

Go to the cell actions menu at the far right and click (Delete).

When you delete a cell, by default a delete confirmation dialog displays. To disable future confirmation dialogs, select the Do not show this again checkbox and click Confirm. You can also toggle the confirmation dialog setting with the Turn on command delete confirmation option in > User Settings > Notebook Settings.

To restore deleted cells, either select Edit > Undo Delete Cells or use the (Z) keyboard shortcut.

Cut a cell

Go to the cell actions menu at the far right, click , and select Cut Cell.

You can also use the (X) keyboard shortcut.

To restore deleted cells, either select Edit > Undo Cut Cells or use the (Z) keyboard shortcut.

Select multiple cells or all cells

You can select adjacent notebook cells using Shift + Up or Down for the previous and next cell respectively. Multi-selected cells can be copied, cut, deleted, and pasted.

To select all cells, select Edit > Select All Cells or use the command mode shortcut Cmd+A.

Default language

The notebook’s default language is indicated by a button next to the notebook name. In the following notebook, the default language is SQL.

To change the default language:

  1. Click the language button. The Change Default Language dialog displays.

  2. Select the new language from the Default Language drop-down.

  3. Click Change.

  4. To ensure that existing commands continue to work, commands of the previous default language are automatically prefixed with a language magic command.

Mix languages

By default, cells use the default language of the notebook. You can override the default language in a cell by clicking the language button and selecting a language from the drop down.

Alternately, you can use the language magic command %<language> at the beginning of a cell. The supported magic commands are: %python, %r, %scala, and %sql.

Note

When you invoke a language magic command, the command is dispatched to the REPL in the execution context for the notebook. Variables defined in one language (and hence in the REPL for that language) are not available in the REPL of another language. REPLs can share state only through external resources such as files in DBFS or objects in object storage.

Notebooks also support a few auxiliary magic commands:

  • %sh: Allows you to run shell code in your notebook. To fail the cell if the shell command has a non-zero exit status, add the -e option. This command runs only on the Apache Spark driver, and not the workers. To run a shell command on all nodes, use an init script.
  • %fs: Allows you to use dbutils filesystem commands. For example, to run the dbutils.fs.ls command to list files, you can specify %fs ls instead. For more information, see Use %fs magic commands.
  • %md: Allows you to include various types of documentation, including text, images, and mathematical formulas and equations. See the next section.

Include documentation

To include documentation in a notebook you can create a markdown cell, either by selecting Markdown from the cell’s language button or by using the %md magic command. The contents of the cell are rendered into HTML. For example, this snippet contains markup for a level-one heading:

%md # Hello This is a Title

It is rendered as a HTML title:

Collapsible headings

Cells that appear after cells containing Markdown headings can be collapsed into the heading cell. The following image shows a level-one heading called Heading 1 with the following two cells collapsed into it.

To expand and collapse headings, click the + and .

Also see Hide and show cell content.

To expand or collapse cells after cells containing Markdown headings throughout the notebook, select Expland all headings or Collapse all headings from the View menu.

Link to other notebooks

You can link to other notebooks or folders in Markdown cells using relative paths. Specify the href
attribute of an anchor tag as the relative path, starting with a $ and then follow the same
pattern as in Unix file systems:

%md
<a href="$./myNotebook">Link to notebook in same folder as current notebook</a>
<a href="$../myFolder">Link to folder in parent folder of current notebook</a>
<a href="$./myFolder2/myNotebook2">Link to nested notebook</a>
Display images

To display images stored in the FileStore, use the syntax:

%md
![test](files/image.png)

For example, suppose you have the Databricks logo image file in FileStore:

databricks-logo-mobile.png

When you include the following code in a Markdown cell:

the image is rendered in the cell:

Display mathematical equations

Notebooks support KaTeX for displaying mathematical formulas and equations. {-1}\delta\\)

where \\(\delta=(\beta – \mu_{t-1})\\)

renders as:

Include HTML

You can include HTML in a notebook by using the function displayHTML. See HTML, D3, and SVG in notebooks for an example of how to do this.

Note

The displayHTML iframe is served from the domain databricksusercontent.com and the iframe sandbox includes the allow-same-origin attribute. databricksusercontent.com must be accessible from your browser. If it is currently blocked by your corporate network, it must added to an allow list.

Change cell display

There are three display options for notebooks:

  • Standard view: results are displayed immediately after code cells
  • Results only: only results are displayed
  • Side-by-side: code and results cells are displayed side by side, with results to the right

Go to the View menu to select your display option.

Show line and command numbers

To show line numbers or command numbers, go to the View menu and select Show line numbers or Show command numbers. Once they’re displayed, you can hide them again from the same menu. You can also enable line numbers with the keyboard shortcut Control+L.

If you enable line or command numbers, Databricks saves your preference and shows them in all of your other notebooks for that browser.

Command numbers above cells link to that specific command. If you click the command number for a cell, it updates your URL to be anchored to that command. If you want to link to a specific command in your notebook, right-click the command number and choose copy link address.

Find and replace text

To find and replace text within a notebook, select Edit > Find and Replace. The current match is highlighted in orange and all other matches are highlighted in yellow.

To replace the current match, click Replace. To replace all matches in the notebook, click Replace All.

To move between matches, click the Prev and Next buttons. You can also press
shift+enter and enter to go to the previous and next matches, respectively.

To close the find and replace tool, click or press esc.

Autocomplete

You can use Databricks autocomplete to automatically complete code segments as you type them. Databricks supports two types of autocomplete: local and server.

Local autocomplete completes words that are defined in the notebook. Server autocomplete accesses the cluster for defined types, classes, and objects, as well as SQL database and table names. To activate server autocomplete, attach your notebook to a cluster and run all cells that define completable objects.

Important

Server autocomplete in R notebooks is blocked during command execution.

To trigger autocomplete, press Tab after entering a completable object. For example, after you define and run the cells containing the definitions of MyClass and instance, the methods of instance are completable, and a list of valid completions displays when you press Tab.

Type completion and SQL database and table name completion work in the same way.

— —

In Databricks Runtime 7.4 and above, you can display Python docstring hints by pressing Shift+Tab after entering a completable Python object. The docstrings contain the same information as the help() function for an object.

Format SQL

Databricks provides tools that allow you to format SQL code in notebook cells quickly and easily. These tools reduce the effort to keep your code formatted and help to enforce the same coding standards across your notebooks.

You can trigger the formatter in the following ways:

  • Single cells

    • Keyboard shortcut: Press Cmd+Shift+F.

    • Command context menu: Select Format SQL in the command context drop-down menu of a SQL cell. This item is visible only in SQL notebook cells and those with a %sql language magic.

  • Multiple cells

    Select multiple SQL cells and then select Edit > Format SQL Cells. If you select cells of more than one language, only SQL cells are formatted. This includes those that use %sql.

Here’s the first cell in the preceding example after formatting:

View table of contents

To display an automatically generated table of contents, click the arrow at the upper left of the notebook (between the sidebar and the topmost cell). The table of contents is generated from the Markdown headings used in the notebook.

To close the table of contents, click the left-facing arrow.

View notebooks in dark mode

You can choose to display notebooks in dark mode. To turn dark mode on or off, select View > Notebook Theme and select Light Theme or Dark Theme.

Run notebooks

This section describes how to run one or more notebook cells.

Requirements

The notebook must be attached to a cluster. If the cluster is not running, the cluster is started when you run one or more cells.

Run a cell

In the cell actions menu at the far right, click and select Run Cell, or press shift+enter.

Important

The maximum size for a notebook cell, both contents and output, is 16MB.

For example, try running this Python code snippet that references the predefined spark variable.

and then, run some real code:

Note

Notebooks have a number of default settings:

  • When you run a cell, the notebook automatically attaches to a running cluster without prompting.
  • When you press shift+enter, the notebook auto-scrolls to the next cell if the cell is not visible.

To change these settings, select > User Settings > Notebook Settings and configure the respective checkboxes.

Run all above or below

To run all cells before or after a cell, go to the cell actions menu at the far right, click , and select Run All Above or Run All Below.

Run All Below includes the cell you are in. Run All Above does not.

Run all cells

To run all the cells in a notebook, select Run All in the notebook toolbar.

Important

Do not do a Run All if steps for mount and unmount are in the same notebook. It could lead to a race condition and possibly corrupt the mount points.

View multiple outputs per cell

Python notebooks and %python cells in non-Python notebooks support multiple outputs per cell.

This feature requires Databricks Runtime 7.1 or above and can be enabled in Databricks Runtime 7. 1 – Databricks Runtime 7.3 by setting spark.databricks.workspace.multipleResults.enabled true.
It is enabled by default in Databricks Runtime 7.4 and above.

Python and Scala error highlighting

Python and Scala notebooks support error highlighting. That is, the line of code that
is throwing the error will be highlighted in the cell. Additionally, if the error output is a stacktrace,
the cell in which the error is thrown is displayed in the stacktrace as a link to the cell. You can click this link to jump to the offending code.

