From 723a14719537eb3dbee3988e450782b84b86812d Mon Sep 17 00:00:00 2001 From: John Sundh Date: Thu, 21 Nov 2024 10:00:12 +0100 Subject: [PATCH 01/14] Begin switch to jupyter lab --- pages/jupyter.qmd | 156 ++++++++++++++++++++-------------------------- 1 file changed, 66 insertions(+), 90 deletions(-) diff --git a/pages/jupyter.qmd b/pages/jupyter.qmd index b56a8424..0c538ec0 100644 --- a/pages/jupyter.qmd +++ b/pages/jupyter.qmd @@ -55,23 +55,15 @@ haven't done so already. Then open up a terminal and go to ## The basics -One thing that sets Jupyter Notebook apart from what you might be used to is -that it's a web application, _i.e._ you edit and run your code from your -browser. But first you have to start the Jupyter Notebook server. At this -point you may either try the classic notebook interface by running: - -```bash -jupyter notebook --allow-root -``` - -Or give the more feature-rich Jupyter lab interface a try by running: +One thing that sets Jupyter apart from what you might be used to is that it's a +web application, _i.e._ you edit and run your code from your browser. But first +you have to start the Jupyter server. Do this by running: ```bash jupyter lab --allow-root ``` -Whichever interface you choose you should see something similar to this -printed to your terminal: +You should see something similar to this printed to your terminal: ```no-highlight [I 18:02:26.722 NotebookApp] Serving notebooks from local directory: /Users/john/workshop-reproducible-research/tutorials/jupyter @@ -90,68 +82,45 @@ printed to your terminal: ::: {.callout-tip title="A note for Windows users"} If you see the error message `Start : This command cannot be run due to the error: The system cannot find the file specified. ...` then try starting -Jupyter with `jupyter notebook --no-browser` then copy the URL given into the +Jupyter with `jupyter lab --no-browser` then copy the URL given into the browser directly. ::: -::: {.callout-note title="Jupyter notebook versions"} -Depending on what version of the `notebook` conda package you have installed, -the interface may look slightly different. The screenshots in this tutorial -are from version 7, an update which has brought the 'classic' Jupyter notebook -closer to the Jupyter lab interface. Read more about this update at the -[Jupyter homepage](https://jupyter-notebook.readthedocs.io/en/latest/migrate_to_notebook7.html). -::: - -The Jupyter Notebook/Lab interface probably opened up a web browser for you +The Jupyter Lab interface probably opened up a web browser for you automatically, otherwise go to the address specified in the message in the -terminal. Note that the server is running locally (as -`http://localhost:8888`) so this does not require that you have an active -internet connection. Also note that it says: +terminal under `Or copy and paste one of these URLs:`. -```no-highlight -Serving notebooks from local directory: -``` - -Everything you do in your Notebook session will be stored in this directory, so -you won't lose any work if you shut down the server. - -> ![](images/jupyter_dashboard.png){ width=700px } - -What you're looking at is the Notebook dashboard. This is where you manage your -files, notebooks, and kernels. The Files tab shows the files in your directory. -The Running tab keeps track of all your processes. - -The Jupyter lab dashboard should look something like this: +What you're looking at is the dashboard