Top Tips and Tricks to use Jupyter Notebook<\/strong><\/h2>\nA number of helpful Jupyter Notebook tips can be found here.<\/p>\n
Shell Commands<\/strong><\/h3>\nDo you exit your notebook to execute a shell command?<\/p>\n
An exclamation mark can be used before a command in your Jupyter Notebook to execute shell commands.<\/p>\n
For example:<\/p>\n
!pip install Tkinter<\/strong><\/p>\nMagic Commands<\/strong><\/h3>\nThere are many useful magic commands in Jupyter to help you with your daily tasks. One quick fix for common issues is to use a magic command, which can list every file in the current directory, among other things. A magic command is handy because it may be added directly to Python code. A magic command starts with %.<\/strong><\/p>\nThese are few helpful magic commands:<\/p>\n
Print the current working directory<\/strong>
\n%pwd<\/strong><\/p>\n# Show all the files in the current directory<\/strong>
\n%ls<\/strong><\/p>\n# Change the working directory<\/strong>
\n%ls [PATH_TO_DIR]<\/strong><\/p>\n# List all the variables<\/strong>
\n%Who<\/strong><\/p>\nView all the magic commands<\/strong><\/h4>\nThere is a long list of helpful magic commands. Use this to see a list of all the magic commands that are available:<\/p>\n
%lsmagic<\/strong><\/p>\nHelp with magic commands<\/strong><\/h4>\nTo view further information on a particular magic command, select it then press Shift + Tab.<\/strong><\/p>\n\u201cReady to take your data science skills to the next level? Sign up for a free demo today!\u201d<\/a><\/strong><\/p>\nView a List of Shortcuts<\/strong><\/h3>\nOver time, you’ll be able to work with Jupyter Notebooks more efficiently if you know helpful shortcut keys. There is no possibility to memorise every shortcut on the extensive list at once. Here’s where it’s useful to see a list of shortcuts:<\/p>\n
\n- Get a Jupyter Notebook open.<\/li>\n
- Press Esc to enter the command mode.<\/li>\n
- Hit the H key.<\/li>\n
- View the complete list of shortcuts.<\/li>\n<\/ul>\n
Measure Cell Execution Time<\/strong><\/h3>\nUse the magic command %%timeit to call timeit. Rather to estimating the time it takes to execute a single line of code, %%timeit determines how long it takes to run all of the code within a Jupyter notebook cell. To utilise it, just start a cell with %%timeit at the top and execute the cell.<\/p>\n
%%timeit<\/strong><\/p>\nimport pandas as pd<\/strong><\/p>\ndf = pd.DataFrame({‘a’: range(100000)})<\/strong>
\ndf[‘b’] = df[‘a’] * 5<\/strong><\/p>\n657 \u00b5s \u00b1 6.73 \u00b5s per loop (mean \u00b1 std. dev. of 7 runs, 1000 loops each)<\/strong><\/p>\nAdd Multiple Cursors<\/strong><\/h3>\nWhen modifying code, use numerous cursors to save time.<\/p>\n
Windows<\/strong>: Drag your cursor by holding alt and left-clicking.