Notifications

Notifications alert you to certain events, such as which command is currently running during Run all cells and which commands are in error state. When your notebook is showing multiple error notifications, the first one will have a link that allows you to clear all notifications.

Notebook notifications are enabled by default. You can disable them under > User Settings > Notebook Settings.

Databricks Advisor

Databricks Advisor automatically analyzes commands every time they are run and displays appropriate advice in the notebooks. The advice notices provide information that can assist you in improving the performance of workloads, reducing costs, and avoiding common mistakes.

View advice

A blue box with a lightbulb icon signals that advice is available for a command. The box displays the number of distinct pieces of advice.

Click the lightbulb to expand the box and view the advice. One or more pieces of advice will become visible.

Click the Learn more link to view documentation providing more information related to the advice.

Click the Don’t show me this again link to hide the piece of advice. The advice of this type will no longer be displayed. This action can be reversed in Notebook Settings.

Click the lightbulb again to collapse the advice box.

Advice settings

Access the Notebook Settings page by selecting > User Settings > Notebook Settings or by clicking the gear icon in the expanded advice box.

Toggle the Turn on Databricks Advisor option to enable or disable advice.

The Reset hidden advice link is displayed if one or more types of advice is currently hidden. Click the link to make that advice type visible again.

Run a notebook from another notebook

You can run a notebook from another notebook by using the %run <notebook> magic command. This is roughly equivalent to a :load command in a Scala REPL on your local machine or an import statement in Python. All variables defined in <notebook> become available in your current notebook.

%run must be in a cell by itself, because it runs the entire notebook inline.

Note

You cannot use %run to run a Python file and import the entities defined in that file into a notebook. To import from a Python file you must package the file into a Python library, create a Databricks library from that Python library, and install the library into the cluster you use to run your notebook.

Example

Suppose you have notebookA and notebookB. notebookA contains a cell that has the following Python code:

Even though you did not define x in notebookB, you can access x in notebookB after you run %run notebookA.

%run /Users/path/to/notebookA

print(x) # => 5

To specify a relative path, preface it with ./ or ../. For example, if notebookA and notebookB are in the same directory, you can alternatively run them from a relative path.

%run ./notebookA

print(x) # => 5
%run ../someDirectory/notebookA # up a directory and into another

print(x) # => 5

For more complex interactions between notebooks, see Notebook workflows.

Manage notebook state and results

After you attach a notebook to a cluster and run one or more cells, your notebook has state and displays results. This section describes how to manage notebook state and results.

Download a cell result

You can download a cell result that contains tabular output to your local machine. Click the button at the bottom of a cell.

A CSV file named export.csv is downloaded to your default download directory.

Hide and show cell content

Cell content consists of cell code and the result of running the cell. You can hide and show the cell code and result using the cell actions menu at the top right of the cell.

To hide cell code:

  • Click and select Hide Code

To hide and show the cell result, do any of the following:

  • Click and select Hide Result
  • Select
  • Type Esc > Shift + o

To show hidden cell code or results, click the Show links:

See also Collapsible headings.

Notebook isolation

Notebook isolation refers to the visibility of variables and classes between notebooks. Databricks supports two types of isolation:

  • Variable and class isolation
  • Spark session isolation

Note

Since all notebooks attached to the same cluster execute on the same cluster VMs, even with Spark session isolation enabled there is no guaranteed user isolation within a cluster.

Variable and class isolation

Variables and classes are available only in the current notebook. For example, two notebooks attached to the same cluster can define variables and classes with the same name, but these objects are distinct.

To define a class that is visible to all notebooks attached to the same cluster, define the class in a package cell. Then you can access the class by using its fully qualified name, which is the same as accessing a class in an attached Scala or Java library.

Spark session isolation

Every notebook attached to a cluster running Apache Spark 2.0.0 and above has a pre-defined variable called spark that represents a SparkSession. SparkSession is the entry point for using Spark APIs as well as setting runtime configurations.

Spark session isolation is enabled by default. You can also use global temporary views to share temporary views across notebooks. See Create View or CREATE VIEW. To disable Spark session isolation, set spark.databricks.session.share to true in the Spark configuration.

Important

Setting spark.databricks.session.share true breaks the monitoring used by both streaming notebook cells and streaming jobs. Specifically:

  • The graphs in streaming cells are not displayed.
  • Jobs do not block as long as a stream is running (they just finish “successfully”, stopping the stream).
  • Streams in jobs are not monitored for termination. Instead you must manually call awaitTermination().
  • Calling the display function on streaming DataFrames doesn’t work.

Cells that trigger commands in other languages (that is, cells using %scala, %python, %r, and %sql) and cells that include other notebooks (that is, cells using %run) are part of the current notebook. Thus, these cells are in the same session as other notebook cells. By contrast, a notebook workflow runs a notebook with an isolated SparkSession, which means temporary views defined in such a notebook are not visible in other notebooks.

Getting started with Anaconda — Anaconda documentation

Anaconda Individual Edition contains conda
and Anaconda Navigator,
as well as Python and hundreds of scientific
packages. When you installed Anaconda,
you installed all these too.

Conda works on your command line interface such as
Anaconda Prompt on Windows and terminal on macOS and Linux.

Navigator is a desktop graphical user interface that
allows you to launch applications and easily manage
conda packages, environments, and channels without
using command-line commands.

You can try both conda and Navigator
to see which is right for you to manage your packages and
environments. You can even switch between them, and the work you
do with one can be viewed in the other.

Try this simple programming exercise, with Navigator and the
command line, to help you decide which approach is right for you.

When you’re done, see What’s next?.

Your first Python program: Hello, Anaconda!

Use Anaconda Navigator to launch an application. Then, create and run
a simple Python program with Spyder and Jupyter Notebook.

Open Navigator

Choose the instructions for your operating system.

Windows

From the Start menu, click the Anaconda Navigator desktop app.

macOS

Open Launchpad, then click the Anaconda Navigator icon.

Linux

Open a terminal window and type anaconda-navigator.

Run Python in Spyder IDE (integrated development environment)

Tip

Navigator’s Home screen displays several applications for you to
choose from. For more information, see links at the bottom of this page.

  1. On Navigator’s Home tab, in the Applications pane on the right, scroll
    to the Spyder tile and click the Install button to install Spyder.

    Note

    If you already have Spyder installed, you can jump right to the
    Launch step.

  2. Launch Spyder by clicking Spyder’s Launch button.

  3. In the new file on the left, delete any placeholder text, then type or
    copy/paste print("Hello Anaconda").

  4. In the top menu, click File – Save As and name your new program
    hello.py.

  5. Run your new program by clicking the triangle Run button.

  6. You can see your program’s output in the bottom right Console pane.

Close Spyder

From Spyder’s top menu bar, select Spyder – Quit Spyder (In macOS,
select Python – Quit Spyder).

Run Python in a Jupyter Notebook

  1. On Navigator’s Home tab, in the Applications pane on the right, scroll
    to the Jupyter Notebook tile and click the Install button to install Jupyter
    Notebook.

    Note

    If you already have Jupyter Notebook installed, you can jump right to
    the Launch step.

  2. Launch Jupyter Notebook by clicking Jupyter Notebook’s Launch button.

    This will launch a new browser window (or a new tab) showing the
    Notebook Dashboard.

  3. On the top of the right hand side, there is a dropdown menu labeled “New”.
    Create a new Notebook with the Python version you installed.

  4. Rename your Notebook. Either click on the current name and edit it or
    find rename under File in the top menu bar.
    You can name it to whatever you’d like, but for this example we’ll use
    MyFirstAnacondaNotebook.

  5. In the first line of the Notebook, type or copy/paste
    print("Hello Anaconda").

  6. Save your Notebook by either clicking the save and checkpoint
    icon or select File – Save and Checkpoint in the top menu.

  7. Run your new program by clicking the Run button or selecting
    Cell – Run All from the top menu.

Close Jupyter Notebook

  1. From Jupyter Notebooks top menu bar, select File – Close and Halt.
  2. Click the Quit button at the upper right of the Notebook Dashboard
    and close the window or tab.

Close Navigator

From Navigator’s top menu bar, select Anaconda Navigator – Quit
Anaconda-Navigator.

Write a Python program using Anaconda Prompt or terminal

Open Anaconda Prompt

Choose the instructions for your operating system.

Windows

From the Start menu, search for and open “Anaconda Prompt”:

macOS

Open Launchpad, then click the terminal icon.

Linux

Open a terminal window.

Start Python

At Anaconda Prompt (terminal on Linux or macOS), type python
and press Enter.

The >>> means you are in Python.

Write a Python program

At the >>>, type print("Hello Anaconda!") and press Enter.

When you press enter, your program runs. The words “Hello Anaconda!” print to
the screen. You’re programming in Python!

Exit Python

On Windows, press CTRL-Z and press Enter. On macOS or Linux type
exit() and press Enter.

Optional: Launch Spyder or Jupyter Notebook from the command line

  1. At the Anaconda Prompt (terminal on Linux or macOS), type spyder
    and press Enter.
    Spyder should start up just like it did when you launched it
    from Anaconda Navigator.
  2. Close Spyder the same way you did in the previous exercise.
  3. At the Anaconda Prompt (terminal on Linux or macOS), type
    jupyter-notebook and press Enter.

