Finish the time-to-learn improvements (#649)

brian-rose · pre-commit-ci[bot] · web-flow · commit 3d97326c0e84 · 2026-06-12T10:24:12.000-07:00
* Consistent time-to-learn style * more time to learn * Cumulative time to learn * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci --------- Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
diff --git a/appendix/template.ipynb b/appendix/template.ipynb
@@ -66,11 +66,14 @@
     "| [Understanding of NetCDF](https://foundations.projectpythia.org/core/data-formats/netcdf-cf) | Helpful | Familiarity with metadata structure |\n",
     "| Project management | Helpful | |\n",
     "\n",
-    "- **Time to learn**: estimate in minutes. For a rough idea, use 5 mins per subsection, 10 if longer; add these up for a total. Safer to round up and overestimate.\n",
     "- **System requirements**:\n",
     "    - Populate with any system, version, or non-Python software requirements if necessary\n",
     "    - Otherwise use the concepts table above and the Imports section below to describe required packages as necessary\n",
-    "    - If no extra requirements, remove the **System requirements** point altogether"
+    "    - If no extra requirements, remove the **System requirements** point altogether\n",
+    "\n",
+    ":::{tip icon=false} ⏱️ Time to learn\n",
+    "Estimate in minutes. For a rough idea, use 5 mins per subsection, 10 if longer; add these up for a total. Safer to round up and overestimate.\n",
+    ":::"
    ]
   },
   {
diff --git a/core/cartopy.md b/core/cartopy.md
@@ -18,3 +18,7 @@ From the [Cartopy website](https://cartopy.readthedocs.io):
 Before working through the Cartopy notebooks in this section of Pythia Foundations, you should first have a basic knowledge of [Matplotlib](matplotlib.md).
 
 In addition, please note that the geographic-features library used by Cartopy makes use of shapefiles directly served by [Natural Earth](https://www.naturalearthdata.com/).
+
+:::{note icon=false} ⏱️ Time to learn (cumulative)
+40 minutes
+:::
diff --git a/core/cartopy/cartopy.ipynb b/core/cartopy/cartopy.ipynb
@@ -8,7 +8,9 @@
    "source": [
     "# Introduction to Cartopy\n",
     "\n",
-    "```{image} ../../images/cartopy_logo.png\n:width: 600\n```"
+    "```{image} ../../images/cartopy_logo.png\n",
+    ":width: 600\n",
+    "```"
    ]
   },
   {
@@ -45,7 +47,9 @@
     "| ------------------------------ | ---------- | --------------------- |\n",
     "| [Matplotlib](../matplotlib.md) | Necessary  | {cite:t}`Hunter:2007` |\n",
     "\n",
-    "- **Time to learn**: 30 minutes"
+    ":::{tip icon=false} ⏱️ Time to learn\n",
+    "30 minutes\n",
+    ":::"
    ]
   },
   {
diff --git a/core/data-formats.md b/core/data-formats.md
@@ -1,3 +1,7 @@
 # Data Formats
 
 Geoscientific data are commonly stored in self-describing files that are readable on multiple computing platforms and programming languages (including Python). This section contains a tutorial on the widely-used netCDF data format.
+
+:::{note icon=false} ⏱️ Time to learn (cumulative)
+1 hour
+:::
diff --git a/core/data-formats/netcdf-cf.ipynb b/core/data-formats/netcdf-cf.ipynb
@@ -35,7 +35,9 @@
     "| [Numpy Basics](../numpy/numpy-basics) | Necessary | |\n",
     "| [Datetime](../datetime.md) | Necessary | |\n",
     "\n",
-    "- **Time to learn**: 50 minutes"
+    ":::{tip icon=false} ⏱️ Time to learn\n",
+    "50 minutes\n",
+    ":::"
    ]
   },
   {
diff --git a/core/datetime.md b/core/datetime.md
@@ -8,3 +8,7 @@ Other time libraries used in the geosciences include:
 - [cftime library](https://unidata.github.io/cftime/) (for dealing with dates and times in non-standard calendars)
 