\nMac<\/strong>: Drag your cursor using option + left-click.<\/p>\nExtensions to Jupyter Notebooks<\/strong><\/h3>\nThe Jupyter Notebook is an excellent tool, yet a basic notebook lacks of functions. Here’s where the extensions start to work.<\/p>\n
\n- To install the extensions, type the following command into the command line: pip install jupyter_contrib_nbextensions && jupyter contrib nbextension install<\/strong><\/li>\n
- Then, open a Jupyter Notebook and navigate to the “Nbextensions” tab:
\n![\"Jupyter\"](\"https:\/\/entri.app\/blog\/wp-content\/uploads\/2024\/02\/Jupyter.webp\")
<\/li>\n - Click the extensions to make them active. The notebook toolbar now has these buttons:<\/li>\n<\/ul>\n
![\"Jupyter.\"](\"https:\/\/entri.app\/blog\/wp-content\/uploads\/2024\/02\/Jupyter-1.webp\")
<\/p>\n
\n- For example, you can easily add structure and style to your code with just one click by using the Code Prettify extension<\/li>\n<\/ul>\n
Set Alarm for Program Completion<\/strong><\/h3>\nSet an alarm when your programme is finished running.<\/p>\n
Windows<\/strong><\/h4>\nYou may set up an alarm to beep on Windows. As an illustration, let’s set a 440Hz<\/strong> alarm for one second, or 1000ms:<\/p>\nimport winsound<\/strong><\/p>\nduration = 1000<\/strong>
\nfreq = 440<\/strong><\/p>\nwinsound.Beep(freq, duration)<\/strong><\/p>\nMac<\/strong><\/h3>\nWhen your programme finishes, you can use the built-in say<\/em> command to hear something on your Mac instead of a blaring alarm:<\/p>\nimport os<\/strong>
\nos.system(‘say “Your program has now finished”‘)<\/strong><\/p>\nView the Documentation of a Method<\/strong><\/h3>\nTo access a method’s documentation, select it and use Shift + Tab. Press the + icon located at the upper right corner of the modal to extend it further.<\/p>\n
Extend the Number of Columns and Rows Shown in pandas<\/strong><\/h3>\nA pandas table has a maximum amount of rows and columns that it can display. But that’s something you can alter.<\/p>\n
Let’s say, for example, that the maximum output rows and columns are 1000<\/strong>.<\/p>\nimport pandas as pd<\/strong>
\npd.set_option(‘display.max_rows’, 1000)<\/strong>
\npd.set_option(‘display.max_columns’, 1000)<\/strong><\/p>\nHide Unnecessary Output<\/strong><\/h3>\nTo prevent an obnoxious output, finish a statement with a semicolon. For instance, a rather redundant output appears before the graph when using Matplotlib for plotting.<\/p>\n
![\"\"](\"https:\/\/entri.app\/blog\/wp-content\/uploads\/2024\/02\/jupyter-2.webp\")
<\/p>\n
Put a semicolon after the plotting statement to remove this:<\/p>\n
plt.scatter(x,y);<\/strong><\/p>\n![\"Jupyter](\"https:\/\/entri.app\/blog\/wp-content\/uploads\/2024\/02\/Jupyter-3.webp\")
<\/p>\n
Sharing Notebooks<\/strong><\/h3>\nSharing reports or code source with outputs is essential and you can accomplish it in a variety of ways:<\/p>\n
\n- Use the File > Download as > HTML option to convert Notebooks into HTML files.<\/li>\n
- Use File > Download as > PDF to save notebooks as PDFs.<\/li>\n
- Notebooks can be downloaded as Markdown or saved as a Markdown file.<\/li>\n
- Build blogs with Pelican<\/a>.<\/li>\n
- Share the.ipynb file with others by uploading it to Google Colab.<\/li>\n
- Use GitHub Gits to distribute the Notebook file to the general audience.<\/li>\n
- Use nbviewer<\/a> to render the notebook after hosting your file on an external server or the cloud.<\/li>\n<\/ul>\n
Installing Other Kernels for Jupyter Notebook<\/strong><\/h3>\nWhile the Python kernel is well-known, you can run code in any language by installing different kernels.<\/p>\n
For instance, you must install R and IRkernel inside the R environment in order to use the R programming language in a Jupyter notebook.<\/p>\n
Do you exit your notebook to execute a shell command?<\/p>\n
An exclamation mark can be used before a command in your Jupyter Notebook to execute shell commands.<\/p>\n
For example:<\/p>\n