Jupyter Notebook should start up just like it did when you launched
it from Anaconda Navigator. Close it the same way you did in the
previous exercise.

What’s next?

Links to IDE documentation

MaxiAids | Low Vision Notebook

Manufacturer:
DO MORE


Bold Lines Make Writing Notes Easier

  • Includes 70 sheets
  • Bold black lines are 0. 75 in. (3/4-inch) apart and printed on both sides
  • Measures 8.5 in. x 11 in.



SKU: 71998
Weight:
Length:
Width:
Height:
Availability:


List Price::
$7. 95


Our Price:


$6.95







You Save:


$1.00 (12%)


Availability:

Usually ships within 1 to 2 business days

Use notebooks – Azure Databricks





  • 18 minutes to read


Is this page helpful?

Please rate your experience




Yes



No



Any additional feedback?

Feedback will be sent to Microsoft: By pressing the submit button, your feedback will be used to improve Microsoft products and services. Privacy policy.


Submit



In this article

A notebook is a collection of runnable cells (commands). When you use a notebook, you are primarily developing and running cells.

All notebook tasks are supported by UI actions, but you can also perform many tasks using keyboard shortcuts. Toggle the shortcut display by clicking the icon.

Develop notebooks

This section describes how to develop notebook cells and navigate around a notebook.

In this section:

About notebooks

A notebook has a toolbar that lets you manage the notebook and perform actions within the notebook:

and one or more cells (or commands) that you can run:

At the far right of a cell, the cell actions , contains three menus: Run, Dashboard, and Edit:

— —

and two actions: Hide and Delete .

Add a cell

To add a cell, mouse over a cell at the top or bottom and click the icon, or access the notebook cell menu at the far right, click , and select Add Cell Above or Add Cell Below.

Delete a cell

Go to the cell actions menu at the far right and click (Delete).

When you delete a cell, by default a delete confirmation dialog displays. To disable future confirmation dialogs, select the Do not show this again checkbox and click Confirm. You can also toggle the confirmation dialog setting with the Turn on command delete confirmation option in > User Settings > Notebook Settings.

To restore deleted cells, either select Edit > Undo Delete Cells or use the (Z) keyboard shortcut.

Cut a cell

Go to the cell actions menu at the far right, click , and select Cut Cell.

You can also use the (X) keyboard shortcut.

To restore deleted cells, either select Edit > Undo Cut Cells or use the (Z) keyboard shortcut.

Select multiple cells or all cells

You can select adjacent notebook cells using Shift + Up or Down for the previous and next cell respectively. Multi-selected cells can be copied, cut, deleted, and pasted.

To select all cells, select Edit > Select All Cells or use the command mode shortcut Cmd+A.

Default language

The notebook’s default language is indicated by a button next to the notebook name. In the following notebook, the default language is SQL.

To change the default language:

  1. Click the language button. The Change Default Language dialog displays.

  2. Select the new language from the Default Language drop-down.

  3. Click Change.

  4. To ensure that existing commands continue to work, commands of the previous default language are automatically prefixed with a language magic command.

Mix languages

By default, cells use the default language of the notebook. You can override the default language in a cell by clicking the language button and selecting a language from the drop down.

Alternately, you can use the language magic command %<language> at the beginning of a cell. The supported magic commands are: %python, %r, %scala, and %sql.

Note

When you invoke a language magic command, the command is dispatched to the REPL in the execution context for the notebook. Variables defined in one language (and hence in the REPL for that language) are not available in the REPL of another language. REPLs can share state only through external resources such as files in DBFS or objects in object storage.

Notebooks also support a few auxiliary magic commands:

  • %sh: Allows you to run shell code in your notebook. To fail the cell if the shell command has a non-zero exit status, add the -e option. This command runs only on the Apache Spark driver, and not the workers. To run a shell command on all nodes, use an init script.
  • %fs: Allows you to use dbutils filesystem commands. For example, to run the dbutils.fs.ls command to list files, you can specify %fs ls instead. For more information, see Use %fs magic commands.
  • %md: Allows you to include various types of documentation, including text, images, and mathematical formulas and equations. See the next section.

Include documentation

To include documentation in a notebook you can create a markdown cell, either by selecting Markdown from the cell’s language button or by using the %md magic command. The contents of the cell are rendered into HTML. For example, this snippet contains markup for a level-one heading:

%md # Hello This is a Title

It is rendered as a HTML title:

Collapsible headings

Cells that appear after cells containing Markdown headings can be collapsed into the heading cell. The following image shows a level-one heading called Heading 1 with the following two cells collapsed into it.

To expand and collapse headings, click the + and .

Also see Hide and show cell content.

To expand or collapse cells after cells containing Markdown headings throughout the notebook, select Expland all headings or Collapse all headings from the View menu.

Link to other notebooks

You can link to other notebooks or folders in Markdown cells using relative paths. Specify the href
attribute of an anchor tag as the relative path, starting with a $ and then follow the same
pattern as in Unix file systems:

%md
<a href="$. {-1}\delta\\)

where \\(\delta=(\beta - \mu_{t-1})\\)

renders as:

Include HTML

You can include HTML in a notebook by using the function displayHTML. See HTML, D3, and SVG in notebooks for an example of how to do this.

Note

The displayHTML iframe is served from the domain databricksusercontent.com and the iframe sandbox includes the allow-same-origin attribute. databricksusercontent.com must be accessible from your browser. If it is currently blocked by your corporate network, it must added to an allow list.

Command comments

You can have discussions with collaborators using command comments.

To toggle the Comments sidebar, click the Comments button at the top right of a notebook.

To add a comment to a command:

  1. Highlight the command text and click the comment bubble:

  2. Add your comment and click Comment.

To edit, delete, or reply to a comment, click the comment and choose an action.

Change cell display

There are three display options for notebooks:

  • Standard view: results are displayed immediately after code cells
  • Results only: only results are displayed
  • Side-by-side: code and results cells are displayed side by side, with results to the right

Go to the View menu to select your display option.

Show line and command numbers

To show line numbers or command numbers, go to the View menu and select Show line numbers or Show command numbers. Once they’re displayed, you can hide them again from the same menu. You can also enable line numbers with the keyboard shortcut Control+L.

If you enable line or command numbers, Databricks saves your preference and shows them in all of your other notebooks for that browser.

Command numbers above cells link to that specific command. If you click the command number for a cell, it updates your URL to be anchored to that command. If you want to link to a specific command in your notebook, right-click the command number and choose copy link address.

Find and replace text

To find and replace text within a notebook, select Edit > Find and Replace. The current match is highlighted in orange and all other matches are highlighted in yellow.

To replace the current match, click Replace. To replace all matches in the notebook, click Replace All.

To move between matches, click the Prev and Next buttons. You can also press
shift+enter and enter to go to the previous and next matches, respectively.

To close the find and replace tool, click or press esc.

Autocomplete

You can use Azure Databricks autocomplete to automatically complete code segments as you type them. Azure Databricks supports two types of autocomplete: local and server.

Local autocomplete completes words that are defined in the notebook. Server autocomplete accesses the cluster for defined types, classes, and objects, as well as SQL database and table names. To activate server autocomplete, attach your notebook to a cluster and run all cells that define completable objects.

Important

Server autocomplete in R notebooks is blocked during command execution.

To trigger autocomplete, press Tab after entering a completable object. For example, after you define and run the cells containing the definitions of MyClass and instance, the methods of instance are completable, and a list of valid completions displays when you press Tab.

Type completion and SQL database and table name completion work in the same way.

— —

In Databricks Runtime 7.4 and above, you can display Python docstring hints by pressing Shift+Tab after entering a completable Python object. The docstrings contain the same information as the help() function for an object.

Format SQL

Azure Databricks provides tools that allow you to format SQL code in notebook cells quickly and easily. These tools reduce the effort to keep your code formatted and help to enforce the same coding standards across your notebooks.

You can trigger the formatter in the following ways:

  • Single cells

    • Keyboard shortcut: Press Cmd+Shift+F.

    • Command context menu: Select Format SQL in the command context drop-down menu of a SQL cell. This item is visible only in SQL notebook cells and those with a %sql language magic.

  • Multiple cells

    Select multiple SQL cells and then select Edit > Format SQL Cells. If you select cells of more than one language, only SQL cells are formatted. This includes those that use %sql.

Here’s the first cell in the preceding example after formatting:

View table of contents

To display an automatically generated table of contents, click the arrow at the upper left of the notebook (between the sidebar and the topmost cell). The table of contents is generated from the Markdown headings used in the notebook.

To close the table of contents, click the left-facing arrow.

View notebooks in dark mode

You can choose to display notebooks in dark mode. To turn dark mode on or off, select View > Notebook Theme and select Light Theme or Dark Theme.

Run notebooks

This section describes how to run one or more notebook cells.