which should look something like this: > ![](images/jupyterlab_dashboard.png){ width=700px } -Let's start by creating an empty notebook. You can do this by selecting the -Files tab and clicking New > Notebook. When the notebook opens, select the -suggested Python 3 kernel from the drop-down menu. - -This will open up a new tab or window looking like this: - -> ![](images/jupyter_empty_nb.png){ width=700px } +In the left margin you have a few icons, the first being a folder icon. This is +the **File browser**, which shows the files in your directory. The next icon is +the **Running terminals and Kernels** tab, which shows you the running kernels. +The third icon is the **Table of contents**, which shows the outline of your +active notebook (if you have one open). This table will be populated with +headers from your markdown cells. The fourth icon is the **Extensions Manager** +tab, where you can install and manage extensions. -Start by giving your notebook a name by clicking on the text "Untitled" at the -top of the page. Enter "jupyter-tutorial.ipynb". +The main part of the dashboard is occupied by what's called the **Main work +area**. This is where you can open and work on notebooks, text files, terminals +and so on. These are opened in tabs, and you can have several tabs open at the +same time. These tabs can be moved, resized, and split by dragging them around. -Note that for most of this tutorial we will describe how you work in the actual -notebook and not devote a lot of time to the extra features available in the -Jupyter lab interface. +Let's start by creating an empty notebook. You can do this by selecting the +Files tab and clicking New > Notebook. From the drop-down menu that appears, +select the `jupyter-env` kernel. -::: {.callout-tip} -If you want to start Jupyter Notebooks on a cluster that you SSH to (_e.g._ -Uppmax) see the section in the [Extra material](#extra-material). -::: +Start by giving your notebook a name by right-clicking on the text "Untitled.ipynb" at the +top of the panel then clicking "Rename Notebook". Enter "jupyter-tutorial.ipynb". -Jupyter notebooks are made up of cells, and you are currently standing in -the first cell in your notebook. Your cursor should be blinking in this cell, -indicating that you are in "Edit mode" meaning that you can type text in the -cell. Pressing the `Esc` key puts you in "Command mode" which allows you to -manipulate the notebook as a whole, more on this later. +Jupyter notebooks are made up of cells, and you should have one cell in your +newly created notebook. Clicking inside the cell puts you in "Edit mode" meaning +that you can type text in the cell. Pressing the `Esc` key puts you in "Command +mode" which allows you to manipulate the notebook as a whole, more on this +later. -Cells in Jupyter notebooks can be of two types:*markdown* or *code*. +Cells in Jupyter notebooks can be of two types: *markdown* or *code*. - **Markdown:** @@ -185,23 +154,18 @@ the menus. You can also view this list of shortcuts from the **Help** menu under | `ctrl-enter` | Run the cell | | `shift-enter` | Run the cell and select the cell below | | `alt-enter` | Run the cell and insert a new cell below | -| `s` | Save the notebook | -| `tab` | For code completion or indentation | | `m,y` | Toggle between Markdown and Code cells | | `d-d` | Delete a cell | | `a` | Insert cells above current cell | | `b` | Insert cells below