!pip install Tkinter<\/strong><\/p>\n There are many useful magic commands in Jupyter to help you with your daily tasks. One quick fix for common issues is to use a magic command, which can list every file in the current directory, among other things. A magic command is handy because it may be added directly to Python code. A magic command starts with %.<\/strong><\/p>\n These are few helpful magic commands:<\/p>\n Print the current working directory<\/strong> # Show all the files in the current directory<\/strong> # Change the working directory<\/strong> # List all the variables<\/strong> There is a long list of helpful magic commands. Use this to see a list of all the magic commands that are available:<\/p>\n %lsmagic<\/strong><\/p>\n To view further information on a particular magic command, select it then press Shift + Tab.<\/strong><\/p>\n \u201cReady to take your data science skills to the next level? Sign up for a free demo today!\u201d<\/a><\/strong><\/p>\n Over time, you’ll be able to work with Jupyter Notebooks more efficiently if you know helpful shortcut keys. There is no possibility to memorise every shortcut on the extensive list at once. Here’s where it’s useful to see a list of shortcuts:<\/p>\n Use the magic command %%timeit to call timeit. Rather to estimating the time it takes to execute a single line of code, %%timeit determines how long it takes to run all of the code within a Jupyter notebook cell. To utilise it, just start a cell with %%timeit at the top and execute the cell.<\/p>\n %%timeit<\/strong><\/p>\n import pandas as pd<\/strong><\/p>\n df = pd.DataFrame({‘a’: range(100000)})<\/strong> 657 \u00b5s \u00b1 6.73 \u00b5s per loop (mean \u00b1 std. dev. of 7 runs, 1000 loops each)<\/strong><\/p>\n When modifying code, use numerous cursors to save time.<\/p>\n Windows<\/strong>: Drag your cursor by holding alt and left-clicking. The Jupyter Notebook is an excellent tool, yet a basic notebook lacks of functions. Here’s where the extensions start to work.<\/p>\n Set an alarm when your programme is finished running.<\/p>\n You may set up an alarm to beep on Windows. As an illustration, let’s set a 440Hz<\/strong> alarm for one second, or 1000ms:<\/p>\n import winsound<\/strong><\/p>\n duration = 1000<\/strong> winsound.Beep(freq, duration)<\/strong><\/p>\n When your programme finishes, you can use the built-in say<\/em> command to hear something on your Mac instead of a blaring alarm:<\/p>\n import os<\/strong> To access a method’s documentation, select it and use Shift + Tab. Press the + icon located at the upper right corner of the modal to extend it further.<\/p>\n A pandas table has a maximum amount of rows and columns that it can display. But that’s something you can alter.<\/p>\n Let’s say, for example, that the maximum output rows and columns are 1000<\/strong>.<\/p>\n import pandas as pd<\/strong> To prevent an obnoxious output, finish a statement with a semicolon. For instance, a rather redundant output appears before the graph when using Matplotlib for plotting.<\/p>\n Put a semicolon after the plotting statement to remove this:<\/p>\n plt.scatter(x,y);<\/strong><\/p>\n Sharing reports or code source with outputs is essential and you can accomplish it in a variety of ways:<\/p>\n While the Python kernel is well-known, you can run code in any language by installing different kernels.<\/p>\n For instance, you must install R and IRkernel inside the R environment in order to use the R programming language in a Jupyter notebook.<\/p>\nMagic Commands<\/strong><\/h3>\n
\n%pwd<\/strong><\/p>\n
\n%ls<\/strong><\/p>\n
\n%ls [PATH_TO_DIR]<\/strong><\/p>\n
\n%Who<\/strong><\/p>\nView all the magic commands<\/strong><\/h4>\n
Help with magic commands<\/strong><\/h4>\n
View a List of Shortcuts<\/strong><\/h3>\n
\n
Measure Cell Execution Time<\/strong><\/h3>\n
\ndf[‘b’] = df[‘a’] * 5<\/strong><\/p>\nAdd Multiple Cursors<\/strong><\/h3>\n
\nMac<\/strong>: Drag your cursor using option + left-click.<\/p>\nExtensions to Jupyter Notebooks<\/strong><\/h3>\n
\n
\n<\/li>\n<\/p>\n\n
Set Alarm for Program Completion<\/strong><\/h3>\n
Windows<\/strong><\/h4>\n
\nfreq = 440<\/strong><\/p>\nMac<\/strong><\/h3>\n
\nos.system(‘say “Your program has now finished”‘)<\/strong><\/p>\nView the Documentation of a Method<\/strong><\/h3>\n
Extend the Number of Columns and Rows Shown in pandas<\/strong><\/h3>\n
\npd.set_option(‘display.max_rows’, 1000)<\/strong>
\npd.set_option(‘display.max_columns’, 1000)<\/strong><\/p>\nHide Unnecessary Output<\/strong><\/h3>\n
<\/p>\n<\/p>\nSharing Notebooks<\/strong><\/h3>\n
\n
Installing Other Kernels for Jupyter Notebook<\/strong><\/h3>\n