In this section:

Requirements

The notebook must be attached to a cluster. If the cluster is not running, the cluster is started when you run one or more cells.

Run a cell

In the cell actions menu at the far right, click and select Run Cell, or press shift+enter.

Important

The maximum size for a notebook cell, both contents and output, is 16MB.

For example, try running this Python code snippet that references the predefined spark variable.

spark

and then, run some real code:

1+1 # => 2

Note

Notebooks have a number of default settings:

  • When you run a cell, the notebook automatically attaches to a running cluster without prompting.
  • When you press shift+enter, the notebook auto-scrolls to the next cell if the cell is not visible.

To change these settings, select > User Settings > Notebook Settings and configure the respective checkboxes.

Run all above or below

To run all cells before or after a cell, go to the cell actions menu at the far right, click , and select Run All Above or Run All Below.

Run All Below includes the cell you are in. Run All Above does not.

Run all cells

To run all the cells in a notebook, select Run All in the notebook toolbar.

Important

Do not do a Run All if steps for mount and unmount are in the same notebook. It could lead to a race condition and possibly corrupt the mount points.

View multiple outputs per cell

Python notebooks and %python cells in non-Python notebooks support multiple outputs per cell.

This feature requires Databricks Runtime 7.1 or above and can be enabled in Databricks Runtime 7.1 – Databricks Runtime 7.3 by setting spark.databricks.workspace.multipleResults.enabled true.
It is enabled by default in Databricks Runtime 7.4 and above.

Python and Scala error highlighting

Python and Scala notebooks support error highlighting. That is, the line of code that
is throwing the error will be highlighted in the cell. Additionally, if the error output is a stacktrace,
the cell in which the error is thrown is displayed in the stacktrace as a link to the cell. You can click this link to jump to the offending code.

Notifications

Notifications alert you to certain events, such as which command is currently running during Run all cells and which commands are in error state. When your notebook is showing multiple error notifications, the first one will have a link that allows you to clear all notifications.

Notebook notifications are enabled by default. You can disable them under > User Settings > Notebook Settings.

Databricks Advisor

Databricks Advisor automatically analyzes commands every time they are run and displays appropriate advice in the notebooks. The advice notices provide information that can assist you in improving the performance of workloads, reducing costs, and avoiding common mistakes.

View advice

A blue box with a lightbulb icon signals that advice is available for a command. The box displays the number of distinct pieces of advice.

Click the lightbulb to expand the box and view the advice. One or more pieces of advice will become visible.

Click the Learn more link to view documentation providing more information related to the advice.

Click the Don’t show me this again link to hide the piece of advice. The advice of this type will no longer be displayed. This action can be reversed in Notebook Settings.

Click the lightbulb again to collapse the advice box.

Advice settings

Access the Notebook Settings page by selecting > User Settings > Notebook Settings or by clicking the gear icon in the expanded advice box.

Toggle the Turn on Databricks Advisor option to enable or disable advice.

The Reset hidden advice link is displayed if one or more types of advice is currently hidden. Click the link to make that advice type visible again.

Run a notebook from another notebook

You can run a notebook from another notebook by using the %run <notebook> magic command. This is roughly equivalent to a :load command in a Scala REPL on your local machine or an import statement in Python. All variables defined in <notebook> become available in your current notebook.

%run must be in a cell by itself, because it runs the entire notebook inline.

Note

You cannot use %run to run a Python file and import the entities defined in that file into a notebook. To import from a Python file you must package the file into a Python library, create an Azure Databricks library from that Python library, and install the library into the cluster you use to run your notebook.

Example

Suppose you have notebookA and notebookB. notebookA contains a cell that has the following Python code:

x = 5

Even though you did not define x in notebookB, you can access x in notebookB after you run %run notebookA.

%run /Users/path/to/notebookA

print(x) # => 5

To specify a relative path, preface it with ./ or ../. For example, if notebookA and notebookB are in the same directory, you can alternatively run them from a relative path.

%run ./notebookA

print(x) # => 5
%run ../someDirectory/notebookA # up a directory and into another

print(x) # => 5

For more complex interactions between notebooks, see Notebook workflows.

Manage notebook state and results

After you attach a notebook to a cluster and run one or more cells, your notebook has state and displays results. This section describes how to manage notebook state and results.

In this section:

Clear notebooks state and results

To clear the notebook state and results, click Clear in the notebook toolbar and select the action:

Download results

By default downloading results is enabled. To toggle this setting, see Manage the ability to download results from notebooks. If downloading results is disabled, the button is not visible.

Download a cell result

You can download a cell result that contains tabular output to your local machine. Click the button at the bottom of a cell.

A CSV file named export.csv is downloaded to your default download directory.

Download full results

By default Azure Databricks returns 1000 rows of a DataFrame. When there are more than 1000 rows, an option appears to re-run the query and display up to 10,000 rows.

When a query returns more than 1000 rows, a down arrow is added to the button. To download all the results of a query:

  1. Click the down arrow next to and select Download full results.

  2. Select Re-execute and download.

    After you download full results, a CSV file named export. csv is downloaded to your local machine and the /databricks-results folder has a generated folder containing full the query results.

Hide and show cell content

Cell content consists of cell code and the result of running the cell. You can hide and show the cell code and result using the cell actions menu at the top right of the cell.

To hide cell code:

  • Click and select Hide Code

To hide and show the cell result, do any of the following:

  • Click and select Hide Result
  • Select
  • Type Esc > Shift + o

To show hidden cell code or results, click the Show links:

See also Collapsible headings.

Notebook isolation

Notebook isolation refers to the visibility of variables and classes between notebooks. Azure Databricks supports two types of isolation:

  • Variable and class isolation
  • Spark session isolation

Note

Since all notebooks attached to the same cluster execute on the same cluster VMs, even with Spark session isolation enabled there is no guaranteed user isolation within a cluster.

Variable and class isolation

Variables and classes are available only in the current notebook. For example, two notebooks attached to the same cluster can define variables and classes with the same name, but these objects are distinct.

To define a class that is visible to all notebooks attached to the same cluster, define the class in a package cell. Then you can access the class by using its fully qualified name, which is the same as accessing a class in an attached Scala or Java library.

Spark session isolation

Every notebook attached to a cluster running Apache Spark 2.0.0 and above has a pre-defined variable called spark that represents a SparkSession. SparkSession is the entry point for using Spark APIs as well as setting runtime configurations.

Spark session isolation is enabled by default. You can also use global temporary views to share temporary views across notebooks. See Create View or CREATE VIEW. To disable Spark session isolation, set spark.databricks.session.share to true in the Spark configuration.

Important

Setting spark.databricks.session.share true breaks the monitoring used by both streaming notebook cells and streaming jobs. Specifically:

  • The graphs in streaming cells are not displayed.
  • Jobs do not block as long as a stream is running (they just finish “successfully”, stopping the stream).
  • Streams in jobs are not monitored for termination. Instead you must manually call awaitTermination().
  • Calling the display function on streaming DataFrames doesn’t work.

Cells that trigger commands in other languages (that is, cells using %scala, %python, %r, and %sql) and cells that include other notebooks (that is, cells using %run) are part of the current notebook. Thus, these cells are in the same session as other notebook cells. By contrast, a notebook workflow runs a notebook with an isolated SparkSession, which means temporary views defined in such a notebook are not visible in other notebooks.

Version control

Azure Databricks has basic version control for notebooks. You can perform the following actions on revisions: add comments, restore and delete revisions, and clear revision history.

To access notebook revisions, click Revision History at the top right of the notebook toolbar.

In this section:

Add a comment

To add a comment to the latest revision:

  1. Click the revision.

  2. Click the Save now link.

  3. In the Save Notebook Revision dialog, enter a comment.

  4. Click Save. The notebook revision is saved with the entered comment.

Restore a revision

To restore a revision:

  1. Click the revision.

  2. Click Restore this revision.

  3. Click Confirm. The selected revision becomes the latest revision of the notebook.

Delete a revision

To delete a notebook’s revision entry:

  1. Click the revision.

  2. Click the trash icon .

  3. Click Yes, erase. The selected revision is deleted from the notebook’s revision history.

Clear a revision history

To clear a notebook’s revision history:

  1. Select File > Clear Revision History.

  2. Click Yes, clear. The notebook revision history is cleared.

    Warning

    Once cleared, the revision history is not recoverable.

Git version control

Note

To sync your work in Azure Databricks with a remote Git repository, Databricks recommends using Repos for Git integration.

Azure Databricks also integrates with these Git-based version control tools:

Essential notebook commands—ArcGIS Notebook Server

ArcGIS Notebooks runs a Jupyter notebook environment, which provides a streamlined cell-based workspace. This topic walks through the basic commands and aspects of working in Notebooks, including shortcuts and best practices.

Specify a cell’s type

There are three types of cells you can use in a notebook. When you have selected a cell with your pointer, you can change the cell’s type using the drop-down list on the toolbar.