current cell | | `x` | Cut currently selected cells | | `v` | Paste cell below | -| `o` | Toggle output of current cell | ## Writing markdown -Let's use our first cell to create a header. Change the format from Code to -Markdown using the drop-down list in the Notebook Toolbar, or by pressing the -`m` key when in command mode. Double click on the cell, or hit `enter` to enter -editing mode and input "# My notebook" ("#" is used in Markdown for header 1). -Run the cell with `ctrl`-`enter` (`cmd`-`enter` on Mac). +Let's use our first cell to create a header. Change the format from Code to by +pressing the `m` key when in command mode. Click inside the cell and input `# My +notebook`. Run the cell with `ctrl`-`enter` (`cmd`-`enter` on Mac). Markdown is a simple way to structure your notebook into sections with descriptive notes, lists, links, images etc. @@ -238,9 +202,10 @@ See [here](https://jupyter-notebook.readthedocs.io/en/stable/examples/Notebook/W ## Writing code -Now let's write some code! Since we chose a Python kernel, Python would be the -native language to run in a cell. Enter this code in the second cell and run -it: +Now let's write some code! Create a new cell either by clicking the `+` in the +tab menu or by pressing `b` when in command mode. Since we chose a Python +kernel, Python would be the native language to run in a cell. Enter this code in +the second cell and run it: ```python print("Hello world!") @@ -253,12 +218,13 @@ one run, while you work *in* a Jupyter notebook in a different way. This requires some special attention when it comes to reproducibility, which we will get back to in the [reproducibility](#reproducibility) section. -What **is** a Jupyter notebook? Let's look a closer at the notebook we're +What **is** a Jupyter notebook? Let's look closer at the notebook we're currently working in. Jupyter Notebooks are autosaved every minute or so, so you will already have it available. We can be a little meta and do this from within the notebook itself, by running some shell commands in a code cell. This very handy functionality is possible by prepending the command with `!`. Try adding -`!ls` to a code cell and run it. This will list the files in the current directory. +`!ls` to a code cell and run it. This will list the files in the current +directory. Aha, we have a new file called `jupyter-tutorial.ipynb`! This is our notebook. Look at the first ten lines of the file by using `!head jupyter-tutorial.ipynb`. @@ -283,10 +249,6 @@ Now create a new cell and add: print_me("Hi!") ``` -Your notebook should now look something like this. - -> ![](images/jupyter_basic_update.png){ width=700px } - The focus of this tutorial is not on how to write Markdown or Python; you can make really pretty notebooks with Markdown and you can code whatever you want with Python. Rather, we will focus on the Jupyter Notebook features that allow @@ -295,6 +257,7 @@ you to do a little more than that. ::: {.callout-note title="Quick recap"} In this section we've learned: +- How to open and work with Jupyter lab - That a Jupyter notebook consists of a series of cells, and that they can be either markdown or code cells. - That we execute the code in a code cell with the kernel that we chose @@ -313,12 +276,13 @@ power of Jupyter notebooks. There are two types of magics: - **Cell magics**: Commands that start with `%%` and then apply to the whole cell. Must be written on the first line of a cell. -Now list all available magics with `%lsmagic` (which itself is a magic). You -add a question mark to a magic to show the help (_e.g._ `%lsmagic?