 The Python packages that are commonly used for timeseries data in the geosciences such as [Pandas](pandas.md) and [Xarray](xarray.md) leverage these libraries.
+
+:::{note icon=false} ⏱️ Time to learn (cumulative)
+40 minutes
+:::
diff --git a/core/datetime/datetime.ipynb b/core/datetime/datetime.ipynb
@@ -48,7 +48,9 @@
     "| [Python Quickstart](../../foundations/quickstart) | Necessary | Understanding strings |\n",
     "| Basic Python string formatting | Helpful | Try this [Real Python string formatting tutorial](https://realpython.com/python-string-formatting/) |\n",
     "\n",
-    "- **Time to learn**: 30 minutes"
+    ":::{tip icon=false} ⏱️ Time to learn\n",
+    "30 minutes\n",
+    ":::"
    ]
   },
   {
diff --git a/core/matplotlib.md b/core/matplotlib.md
@@ -27,3 +27,7 @@ Currently, Pythia Foundations provides a basic introduction to Matplotlib, as we
 - [Colormaps](#colormap-overview)
 - [Contour plots](#contour-and-filled-contour-plots)
 - [Customizing layouts](#mosaic-subplots)
+
+:::{note icon=false} ⏱️ Time to learn (cumulative)
+2 hours
+:::
diff --git a/core/matplotlib/annotations-colorbars-layouts.ipynb b/core/matplotlib/annotations-colorbars-layouts.ipynb
@@ -36,7 +36,9 @@
     "| [NumPy Basics](../numpy/numpy-basics) | Necessary | {cite:t}`harris2020array` |\n",
     "| [Matplotlib Basics](matplotlib-basics) | Necessary | {cite:t}`Hunter:2007` |\n",
     "\n",
-    "- **Time to learn**: *30-40 minutes*"
+    ":::{tip icon=false} ⏱️ Time to learn\n",
+    "30-40 minutes\n",
+    ":::"
    ]
   },
   {
diff --git a/core/matplotlib/histograms-piecharts-animation.ipynb b/core/matplotlib/histograms-piecharts-animation.ipynb
@@ -36,7 +36,9 @@
     "| [NumPy Basics](../numpy/numpy-basics) | Necessary | {cite:t}`harris2020array` |\n",
     "| [Matplotlib Basics](matplotlib-basics) | Necessary | {cite:t}`Hunter:2007` |\n",
     "\n",
-    "* **Time to Learn**: 30 minutes"
+    ":::{tip icon=false} ⏱️ Time to learn\n",
+    "30 minutes\n",
+    ":::"
    ]
   },
   {
diff --git a/core/matplotlib/matplotlib-basics.ipynb b/core/matplotlib/matplotlib-basics.ipynb
@@ -41,7 +41,9 @@
     "| [NumPy Basics](../numpy/numpy-basics) | Necessary | {cite:t}`harris2020array` |\n",
     "| MATLAB plotting experience | Helpful | |\n",
     "\n",
-    "* **Time to Learn**: 30 minutes"
+    ":::{tip icon=false} ⏱️ Time to learn\n",
+    "30 minutes\n",
+    ":::"
    ]
   },
   {
diff --git a/core/numpy.md b/core/numpy.md
@@ -20,3 +20,7 @@ In [NumPy Basics](./numpy/numpy-basics), you will get an introduction to NumPy a
 [Intermediate NumPy](./numpy/intermediate-numpy) covers additional concepts related to indexing and slicing multidimensional arrays,
 and [NumPy Broadcasting](./numpy/numpy-broadcasting) introduces the way NumPy treats arithmetic on arrays of different
 shapes, which can help make your code more efficient by avoiding loops.
+
+:::{note icon=false} ⏱️ Time to learn (cumulative)
+1 hour 30 minutes
+:::
diff --git a/core/numpy/intermediate-numpy.ipynb b/core/numpy/intermediate-numpy.ipynb
@@ -6,7 +6,10 @@
    "source": [
     "# Intermediate NumPy\n",
     "\n",
-    "```{image} https://github.com/numpy/numpy/raw/main/branding/logo/primary/numpylogo.svg\n:alt: NumPy Logo\n:width: 250\n```\n",
+    "```{image} https://github.com/numpy/numpy/raw/main/branding/logo/primary/numpylogo.svg\n",
+    ":alt: NumPy Logo\n",
+    ":width: 250\n",
+    "```\n",
     "\n",
     "---"
    ]
@@ -31,7 +34,10 @@
     "| ------------------------------- | ---------- | ------------------------- |\n",
     "| [NumPy Basics](numpy-basics)    | Necessary  | {cite:t}`harris2020array` |\n",
     "\n",
-    "* **Time to learn**: 20 minutes\n",
+    ":::{tip icon=false} ⏱️ Time to learn\n",
+    "20 minutes\n",
+    ":::\n",
+    "\n",
     "---"
    ]
   },
diff --git a/core/numpy/numpy-basics.ipynb b/core/numpy/numpy-basics.ipynb
@@ -6,7 +6,10 @@
    "source": [
     "# NumPy Basics\n",
     "\n",
-    "```{image} https://github.com/numpy/numpy/raw/main/branding/logo/primary/numpylogo.svg\n:alt: NumPy Logo\n:width: 250\n```\n",
+    "```{image} https://github.com/numpy/numpy/raw/main/branding/logo/primary/numpylogo.svg\n",
+    ":alt: NumPy Logo\n",
+    ":width: 250\n",
+    "```\n",
     "\n",
     "---"
    ]
@@ -39,7 +42,10 @@
     "| --- | --- | --- |\n",
     "| [Python Quickstart](../../foundations/quickstart) | Necessary | Lists, indexing, slicing, math |\n",
     "\n",
-    "* **Time to learn**: 35 minutes\n",
+    ":::{tip icon=false} ⏱️ Time to learn\n",
+    "35 minutes\n",
+    ":::\n",
+    "\n",
     "---"
    ]
   },
diff --git a/core/numpy/numpy-broadcasting.ipynb b/core/numpy/numpy-broadcasting.ipynb
@@ -6,7 +6,10 @@
    "source": [
     "# NumPy Broadcasting\n",
     "\n",
-    "```{image} https://github.com/numpy/numpy/raw/main/branding/logo/primary/numpylogo.svg\n:alt: NumPy Logo\n:width: 250\n```\n",
+    "```{image} https://github.com/numpy/numpy/raw/main/branding/logo/primary/numpylogo.svg\n",
+    ":alt: NumPy Logo\n",
+    ":width: 250\n",
+    "```\n",
     "---"
    ]
   },
@@ -33,7 +36,10 @@
     "| [Intermediate NumPy](intermediate-numpy) | Helpful | |\n",
     "| [Conceptual guide to broadcasting](https://numpy.org/doc/stable/user/theory.broadcasting.html#array-broadcasting-in-numpy) | Helpful | |\n",
     "\n",
-    "* **Time to learn**: 30 minutes\n",
+    ":::{tip icon=false} ⏱️ Time to learn\n",
+    "30 minutes\n",
+    ":::\n",
+    "\n",
     "---"
    ]
   },
diff --git a/core/overview.md b/core/overview.md
@@ -6,6 +6,14 @@ You've made it to the **Core Packages** section of the book!
 