The following are the three available types:

  • Code—The notebook will interpret all content in a code cell in the Python language. When writing Python code, typing certain strings, such as from or the equal sign (=), will prompt the notebook to automatically recolor or highlight them for clarity. Any line of code that starts with a number sign (#) will be interpreted as a comment, colored green and italicized, and will not be executed as code by the notebook.
  • Markdown—The notebook will interpret all content in a Markdown cell in the Markdown language. This is a simple language for formatting rich text, used across the internet by clients such as GitHub. See the Markdown Guide online for a reference to using Markdown. Running a Markdown cell will turn its content into rich text. Any lines that start with one or multiple number signs (#) will be formatted as headings. You can also add raw HTML code to Markdown cells.
  • Raw NBConvert—The notebook will not process content in a Raw NBConvert cell. This cell type is rarely used.

The Heading cell type is also available in the drop-down list. However, this cell type is no longer used in Jupyter notebook environments. Clicking this cell type will turn the cell into a Markdown cell and append an number sign (#), which denotes a top-level heading in Markdown.

The use of rich text and code comments will make your notebooks more readable and valuable to users with whom they are shared.

Work with cells

For a notebook to execute code, the code must be contained in a cell. The code in cells allows you to define variables and run functions contained in Python libraries.

To define a variable, run a cell that contains a variable statement, including an equal sign (=). The default notebook template, for example, launches having defined a variable gis. If you run a cell containing only that variable name, gis, the notebook will return the URL of your ArcGIS Enterprise portal as an output.

The iPython commands using exclamation points, such as !cd <directory>, to change directories from the command line will not work in ArcGIS Notebooks. Instead, use commands without exclamation points, such as cd <directory>.

To run a Python function, provide the function’s syntax and any arguments required or accepted by the function. See the Use functions in a cell section below to learn more.

You can create a new cell by pressing Shift+Enter, or by clicking Insert on the menu ribbon, which gives you the option to insert a new cell above or below your current cell.

Cell toolbar options

You can include additional information about individual cells in a notebook using the options in the cell toolbar:

  • None—Do not show cell toolbars.
  • Edit Metadata—Enter metadata for each cell using JSON.
  • Raw Cell Format—Raw cells allow you to write output directly; the content of these cells is not evaluated by the notebook.
  • Slideshow—Specify how each cell will display in a slide show. Helpful when presenting code.
  • Attachments—Manage the associated attachments within each cell in the notebook workspace.
  • Tags—Create and manage tags for each cell within the notebook workspace.

When any of these options are on, a bar appears above each cell in the notebook. Only one option can be on at a time, but any information you add to the toolbar remains even when switched off. You can change the cell toolbar options by clicking View > Cell Toolbar.

The Tags option can be used when you are preparing a notebook to be scheduled or remotely executed. The Execute Notebook operation provides the option to insert parameters as a new cell at execution time, such as account credentials or variables to define. You can designate the place in the notebook where this new cell is added by adding the tag parameters to a cell in your notebook. The new cell is inserted after this cell. Only one cell with the parameters tag is recognized by the operation.

Import libraries and modules

In the default notebook template, ArcGIS Notebooks only imports the gis module from the ArcGIS API for Python. Typically, you will want to use additional Python libraries available in your notebook’s runtime. To access these libraries, run an import command.

See all Python libraries available in ArcGIS Notebooks

Create a new cell and type import <library>, and then run the cell.

In the ArcGIS API for Python and ArcPy, and in some other cases, Python libraries are organized into modules. To access the libraries within a module, declare the module to access with a from statement, and then declare a library using an import statement. For example, to call the WebScene library from the mapping module in the ArcGIS API for Python, run the following command in a cell:

from arcgis.mapping import WebScene

ArcGIS Notebooks includes an autocomplete feature when running cells. You can use it to help you find the libraries and modules you need. In a cell, type the first portion of your command, and press Tab to activate the autocomplete feature. It provides possible values that can complete the command.

For example, if you type arcgis. and then press Tab, the notebook will provide a drop-down list of all the modules available in the ArcGIS API for Python. You can use the up and down arrows to navigate the list; when you find the option you want, press Enter to insert it into your line of code.

To learn more about how the ArcGIS API for Python and ArcPy work in your notebooks, see the following topics:

Use functions in a cell

To perform analysis and work with data in notebooks, you use Python functions. Functions are contained within Python libraries, and often take input arguments to specify how they will execute and what content they will execute on.

The notebook’s autocomplete tool can help you find functions by providing a drop-down list of what’s available. For any library bar, type bar. and press Tab to show the functions available in it.

For example, to view the tools available in the Summarize Data library of the arcgis.features module, enter the following code and press Tab:

The autocomplete tool shows a drop-down list of the tools available in the library.

Often, a command in a notebook has required or optional arguments—parameters that provide information to execute a command. If a command’s syntax ends with an empty set of parentheses (()), the command requires or can include optional arguments for you to add.

Enter arguments within the parentheses, separating multiple arguments with commas. To view the string of required and optional arguments for any function, replace its empty parentheses with a question mark and run the cell. This will show the function’s docstring, which lists all arguments.

For example, all tools available through the notebook editor’s Analysis pane require arguments. Adding a tool from this pane to a cell will insert the tool’s ArcGIS API for Python syntax, ending in empty parentheses. If you try to run this syntax in a cell without providing one or more arguments, the cell will fail and provide an error message.

If you want to run the Aggregate Points tool in the Summarize Data library, locate the tool in the Analysis pane and add it to a new cell, or type the tool syntax as follows:

features.summarize_data.aggregate_points()

To view the list of arguments for the tool, modify the syntax as follows and run the cell:

features.summarize_data.aggregate_points?

This opens the docstring reference window for the tool. This reference has buttons to expand or close the window in the upper right corner.

When you’re working in a cell, keep the following in mind:

  • For any function foo(), type foo? and press Enter to show the function’s docstring, which describes the function.
  • If you start a cell with !, the cell’s contents run as a bash command in your notebook container.

Run a cell

When you run a cell, its code is executed, and all operations within are performed. You can only run a whole cell, not a subsection of the cell or a specific line of code. Cells can consist of one or multiple lines of code.

To run a selected cell, click the Run button on the toolbar, or click Cells > Run Cells. You can also press Ctrl+Enter to run the cell your mouse pointer is in.

To manually stop a cell that is being run, click Kernel > Interrupt. You can also click the square stop button in the toolbar.

To the left of each code cell is an In [ ] element. If the cell has not yet been run, or if a previously run cell has been cleared of its output, the bracket is empty. While the cell is being run, it contains an asterisk: In [*]. When a cell has completed running, its In [ ] bracket is populated with a number that indicates the order of cells that have been run. Because cells in a notebook can be run in any order and can be run multiple times, the In [ ] numbers in a notebook’s cells may not be in sequential order.

Markdown cells maintain an In [ ] element until they are run, at which point the element disappears and the cell’s content becomes rich text.

When a line of code in a cell you run produces an output, the output is displayed in your notebook underneath the executed cell. Next to the output is an Out [ ] element, which matches what’s in the corresponding cell’s In [ ] element.

Work with the kernel

When you launch a new notebook, a kernel is launched with it. This kernel executes the code you run in the notebook. As you run cells in the notebook (populating their In [ ] elements), variables you have defined in executed cells are stored in the kernel’s memory.

To restart your notebook’s kernel and clear in-memory variables, click Kernel > Restart. If you want to restart the kernel, clear in-memory variables, and run all cells in the notebook sequentially, click Kernel > Restart & Run All.

When you are done actively using a notebook, click Kernel > Shutdown to shut down the notebook’s kernel and clear all in-memory variables. The kernel stops running, but it does not erase the outputs of cells that have been run.

When a notebook has been left idle for an extended period of time, the kernel will shut down and clear all in-memory values automatically. This time period is 24 hours by default, but can be specified by your site administrator to be shorter or longer.


Feedback on this topic?

Samsung Updates New Notebook 9 Line – Samsung Global Newsroom

 

The Samsung Notebook 9 delivers the latest in Notebook technology in a sleek and light design. With advanced features including enhanced connectivity, premium display and an added layer of security, the Samsung Notebook 9 offers the performance and portability to go wherever you need to go.

 

 

Sleek and Light Design

  • Impossibly Light: The Samsung Notebook 9 13.3-inch — at 1.8 pounds — is the lightest notebook on the market. It’s effortless to carry, and easy to travel with. It’s the perfect combination of performance and portability.
  • Refined Design: The Samsung Notebook 9 13.3-inch and 15-inch feature an ultra-slim bezel and near edge-to-edge display sets a new design standard and gives you more screen to do what you need to do
  • Versatile: The Samsung Notebook 9 display reclines 180°, making it simple to share presentations with co-workers, or pictures with your friends and family.
  • Durable: With a sleek single shell structure, and Micro Arc Oxidation (MAO) Rigidity technology, the Notebook 9 features added integrity, resiliency, and thermal and shock resistance.

 

 

Advanced Features for Strong Performance and Connectivity

  • Powerful Performance: The Samsung Notebook 9 isn’t just a beautiful device, it also packs power and performance. It is equipped with the latest 7th Generation Intel® Core™ i7/i5 Processors, as well as faster storage and memory.
  • Connectivity Features: The Samsung Notebook 9 offers exclusive software solutions for peer-to-peer sharing with other devices including smartphones. With PC Message and PC Gallery, users can easily share files, messages and photos anytime, anywhere.