`). Some of -them act as shortcuts for commonly used shell commands (`%ls`, `%cp`, `%cat`, -..). Others are useful for debugging and optimizing your code (`%timeit`, -`%debug`, `%prun`, ..). For more information see the -[magics documentation](https://ipython.readthedocs.io/en/stable/interactive/magics.html). +Now list all available magics with by adding `%lsmagic` (which itself is a +magic) to a cell and running it. You can add a question mark to a magic to show +the help (_e.g._ `%lsmagic?`). Some of them act as shortcuts for commonly used +shell commands (`%ls`, `%cp`, `%cat`, ..). Others are useful for debugging and +optimizing your code (`%timeit`, `%debug`, `%prun`, ..). For more information +see the [magics +documentation](https://ipython.readthedocs.io/en/stable/interactive/magics.html). A very useful magic, in particular when using shell commands a lot in your work, is `%%capture`. This will capture the stdout/stderr of any code cell and @@ -340,8 +304,11 @@ print("stdout:" + output.stdout) print("stderr:" + output.stderr) ``` -> **Tip**
-> You can capture the output of some magics directly like this: `my_dir = %pwd`. +::: {.callout-tip} + +You can capture the output of some magics directly like this: `my_dir = %pwd`. + +::: The `%%script` magic is used for specifying a program (Bash, Perl, Ruby, ..) with which to run the code (similar to a shebang). For some languages it's @@ -361,10 +328,19 @@ environment you're using for this tutorial. However, you also have to load it by running `%load_ext rpy2.ipython` in a cell. ::: -Try this out if you know any of the languages above. Otherwise you can always -try to print the quadratic formula with LaTeX! +Try this out if you know any of the languages above. For example, to run some +simple R code: + +``` +%%R +print(paste("Hello","world", sep=" ")) +``` + + +Or to print the quadratic formula with LaTeX: ```no-highlight +%%latex \begin{array}{*{20}c} {x = \frac{{ - b \pm \sqrt {b^2 - 4ac} }}{{2a}}} & {{\rm{when}}} & {ax^2 + bx + c = 0} \\ \end{array} ``` @@ -1163,7 +1139,7 @@ general: - A [guide](http://ipywidgets.readthedocs.io/en/stable/index.html) to using widgets for creating interactive notebooks. -## Running Jupyter notebooks on a cluster +### Running Jupyter notebooks on a cluster - Login to Uppmax, making sure to use a specific login node, _e.g._ `rackham1`: @@ -1223,7 +1199,7 @@ Connect to the Jupyter server by opening `localhost:8080` in your browser. When prompted, paste the token you got when starting the server on Uppmax and set a new password. -## Using Binder to share interactive notebooks +### Using Binder to share interactive notebooks [Binder](https://mybinder.org/) is a service that allows you to share Jupyter notebooks with others, while also allowing them to run the notebooks in the From a5245ad20a4afd2c82449d614a95faadecf8695e Mon Sep 17 00:00:00 2001 From: John Sundh Date: Thu, 21 Nov 2024 10:15:45 +0100 Subject: [PATCH 02/14] Remove example file --- .../jupyter/jupyter-tutorial-example.ipynb | 4074 ----------------- 1 file changed, 4074 deletions(-) delete mode 100644 tutorials/jupyter/jupyter-tutorial-example.ipynb diff --git a/tutorials/jupyter/jupyter-tutorial-example.ipynb b/tutorials/jupyter/jupyter-tutorial-example.ipynb deleted file mode 100644 index 4ebd0c81..00000000 --- a/tutorials/jupyter/jupyter-tutorial-example.ipynb +++ /dev/null @@ -1,4074 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "id": "6e87037d-b180-4f51-944c-aaa1d8948f27", - "metadata": {}, - "source": [ - "# The basics" - ] - }, - { - "cell_type": "markdown", - "id": "07bb04c6", - "metadata": {}, - "source": [ - "## Introduction\n", - "In this notebook I will try out some of the **fantastic** concepts of Jupyter\n", - "Notebooks.