 

 

Fast Charging Battery

  • Long-Lasting Battery: The Samsung Notebook 9 battery last for 7 hours on a single charge—more than enough for a day at the office, or even an international flight.
  • Adaptive Fast Charge: Users can fully recharge the Samsung Notebook 9 in 80 minutes, or get 2.1 hours of power in just 20 minutes.
  • USB Type-C™: The latest USB Type-C™ port lets users charge the Samsung Notebook 9 through via a cell-phone charger, and also enables quick data transfer and connectivity to displays and other devices.

 

 

Improved Security with Built-in Fingerprint Sensor

  • Security is always top-of-mind which is why the Samsung Notebook 9 includes a built-in fingerprint sensor as well as support for Windows Hello, which enables secure sign in with a single touch, so users can log into the Windows 10 device without typing in a password.

 

 

Immersive Experiences with Premium Display Technology

  • Vibrant Full-HD Display: The Samsung Notebook 9 was created with a stunningly immersive full-HD display with bright, vivid and accurate colors. Featuring Samsung RealView Display, the Samsung Notebook 9 elevates the viewing experience to new heights with support for a high-level of brightness, true-to-life colors and a wide viewing angle. Also, with Outdoor Mode, instantly boost the clarity of the display with a quick shortcut command when working under direct sunlight.
  • HDR Video: View content in high dynamic range (HDR) to experience more vibrant videos.

 

 

Samsung Notebook 9 15” EXT Product Specifications

OS Windows 10 Home
PROCESSOR Intel Core i7 7500U
DISPLAY 15.0-inch, 350nit, FHD (1,920X1,080), 178°, LR, sRGB 95% Delta E<2.5, Outdoor mode (500 nits), Video HDR
GRAPHICS Dedicated; NVIDIA 940MX Graphics Card
STORAGE PCIe NVMe,256GB SSD
MEMORY DDR4 dual channel, 16GB (on board)
WIRELESS 802.11 ac 2X2
BLUETOOTH Bluetooth 4.1
SOUND 1.5W X 2 SPEAKERS
INTEGRATED CAMERA 720p
MIC Internal Dual Array Digital Mic
KEYBOARD 1.5mm stroke, backlit, curved keycap, fingerprint sensor
I/O PORTS 1 x USB-C™ Thunderbolt 3 [up to 40Gbps, 4K display out with optional adapter, Charging] + 2 x USB 3.0 + 1 USB 2.0
AC ADAPTER 65W adaptor
DIMENSIONS 13.70″ x 9.03″ x 0.61″
WEIGHT 2.73 lbs
BATTERY 66Wh
MATERIAL/COLOR Light Titan
SOFTWARE Wi-Fi Transfer, Simple Sharing, PC Message, PC Gallery, SideSync

* Samsung Notebook 9 15″ EXT is only available for purchase in US markets.

 

 

Samsung Notebook 9 (15-inch) Product Specifications

OS WINDOWS 10 Home
PROCESSOR 7TH GEN INTEL® CORE™ i7
DISPLAY 15.0″, 350nit, FHD (1,920X1,080), 178°, LR, sRGB 95% Delta E<2.5, Outdoor mode (500 nits), Video HDR
GRAPHICS SHARED
STORAGE PCIe NVMe, up to 256GB SSD
MEMORY DDR4 dual channel, up to 8GB (on board)
WIRELESS 802.11 ac 2X2
BLUETOOTH Bluetooth 4.1
SOUND 1.5W X 2 SPEAKERS
INTEGRATED CAMERA 720p
MIC Internal Dual Array Digital Mic
KEYBOARD 1.5mm stroke, backlit, curved keycap, finger print sensor
I/O PORTS 2XUSB 3.0, 1XUSB 2.0, 1XUSB-C, HDMI, MicroSD, HP/Mic
AC ADAPTER 45W small adaptor
DIMENSIONS 347.9 X 229.4 X 14.9mm
WEIGHT 2.17lbs
BATTERY 30Wh, Fast Charging, External Battery Charging
MATERIAL / COLOR Light Titan
SOFTWARE Wi-Fi Transfer, Simple Sharing, PC Message, PC Gallery, SideSync

 

Samsung Notebook 9 (13.3-inch) Product Specifications

OS WINDOWS 10 Home
PROCESSOR 7TH GEN INTEL® CORE™ i5/i7
DISPLAY 13.3”, 350nit, FHD (1,920X1,080), 178°, LR, sRGB 95% Delta E<2.5, Outdoor mode (500 nits), Video HDR
GRAPHICS SHARED
STORAGE SATA3 SSD, up to 256GB SSD
MEMORY DDR4 dual channel, up to 8GB for i3, up to 16GB for i7 (on board)
WIRELESS 802.11 ac 2X2
BLUETOOTH Bluetooth 4.1
SOUND 1.5W X 2 SPEAKERS
INTEGRATED CAMERA 720p
MIC Internal Dual Array Digital Mic
KEYBOARD 1.5mm stroke, backlit, curved keycap, finger print sensor
I/O PORTS 2XUSB 3.0, 1XUSB-C, HDMI, MicroSD, HP/Mic
AC ADAPTER 45W small adaptor
DIMENSIONS 309.4 X 208 X 13.9mm
WEIGHT 1.8lbs
BATTERY 30Wh, Fast Charging, External Battery Charging
MATERIAL / COLOR Light Titan
SOFTWARE Wi-Fi Transfer, Simple Sharing, PC Message, PC Gallery, SideSync

 

* All functionality, features, specifications and other product information provided in this document including, but not limited to, the benefits, design, pricing, components, performance, availability, and capabilities of the product are subject to change without notice or obligation.

 

** Portion of memory occupied by existing content.

 

*** Battery life is based on internal testing conducted by Samsung. Results may differ by usage pattern.

 

Source: US Newsroom

NFL notebook: Patriots’ offensive line will be shorthanded vs. Texans

Offensive lineman Trent Brown has been ruled out for the Patriots’ game against the Texans on Sunday. Winslow Townson/Associated Press Images for Panini

The Patriots will be without at least two of their starting offensive linemen this weekend in Houston.

Trent Brown (calf) and Shaq Mason (abdomen) were both ruled out for the Texans game after missing an entire week of practice. New England could be without as many as four starters on the offensive line this Sunday, as Michael Onwenu and Isaiah Wynn are both still on the COVID-19 reserve list.

If that’s the case, the Patriots could have a surprisingly difficult afternoon in Houston.

New England also listed eight players questionable: Ja’Whaun Bentley (shoulder), Cody Davis (knee), Kyle Dugger (hamstring), Nick Folk (left knee), Jonathan Jones (ankle), Jalen Mills (hamstring), Ronnie Perkins (ankle), Kyle Van Noy (groin).

Surprisingly thin at cornerback after the Stephon Gilmore trade, the Patriots could also be in trouble if either Jones or Mills isn’t ready to go in the defensive backfield. Shaun Wade (concussion), has been ruled out, too.

On the Houston side, old friends Danny Amendola (thigh) and Marcus Cannon (back) are questionable, while Rex Burkhead (hip) has been ruled out.

RAIDERS: The NFL reacted strongly and quickly to a report that Jon Gruden used a racist comment about NFL Players Association leader DeMaurice Smith in an email 10 years ago.

A Wall Street Journal story noted that Gruden, then working for ESPN and now coach of the Las Vegas Raiders, referred in a racist way to Smith’s facial features.

“The email from Jon Gruden denigrating DeMaurice Smith is appalling, abhorrent and wholly contrary to the NFL’s values,” NFL spokesman Brian McCarthy said. “We condemn the statement and regret any harm that its publication may inflict on Mr. Smith or anyone else.”

The league is looking into the matter and a person familiar with that probe told The Associated Press that disciplinary action is possible for Gruden. The person spoke on condition of anonymity because details of any league probe are not made public.

Gruden’s comment in an email to then-Washington Football Team President Bruce Allen came during the 2011 lockout of the players by the NFL. Gruden told the newspaper he was angry about the lockout during labor negotiations and he didn’t trust the direction the union was taking. He also apologized for the remark, the Journal reported.

During a review of emails regarding workplace misconduct at the Washington Football Team that was completed during the summer, “the league was informed of the existence of emails that raised issues beyond the scope of that investigation,” McCarthy added.

SEAHAWKS: Quarterback Russell Wilson was seeing a hand specialist regarding his injured right middle finger suffered in the Thursday night loss to the Los Angeles Rams.

Seattle Coach Pete Carroll declined to go into many specifics regarding the injury until after Wilson saw a specialist in the Los Angeles area. Carroll said Wilson did have an initial set of X-rays after the 26-17 loss the Rams.

“I want him to go to the specialist and make sure he tells us,” Carroll said. “But there’s something going on. There’s definitely something going on and we’ve got to figure out what the extent of it is and what is the next step to deal with it.”

Wilson was injured in the third quarter when his fingers hit the arm of defensive tackle Aaron Donald on the follow through of a pass attempt. Wilson tried to play one more series and threw one more pass before giving way to Geno Smith in the fourth quarter. Carroll said Wilson simply didn’t have the strength in the finger to control the ball as needed to throw.

PANTHERS: Carolina listed running back Christian McCaffrey as doubtful for Sunday’s game against the Philadelphia Eagles, even after McCaffrey practiced all three days on a limited basis this week. He missed last week’s game against the Dallas Cowboys with a strained hamstring. If McCaffrey doesn’t play he will have missed 15 of Carolina’s last 21 games due to injury.

“Nothing much more to add,” Panthers Coach Matt Rhule said Friday. “He’s been going. It’s doubtful he’ll play on Sunday. That could change. I’m not going to play any games.’’

The team has also listed left tackle Cam Erving (neck) and linebacker Shaq Thompson (foot) as out for Sunday.

BRONCOS: Teddy Bridgewater is trending toward starting Sunday against the Steelers one week after suffering a concussion in Denver’s loss to Baltimore.

Bridgewater was cleared for a full practice Friday and met with medical staff afterward. He hopes to get the green light Saturday morning before the Broncos (3-1) fly to Pittsburgh (1-3).

BROWNS: Star defensive end and NFL sacks leader Myles Garrett expects to play Sunday against the Los Angeles Chargers despite missing his second practice of the week Friday due to soreness.

Garrett is listed as questionable by the Browns (3-1), who are dealing with numerous injuries across their second-ranked defense and continue to downplay quarterback Baker Mayfield’s shoulder injury. While his teammates went through the portion of practice open to media members, Garrett worked on his conditioning to the side with starting rookie cornerback Greg Newsome, who will miss his second straight game with a calf injury.

Afterward, Garrett, who was rested Wednesday and was limited in Thursday’s practice, said he’s been dealing with “nagging pain” for several weeks, but wouldn’t specify his injuries.

JETS: New York signed defensive end John Franklin-Myers to a contract extension, rewarding one of their young standouts.

A person with direct knowledge of the deal told The Associated Press it’s a four-year contract worth up to $55 million.

TITANS: Tennessee placed linebacker Jayon Brown and three others on injured reserve after declaring them out against the Jacksonville Jaguars.

Brown played three of the last four games, including last week’s loss to the Jets. But he’s been on the injury report most recently with a knee that kept him from practicing this week. The Titans also put rookie wide receiver Racey McMath, offensive lineman Aaron Brewer and tight end Tommy Hudson on injured reserve.

49ERS: Trey Lance drew Kyle Shanahan’s official nod to debut as the 49ers’ starting quarterback Sunday, but only after Jimmy Garoppolo’s calf injury kept him out of practice all week, including Friday’s light session.

The undefeated Arizona Cardinals (4-0) and State Farm Stadium in Glendale, Ariz., will serve as the launching pad for Lance’s much-anticipated starting tenure, one that officially isn’t promised beyond this game.

Garoppolo was ruled out, and tight end George Kittle is doubtful because of his own calf injury that kept him out of practice, too.


Invalid username/password.

Please check your email to confirm and complete your registration.

Use the form below to reset your password. When you’ve submitted your account email, we will send an email with a reset code.

« Previous

College football preview: UMaine (1-2) vs. Elon (2-3)

Next »

Sports Digest: Maine men’s hockey falls in debut for Coach Ben Barr

Related Stories

Linear Notepad Image_Photo Number 400328242_PNG Image Format_lovepik.com

Applicable Groups Personal Start command Micro-enterprise Medium enterprise
Authorization period PERMANENT PERMANENT PERMANENT PERMANENT
Portrait authorization

PERMANENT PERMANENT PERMANENT
Authorized agreement Personal authorization Company authorization Company authorization Company authorization
Online account

Media Marketing

(Facebook, Twitter, Instagram, etc.)

Personal Commercial

90,070 (Limit 20,000 impressions) 90,071

Digital Media Marketing

(SMS, Email, Online Advertising, E-books, etc.)

Personal Commercial

90,070 (Limit 20,000 impressions) 90,071

Design of web pages, mobile and software pages

Web Application & Application Development, Software & Gaming Application Development, H5, E-Commerce &

Product

Personal Commercial

90,070 (Limit 20,000 impressions) 90,071

Physical products printed products

Food packaging, books and magazines, newspapers, postcards, posters, brochures, coupons, etc.D.

Personal Commercial

(Print limit 200 copies)

limit 5000 Copies Print limit 20000 Copies Print unlimited Copies Printing

Product Marketing & Business Plan

Proposal for network design, VI design, marketing planning, PPT (not resale), etc.

Personal Commercial

Marketing and display of outdoor advertising

Outdoor billboards, bus advertisements, shop windows, office buildings, hotels, shops, other public places, etc.D.

Personal Commercial

(Print limit 200 copies)

Media

(CD, DVD, Movie, TV, Video, etc.)

Personal Commercial

90,070 (Limit 20,000 impressions) 90,071

Resale of physical product

textiles, mobile phone cases, greeting cards, postcards, calendars, cups, t-shirts

Online Resale

Mobile wallpaper, design templates, design elements, PPT templates and the use of our designs as the main item for resale.

Portrait Commercial

(For teaching and communication only)

Portrait-sensitive use

(tobacco, medical, pharmaceutical, cosmetic and other industries)

(For teaching and communication only)

(Contact customer service to customize)

(Contact customer service to customize)

(Contact customer service to customize)

ORE Lab.What is Rebuk and what is it for

Traditional binders focus on consistent, linear page binding. Such a rigid system creates a framework imposed by publishers and limits our ability to work with text.

Disc binding makes all sheets loose. They are organized in any order, in the order that is needed.
Modular system with separate page interfaces.

We are used to the word book. This name is given to all types of printed products, consisting of stitched (from brocher – “to stitch”) paper sheets.By the nature of the text, they are divided into a large number of literary directions and already consist of at least two words – a fiction book, a business book, a non-fiction book, a popular science book, an academic book. Books in which you can take notes also have many definitions – notebook, notebook, notepad, diary, diary, planner, organizer, sketchbook.

A new term is needed to distinguish the category of editions that have a binding with the ability to rearrange individual sheets.Binders with mobile sheets provide other possibilities for working with the book. They are closer to the constructor. A person becomes an active participant in the creation of his own product, which he needs. The publisher only provides a platform for this creative process.

Page-Card Interface

Each sheet, like a card, lives its own life – in exactly the order that is needed. Can be easily and painlessly removed for binding and easily attached back.It can be moved to any other place it needs. Pages with different rulers – checkered, ruled or blank sheets for sketches, side by side. Without the dictates of developers and printers. No hard grip.

Mobile Sheets

They move to where they need to – to another rebuild, to an archive, to a scanner, to a printer.
Rotates 360 ° around the axis. Convenient in confined spaces, on the road, in the park.
New sheets may appear – different sizes, different rulers.
Rubber text.

All in one

Suitable for different tasks:

  • planning
  • tracking cases
  • diary
  • sketchbook
  • notebook
  • diary
  • hobbies

Any templates and techniques are possible to suit your needs.

Focuses on what you want, no distractions

Actually a handbook. Always in sight.
Recursion of attention to the main thing.
What is important is to remember.It doesn’t matter – write it down, do it, throw it away.


Jupyter Notebook for Linear Regression

  import numpy as np
X = 2 * np.random.rand (100,1)
y = 4 + 3 * X + np.random.randn (100,1)
from sklearn.linear_model import LinearRegression
lin_reg = LinearRegression ()
lin_reg.fit (X, y)
  
  LinearRegression (copy_X = True, fit_intercept = True, n_jobs = 1, normalize = False)
  
  lin_reg.intercept_, lin_reg.coef_
  
  (array ([3.97333023]), array ([[3.02174689]]))
  
  X_new = np.array ([[0], [2]])
y_predict = lin_reg.predict (X_new)
y_predict
  
  array ([[3.97333023],
       [10.01682401]])
  
  import matplotlib.pyplot as plt
plt.plot (X_new, y_predict, 'r-')
plt.plot (X, y, 'b.')
plt.axis ([0,2,0,15])
plt.show ()
  

  from sklearn.linear_model import SGDRegressor
sgd_reg = SGDRegressor (n_iter = 50, penalty = None, eta0 = 0.1)
sgd_reg.fit (X, y.ravel ())
  
  D: \ Anaconda \ lib \ site-packages \ sklearn \ linear_model \ stochastic_gradient.py: 117: DeprecationWarning: n_iter parameter is deprecated in 0.19 and will be removed in 0.21. Use max_iter and tol instead.
  DeprecationWarning)





SGDRegressor (alpha = 0.0001, average = False, epsilon = 0.1, eta0 = 0.1,
       fit_intercept = True, l1_ratio = 0.15, learning_rate = 'invscaling',
       loss = 'squared_loss', max_iter = None, n_iter = 50, penalty = None,
       power_t = 0.25, random_state = None, shuffle = True, tol = None, verbose = 0,
       warm_start = False)
  
  sgd_reg.intercept_, sgd_reg.coef_
  
  (array ([4.01782085]), array ([3.08462177]))
  