\n", - "\n", - "## Markdown basics\n", - "Examples of text attributes are:\n", - "\n", - "* *italics*\n", - "* **bold**\n", - "* `monospace`\n", - "\n", - "Sections can be separated by horizontal lines." - ] - }, - { - "cell_type": "markdown", - "id": "02726021", - "metadata": {}, - "source": [ - "---\n", - "\n", - "Blockquotes can be added, for instance to insert a Monty Python quote:\n", - "\n", - "> Spam!\n", - "> Spam!\n", - "> Spam!\n", - "> Spam!\n", - "\n", - "See [here](https://jupyter-notebook.readthedocs.io/en/stable/examples/Notebook/Working%20With%20Markdown%20Cells.html) for more information." - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "id": "8fc746f0", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Hello world!\n" - ] - } - ], - "source": [ - "print(\"Hello world!\")" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "id": "c4f8feff", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "environment.yml references.bib\n", - "\u001b[1m\u001b[36mintermediate\u001b[m\u001b[m \u001b[1m\u001b[36mresults\u001b[m\u001b[m\n", - "jupyter-tutorial-example.ipynb supplementary_material.ipynb\n" - ] - } - ], - "source": [ - "!ls" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "id": "77ec8160", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "head: jupyter-tutorial.ipynb: No such file or directory\n" - ] - } - ], - "source": [ - "!head jupyter-tutorial.ipynb" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "id": "96582697", - "metadata": {}, - "outputs": [], - "source": [ - "def print_me(str):\n", - " print(str)" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "id": "8b4b3e37", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Hi!\n" - ] - } - ], - "source": [ - "print_me(\"Hi!\")" - ] - }, - { - "cell_type": "markdown", - "id": "25825c38-522e-4696-9f6b-4dc915ffdada", - "metadata": {}, - "source": [ - "# Magics" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "id": "996fa490", - "metadata": {}, - "outputs": [], - "source": [ - "%load_ext rpy2.ipython" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "id": "739326dd", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[1] \"Hello World\"\n" - ] - } - ], - "source": [ - "%%R\n", - "paste(\"Hello\",\"World\")" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "id": "7cbafd35", - "metadata": {}, - "outputs": [ - { - "data": { - "text/latex": [ - "\\begin{array}{*{20}c} {x = \\frac{{ - b \\pm \\sqrt {b^2 - 4ac} }}{{2a}}} & {{\\rm{when}}} & {ax^2 + bx + c = 0} \\\\ \\end{array}\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "%%latex\n", - "\\begin{array}{*{20}c} {x = \\frac{{ - b \\pm \\sqrt {b^2 - 4ac} }}{{2a}}} & {{\\rm{when}}} & {ax^2 + bx + c = 0} \\\\ \\end{array}" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "id": "f0405fcb", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "33.333333333333336" - ] - }, - "execution_count": 9, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "float(100/3)" - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "id": "32991924", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "'%.4f'" - ] - }, - "execution_count": 10, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "%precision 4" - ] - }, - { - "cell_type": "markdown", - "id": "6b5a6fef-b005-4a43-90a5-53de317b4063", - "metadata": {}, - "source": [ - "# Plotting" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "id": "1137e967", - "metadata": {}, - "outputs": [ - { - "data": { - "application/pdf": 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# Import packages\n", - "import numpy as np\n", - "import matplotlib.pyplot as plt\n", - "import matplotlib_inline\n", - "matplotlib_inline.backend_inline.set_matplotlib_formats('pdf', 'svg')\n", - "# Generate a set of evenly spaced numbers between 0 and 100\n", - "x = np.linspace(0,3*np.pi,100)\n", - "# Use the sine function to generate y-values\n", - "y = np.sin(x)\n", - "# Plot the data\n", - "line, = plt.plot(x, y, color='red', linestyle=\"-\")" - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "id": "62ce1f0d", - "metadata": {}, - "outputs": [], - "source": [ - "import seaborn as sns" - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "id": "5aae0487", - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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speciesislandbill_length_mmbill_depth_mmflipper_length_mmbody_mass_gsex
0AdelieTorgersen39.118.7181.03750.0Male
1AdelieTorgersen39.517.4186.03800.0Female
2AdelieTorgersen40.318.0195.03250.0Female
3AdelieTorgersenNaNNaNNaNNaNNaN
4AdelieTorgersen36.719.3193.03450.0Female
\n", - "
" - ], - "text/plain": [ - " species island bill_length_mm bill_depth_mm flipper_length_mm \\\n", - "0 Adelie Torgersen 39.1 18.7 181.0 \n", - "1 Adelie Torgersen 39.5 17.4 186.0 \n", - "2 Adelie Torgersen 40.3 18.0 195.0 \n", - "3 Adelie Torgersen NaN NaN NaN \n", - "4 Adelie Torgersen 36.7 19.3 193.0 \n", - "\n", - " body_mass_g sex \n", - "0 3750.0 Male \n", - "1 3800.0 Female \n", - "2 3250.0 Female \n", - "3 NaN NaN \n", - "4 3450.0 Female " - ] - }, - "execution_count": 13, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "penguins = sns.load_dataset(\"penguins\")\n", - "# Look at first 5 lines of the data\n", - "penguins.head(5)" - ] - }, - { - "cell_type": "code", - "execution_count": 14, - "id": "7ff1ac64", - "metadata": {}, - "outputs": [ - { - "data": { - "application/pdf": 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AiCDrArIYLJQ2NhMyWc4D7Q3JDVpg16kbUYuCK5TWCXSiVsSqzOCz5tZ2N0Mt8uCoffH6aFaXYIXRS/VYeF+FPpipmXbukkJ64U07IsweCqQyOy0rtXvE6m6B+j/LUvD9yff4Ha8PzfxcnAplbmRzdHJlYW0KZW5kb2JqCjI2IDAgb2JqCjw8IC9MZW5ndGggOTQgL0ZpbHRlciAvRmxhdGVEZWNvZGUgPj4Kc3RyZWFtCnicRY3BEcAgCAT/VEEJCgraTyaTh/b/jRAyfGDnDu6EBQu2eUYfBZUmXhVYB0pj3FCPQL3hci3J3AUPcCd/2tBUnJbTd2mRSVUp3KQSef8OZyaQqHnRY533C2P7IzwKZW5kc3RyZWFtCmVuZG9iagoyNyAwIG9iago8PCAvTGVuZ3RoIDM0MSAvRmlsdGVyIC9GbGF0ZURlY29kZSA+PgpzdHJlYW0KeJxFUktuRDEI279TcIFI4ZeQ87Squpjef1ubTNXN4AlgbHjLU6ZkyrC5JSMk15RPfSJDrKb8NHIkIqb4SQkFdpWPx2tLrI3skagUn9rx47H0RqbZFVr17tGlzaJRzcrIOcgQoZ4VurJ71A7Z8HpcSLrvlM0hHMv/UIEsZd1yCiVBW9B37BHfDx2ugiuCYbBrLoPtZTLU//qHFlzvffdixy6AFqznvsEOAKinE7QFyBna7jYpaABVuotJwqPyem52omyjVen5HAAzDjBywIglWx2+0d4Aln1d6EWNiv0rQFFZQPzI1XbB3jHJSHAW5gaOvXA8xZlwSzjGAkCKveIYevAl2OYvV66ImvAJdbpkL7zCntrm50KTCHetAA5eZMOtq6Oolu3pPIL2Z0VyRozUizg6IZJa0jmC4tKgHlrjXDex4m0jsblX3+4f4ZwvXPbrF0vshMQKZW5kc3RyZWFtCmVuZG9iagoyOCAwIG9iago8PCAvTGVuZ3RoIDcyIC9GaWx0ZXIgL0ZsYXRlRGVjb2RlID4+CnN0cmVhbQp4nDMyt1AwULA0ARKGFiYK5mYGCimGXEC+qYm5Qi4XSAzEygGzDIC0JZyCiGeAmCBtEMUgFkSxmYkZRB2cAZHL4EoDACXbFskKZW5kc3RyZWFtCmVuZG9iagoyOSAwIG9iago8PCAvTGVuZ3RoIDQ3IC9GaWx0ZXIgL0ZsYXRlRGVjb2RlID4+CnN0cmVhbQp4nDMyt1AwULA0ARKGFiYK5mYGCimGXJYQVi4XTCwHzALRlnAKIp7BlQYAuWcNJwplbmRzdHJlYW0KZW5kb2JqCjMwIDAgb2JqCjw8IC9MZW5ndGggMjU4IC9GaWx0ZXIgL0ZsYXRlRGVjb2RlID4+CnN0cmVhbQp4nEWRS3IEIAhE956CI4D85DyTSmUxuf82Dc5kNnaXqP2ESiOmEiznFHkwfcnyzWS26Xc5VjsbBRRFKJjJVeixAqs7U8SZa4lq62Nl5LjTOwbFG85dOalkcaOMdVR1KnBMz5X1Ud35dlmUfUcOZQrYrHMcbODKbcMYJ0abre4O94kgTydTR8XtINnwByeNfZWrK3CdbPbRSzAOBP1CE5jki0DrDIHGzVP05BLs4+N254Fgb3kRSNkQyJEhGB2Cdp1c/+LW+b3/cYY7z7UZrhzv4neY1nbHX2KSFXMBi9wpqOdrLlrXGTrekzPH5Kb7hs65YJe7g0zv+T/Wz/r+Ax4pZvoKZW5kc3RyZWFtCmVuZG9iagozMSAwIG9iago8PCAvTGVuZ3RoIDE2MyAvRmlsdGVyIC9GbGF0ZURlY29kZSA+PgpzdHJlYW0KeJxFkDsSAyEMQ3tOoSP4IwM+z2YyKTb3b2PYbFLA01ggg7sTgtTagonogoe2Jd0F760EZ2P86TZuNRLkBHWAVqTjaJRSfbnFaZV08Wg2cysLrRMdZg56lKMZoBA6Fd7touRypu7O+UNw9V/1v2LdOZuJgcnKHQjN6lPc+TY7orq6yf6kx9ys134r7FVhaVlLywm3nbtmQAncUznaqz0/Hwo69gplbmRzdHJlYW0KZW5kb2JqCjMyIDAgb2JqCjw8IC9MZW5ndGggMjE4IC9GaWx0ZXIgL0ZsYXRlRGVjb2RlID4+CnN0cmVhbQp4nD1QuY0EMQzLXYUaWMB67alnFotLpv/0SPn2ItEWRVIqNZmSKS91lCVZU946fJbEDnmG5W5kNiUqRS+TsCX30ArxfYnmFPfd1ZazQzSXaDl+CzMqqhsd00s2mnAqE7qg3MMz+g1tdANWhx6xWyDQpGDXtiByxw8YDMGZE4siDEpNBv+uco+fXosbPsPxQxSRkg7mNf9Y/fJzDa9TjyeRbm++4l6cqQ4DERySmrwjXVixLhIRaTVBTc/AWi2Au7de/hu0I7oMQPaJxHGaUo6hv2twpc8v5SdT2AplbmRzdHJlYW0KZW5kb2JqCjMzIDAgb2JqCjw8IC9MZW5ndGggODMgL0ZpbHRlciAvRmxhdGVEZWNvZGUgPj4Kc3RyZWFtCnicRYy7DcAwCER7pmAEfib2PlGUwt6/DRAlbrgn3T1cHQmZKW4zw0MGngwshl1xgfSWMAtcR1COneyjYdW+6gSN9aZS8+8PlJ7srOKG6wECQhpmCmVuZHN0cmVhbQplbmRvYmoKMzQgMCBvYmoKPDwgL0xlbmd0aCAxNjAgL0ZpbHRlciAvRmxhdGVEZWNvZGUgPj4Kc3RyZWFtCnicRZA5EgMxCARzvYInSFyC96zLtcH6/6kH1kei6QI0HLoWTcp6FGg+6bFGobrQa+gsSpJEwRaSHVCnY4g7KEhMSGOSSLYegyOaWLNdmJlUKrNS4bRpxcK/2VrVyESNcI38iekGVPxP6lyU8E2Dr5Ix+hhUvDuDjEn4XkXcWjHt/kQwsRn2CW9FJgWEibGp2b7PYIbM9wrXOMfzDUyCN+sKZW5kc3RyZWFtCmVuZG9iagozNSAwIG9iago8PCAvTGVuZ3RoIDMzNCAvRmlsdGVyIC9GbGF0ZURlY29kZSA+PgpzdHJlYW0KeJwtUktyxSAM23MKXaAz+AfkPOl0uni9/7aSk0VGDmD0MeWGiUp8WSC3o9bEt43MQIXhr6vMhc9I28g6iMuQi7iSLYV7RCzkMcQ8xILvq/EeHvmszMmzB8Yv2XcPK/bUhGUh48UZ2mEVx2EV5FiwdSGqe3hTpMOpJNjji/8+xXMtBC18RtCAX+Sfr47g+ZIWafeYbdOuerBMO6qksBxsT3NeJl9aZ7k6Hs8Hyfau2BFSuwIUhbkzznPhKNNWRrQWdjZIalxsb479WErQhW5cRoojkJ+pIjygpMnMJgrij5wecioDYeqarnRyG1Vxp57MNZuLtzNJZuu+SLGZwnldOLP+DFNmtXknz3Ki1KkI77FnS9DQOa6evZZZaHSbE7ykhM/GTk9Ovlcz6yE5FQmpYlpXwWkUmWIJ2xJfU1FTmnoZ/vvy7vE7fv4BLHN8cwplbmRzdHJlYW0KZW5kb2JqCjM2IDAgb2JqCjw8IC9MZW5ndGggMzQwIC9GaWx0ZXIgL0ZsYXRlRGVjb2RlID4+CnN0cmVhbQp4nDVSOW4EMQzr/Qp9IIBu2+/ZIEiR/L8NqdkUA3F0UpQ7WlR2y4eFVLXsdPm0ldoSN+R3ZYXECcmrEu1ShkiovFYh1e+ZMq+3NWcEyFKlwuSk5HHJgj/DpacLx/m2sa/lyB2PHlgVI6FEwDLFxOgals7usGZbfpZpwI94hJwr1i3HWAVSG9047Yr3oXktsgaIvZmWigodVokWfkHxoEeNffYYVFgg0e0cSXCMiVCRgHaB2kgMOXssdlEf9DMoMRPo2htF3EGBJZKYOcW6dPTf+NCxoP7YjDe/OirpW1pZY9I+G+2Uxiwy6XpY9HTz1seDCzTvovzn1QwSNGWNksYHrdo5hqKZUVZ4t0OTDc0xxyHzDp7DGQlK+jwUv48lEx2UyN8ODaF/Xx6jjJw23gLmoj9tFQcO4rPDXrmBFUoXa5L3AalM6IHp/6/xtb7X1x8d7YDGCmVuZHN0cmVhbQplbmRvYmoKMzcgMCBvYmoKPDwgL0xlbmd0aCAyNTEgL0ZpbHRlciAvRmxhdGVEZWNvZGUgPj4Kc3RyZWFtCnicLVFJcgNBCLvPK/SEZqffY5crh+T/1wjKBwYNi0B0WuKgjJ8gLFe85ZGraMPfMzGC3wWHfivXbVjkQFQgSWNQNaF28Xr0HthxmAnMk9awDGasD/yMKdzoxeExGWe312XUEOxdrz2ZQcmsXMQlExdM1WEjZw4/mTIutHM9NyDnRliXYZBuVhozEo40hUghhaqbpM4EQRKMrkaNNnIU+6Uvj3SGVY2oMexzLW1fz004a9DsWKzy5JQeXXEuJxcvrBz09TYDF1FprPJASMD9bg/1c7KT33hL584W0+N7zcnywlRgxZvXbkA21eLfvIjj+4yv5+f5/ANfYFuICmVuZHN0cmVhbQplbmRvYmoKMzggMCBvYmoKPDwgL0xlbmd0aCA1NCAvRmlsdGVyIC9GbGF0ZURlY29kZSA+PgpzdHJlYW0KeJwzNTBQMFDQtVTQNTI2VTA1BLINzUwVUgy54OxcCBMkn8MFUwlhgaRzECpzuDK40gBzUQ+PCmVuZHN0cmVhbQplbmRvYmoKMzkgMCBvYmoKPDwgL0xlbmd0aCAxNDEgL0ZpbHRlciAvRmxhdGVEZWNvZGUgPj4Kc3RyZWFtCnicPY/BDsMwCEPv+Qr/QKTYKaF8T6dqh+7/ryNLuwt6AmOMhdDQG6qaw4Zgm+PF0iVUa/gUxUAlN8iZYA6lpNIdR5F6YjgYXB60G47isej6EbuSZn3QxkK6JWiAe6xTadymcRPEHTUF6inqnKO8ELmfqWfYNJLdNLOSc7gNv3vPU9f/p6u8y/kFvXcu/gplbmRzdHJlYW0KZW5kb2JqCjQwIDAgb2JqCjw8IC9MZW5ndGggMjE1IC9GaWx0ZXIgL0ZsYXRlRGVjb2RlID4+CnN0cmV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\n", - " \n", - "\n" - ], - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "ax = sns.scatterplot(data=penguins, x=\"bill_length_mm\", y=\"body_mass_g\",\n", - " hue=\"species\")\n", - "# Modify the labels of the plot\n", - "ax.set_xlabel(\"Bill length (mm)\")\n", - "ax.set_ylabel(\"Body mass (g)\")\n", - "# Set legend position outside of plot\n", - "ax.legend(bbox_to_anchor=(1,1));\n", - "plt.savefig(\"scatterplot.pdf\", bbox_inches=\"tight\")" - ] - }, - { - "cell_type": "markdown", - "id": "88d80b88-ceb0-40ed-9711-be33137f1200", - "metadata": {}, - "source": [ - "# Widgets" - ] - }, - { - "cell_type": "code", - "execution_count": 16, - "id": "c89bffb3", - "metadata": {}, - "outputs": [], - "source": [ - "from ipywidgets import interactive, widgets" - ] - }, - { - "cell_type": "code", - "execution_count": 17, - "id": "41109426", - "metadata": {}, - "outputs": [], - "source": [ - "def scatterplot(x, y, hue, palette, size, color):\n", - " ax = sns.scatterplot(data=penguins, x=x, y=y, hue=hue, palette=palette, s=size)\n", - " ax.set_title(\"Penguin scatterplot\", color=color)" - ] - }, - { - "cell_type": "code", - "execution_count": 18, - "id": "701e3665", - "metadata": {}, - "outputs": [], - "source": [ - "colorpicker = widgets.ColorPicker(\n", - " concise=False,\n", - " description='Title color',\n", - " value='blue',\n", - " disabled=False\n", - ")\n", - "interactive_scatterplot = interactive(scatterplot, \n", - " x=[\"bill_length_mm\",\"bill_depth_mm\",\"flipper_length_mm\",\"body_mass_g\"], \n", - " y=[\"body_mass_g\",\"bill_length_mm\",\"bill_depth_mm\",\"flipper_length_mm\"],\n", - " hue=[\"species\",\"island\",\"sex\"],\n", - " palette=[\"Set1\",\"Set2\",\"Dark2\",\"Paired2\"],\n", - " size=(20, 100, 10),\n", - " color=colorpicker)" - ] - }, - { - "cell_type": "code", - "execution_count": 19, - "id": "66a5e7d6", - "metadata": {}, - "outputs": [ - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "4cef88f0e4a242799313c531cd0984e0", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - "interactive(children=(Dropdown(description='x', options=('bill_length_mm', 'bill_depth_mm', 'flipper_length_mm…" - ] - }, - "execution_count": 19, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "interactive_scatterplot" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python [conda env:jupyter-env] *", - "language": "python", - "name": "conda-env-jupyter-env-py" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.11.6" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} From ac163230141540646da2fbaaa2ffb28cbcb04311 Mon Sep 17 00:00:00 2001 From: John Sundh Date: Thu, 21 Nov 2024 10:17:42 +0100 Subject: [PATCH 03/14] Update jupyterlab dashboard 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