  X = 6 * np.random.rand (100,1) -3
y = 0.5 * X ** 2 + X + 2 + np.random.randn (100,1)
from sklearn.preprocessing import PolynomialFeatures
poly_features = PolynomialFeatures (degree = 2, include_bias = False)
X_poly = poly_features.fit_transform (X)
X_poly
  
  array ([[-2.27162782e + 00, 5.16029294e + 00],
       [2.48828797e + 00, 6.19157701e + 00],
       [-2.86471747e + 00, 8.20660618e + 00],
       [-3.51446471e-02, 1.23514622e-03],
       [-4.76605499e-01, 2.27152802e-01],
       [-2.22396650e-01, 4.94602700e-02],
       [-1.52332987e-01, 2.32053389e-02],
       [2.56964604e + 00, 6.60308077e + 00],
       [-2.09791253e-01, 4.40123696e-02],
       [2.82843260e + 00, 8.00003096e + 00],
       [-1.77694039e + 00, 3.15751715e + 00],
       [-2.96294112e + 00, 8.776e + 00],
       [2.06573299e + 00, 4.26725280e + 00],
       [-4.15237916e-01, 1.72422527e-01],
       [1.62632664e + 00, 2.64493834e + 00],
       [-2.76537161e + 00, 7.64728015e + 00],
       [1.62333777e + 00, 2.63522552e + 00],
       [-1.69748510e + 00, 2.88145568e + 00],
       [-1.61874247e + 00, 2.62032719e + 00],
       [3.48079300e-01, 1.21159199e-01],
       [-1.63800646e + 00, 2.68306515e + 00],
       [2.78117263e + 00, 7.73492122e + 00],
       [2.58737964e + 00, 6.69453340e + 00],
       [-2.38647549e + 00, 5.69526527e + 00],
       [5.83641864e-01, 3.40637826e-01],
       [1.13887061e + 00, 1.29702626e + 00],
       [  1.54696577e + 00, 2.39310310e + 00],
       [-8.48886440e-01, 7.20608189e-01],
       [2.61854833e + 00, 6.85679536e + 00],
       [2.39614219e + 00, 5.74149738e + 00],
       [2.29832868e + 00, 5.28231471e + 00],
       [8.63057295e-01, 7.44867894e-01],
       [6.71615556e-01, 4.51067455e-01],
       [-2.28821538e + 00, 5.23592965e + 00],
       [-7.18192648e-03, 5.15800679e-05],
       [2.56850875e + 00, 6.59723722e + 00],
       [-2.67808813e + 00, 7.17215604e + 00],
       [9.18276140e-02, 8.43231069e-03],
       [2.84179527e + 00, 8.07580038e + 00],
       [4.76848123e-01, 2.27384132e-01],
       [-1.05859444e + 00, 1.12062218e + 00],
       [-4.83050710e-01, 2.33337988e-01],
       [1.09830708e + 00, 1.20627845e + 00],
       [-8.41943591e-01, 7.08869010e-01],
       [-2.31281777e + 00, 5.34912602e + 00],
       [1.41680454e + 00, 2.00733510e + 00],
       [2.32192647e + 00, 5.39134253e + 00],
       [2.75357785e + 00, 7.58219100e + 00],
       [1.22932198e + 00, 1.51123253e + 00],
       [3.24293184e-01, 1.05166069e-01],
       [2.31784975e + 00, 5.37242748e + 00],
       [1.48079539e + 00, 2.19275497e + 00],
       [8.29783809e-01, 6.88541170e-01],
       [-2.24983274e-01, 5.06174735e-02],
       [-1.11656349e-01, 1.24671402e-02],
       [-1.21038946e + 00, 1.46504264e + 00],
       [2.16525157e + 00, 4.68831435e + 00],
       [-1.477e + 00, 2.18420216e + 00],
       [-2.85236952e + 00, 8.13601189e + 00],
       [1.41389032e + 00, 1.99908582e + 00],
       [-1.07533455e + 00, 1.15634439e + 00],
       [2.28026745e + 00, 5.19961966e + 00],
       [1.28117214e-02, 1.64140205e-04],
       [-2.32504972e + 00, 5.40585622e + 00],
       [-2.57139421e + 00, 6.61206817e + 00],
       [1.35085363e + 00, 1.82480553e + 00],
       [-2.77598303e + 00, 7.70608177e + 00],
       [-1.38921503e + 00, 1.92991839e + 00],
       [2.17698652e + 00, 4.73927033e + 00],
       [1.19594968e-01, 1.43029563e-02],
       [-2.53910356e + 00, 6.44704689e + 00],
       [-1.47461118e + 00, 2.17447814e + 00],
       [ -1.75114805e + 00, 3.06651949e + 00],
       [5.79263192e-01, 3.35545846e-01],
       [1.47052864e + 00, 2.16245448e + 00],
       [-2.54646747e-01, 6.48449660e-02],
       [-4.11794540e-01, 1.69574744e-01],
       [1.92154543e + 00, 3.69233684e + 00],
       [7.42522075e-01, 5.51339032e-01],
       [1.37807725e + 00, 1.89909689e + 00],
       [-2.16306259e + 00, 4.67883975e + 00],
       [-2.33519899e + 00, 5.45315431e + 00],
       [2.04329979e + 00, 4.17507405e + 00],
       [1.37057964e + 00, 1.87848854e + 00],
       [-2.78831283e + 00, 7.77468842e + 00],
       [4.66626908e-01, 2.17740671e-01],
       [2.21258986e + 00, 4.89555391e + 00],
       [-1.25511286e + 00, 1.57530829e + 00],
       [-2.13063729e-01, 4.53961525e-02],
       [2.41312639e + 00, 5.82317895e + 00],
       [1.65076148e + 00, 2.72501347e + 00],
       [-1.35578522e-01, 1.83815357e-02],
       [2.96954953e + 00, 8.81822440e + 00],
       [1.08991308e + 00, 1.18791053e + 00],
       [2.30045106e-01, 5.29207510e-02],
       [-3.35162652e-01, 1.12334003e-01],
       [2.92046596e + 00, 8.52912144e + 00],
       [1.27428035e + 00, 1.62379040e + 00],
       [-1.22411248e + 00, 1.49845135e + 00],
       [1.13624452e-01, 1.29105161e-02]])
  
  lin_reg = LinearRegression ()
lin_reg.fit (X_poly, y)
  
  LinearRegression (copy_X = True, fit_intercept = True, n_jobs = 1, normalize = False)
  
  lin_reg.intercept_, lin_reg.coef_
  
  (array ([2.23279821]), array ([[0.95930232, 0.42162001]]))
  
  X_new = np.array ([[i, i ** 2] for i in range (-3,4)])
y_predict = lin_reg.predict (X_new)
y_predict
  
  array ([[3.14947133],
       [2.0006736],
       [1.6951159],
       [2.23279821],
       [3.61372054],
       [5.83788289],
       [8.526]])
  
  plt.plot (X, y, 'b.')
plt.plot ([i for i in range (-3,4)], y_predict, 'r-')
plt.axis ([- 3,3,0,10])
plt.show ()
  

Create Equations and Formulas

To type a new formula from scratch, press Alt + = on your keyboard.

Or

Select Insert > Formula and select Insert New Formula at the bottom of the built-in Formula Gallery. A placeholder is inserted where you can enter your formula.

Insert a checkbox or other symbol

Add a formula to a collection

  1. Highlight the formula you want to add.

  2. Click the down arrow and select Save as New Formula … .

  3. In the Create New Building Block dialog box, enter a name for the formula.

  4. In the list of collections, select Formulas .

  5. Click OK .

To change or edit previously created formulas:

  1. Select a formula to open the Formula Tools tab on the ribbon.

  2. Click Constructor to see tools for adding various elements to your formula. You can add or change the following formula elements.

    • Group Symbols contains mathematical symbols.To see all symbols, press more. To see other character sets, click the arrow in the upper right corner of the gallery.

    • Group Structures contains structures that you can insert. Just select an element and then replace the placeholders in the outline (dash-dotted rectangles) with the values ​​you want.

    • Option Professional displays the formula in a professional format that is optimized for display. Parameter Linear displays the formula as original text that you can use to make changes to the formula as needed. The Linear option displays the formula in UnicodeMath or LaTeX format, which you can select in the Transforms box.

    • You can convert to Professional or Linear format all formulas in a document, or just one by selecting a math zone or hovering over a formula.

On touch and pen-enabled devices, you can write formulas with the pen or your finger.For handwriting the formula

  1. Select Draw > Convert Ink to Math and then select Ink Equation at the bottom of the built-in gallery.

  2. Use your pen or finger to enter a math formula by hand. If your device does not have a touchscreen, use your mouse to write the equation.

Related Posts

Leave a Reply

Your email address will not be published. Required fields are marked *