 As you might know by now that Python is a programming language. To make your job easier, developers of this programming language provide users like you with libraries (or packages). Core libraries will help you with fundamental numerical functions, and high-level libraries will help you efficiently analyze and visualize your data. Some of these libraries are used all across the Python community, while others are domain-specific. Read below to learn more about core and high-level libraries, and domain-specific libraries of the geoscience community. We suggest that new users start with the [Foundational Skills](../foundations/overview) section in order to get the most out of the tutorials below.
 
+:::{tip icon=false} ⏱️ Time to learn (this page)
+20 minutes
+:::
+
+:::{note icon=false} ⏱️ Time to learn (cumulative)
+11 hours
+:::
+
 ## Core libraries
 
 Most geoscience data analysis involves working with numerical arrays.
diff --git a/core/pandas.md b/core/pandas.md
@@ -10,3 +10,7 @@ From the [official documentation](https://pandas.pydata.org/), Pandas {cite:p}`r
 Pandas is a very powerful library for working with tabular data (e.g., spreadsheets, comma-separated-value files, or database printouts; all of these are quite common for geoscientific data). It allows us to use labels for our data; this, in turn, allows us to write expressive and robust code to manipulate the data.
 
 Key features of Pandas are the abilities to read in tabular data and to slice and dice data, as well as exploratory analysis tools native to the library.
+
+:::{note icon=false} ⏱️ Time to learn (cumulative)
+1 hour
+:::
diff --git a/core/pandas/pandas.ipynb b/core/pandas/pandas.ipynb
@@ -7,7 +7,10 @@
    "source": [
     "# Introduction to Pandas\n",
     "\n",
-    "```{image} https://github.com/pandas-dev/pandas/raw/main/web/pandas/static/img/pandas.svg\n:alt: pandas Logo\n:width: 800px\n```\n",
+    "```{image} https://github.com/pandas-dev/pandas/raw/main/web/pandas/static/img/pandas.svg\n",
+    ":alt: pandas Logo\n",
+    ":width: 800px\n",
+    "```\n",
     "\n",
     "---"
    ]
@@ -29,7 +32,9 @@
     "| [Python Quickstart](../../foundations/quickstart) | Necessary | Intro to `dict` |\n",
     "| [Numpy Basics](../numpy/numpy-basics) | Necessary | {cite:t}`harris2020array` |\n",
     "\n",
-    "* **Time to learn**: 60 minutes"
+    ":::{tip icon=false} ⏱️ Time to learn\n",
+    "60 minutes\n",
+    ":::"
    ]
   },
   {
diff --git a/core/xarray.md b/core/xarray.md
@@ -16,4 +16,8 @@ From the [Xarray website][xarray home]:
 
 You should have a basic familiarity with [Numpy arrays](numpy.md) prior to working through the Xarray notebooks presented here.
 
+:::{note icon=false} ⏱️ Time to learn (cumulative)
+3 hours
+:::
+
 [xarray home]: http://xarray.pydata.org/en/stable/
diff --git a/core/xarray/computation-masking.ipynb b/core/xarray/computation-masking.ipynb
@@ -52,7 +52,9 @@
     "| [Introduction to Xarray](xarray-intro) | Necessary | {cite:t}`hoyer2017xarray` |\n",
     "\n",
     "\n",
-    "- **Time to learn**: 60 minutes"
+    ":::{tip icon=false} ⏱️ Time to learn\n",
+    "60 minutes\n",
+    ":::"
    ]
   },
   {
@@ -281,7 +283,8 @@
     "\n",
     "While we can obtain useful summaries of datasets using simple aggregation methods, it is more often the case that aggregation must be performed over coordinate labels or groups. In order to perform this type of aggregation, it is helpful to use the **split-apply-combine** workflow. Fortunately, Xarray provides this functionality for `DataArrays` and `Datasets` by means of the `groupby` operation. The following figure illustrates the split-apply-combine workflow in detail:\n",
     "\n",
-    "```{image} ./images/xarray-split-apply-combine.jpeg\n```\n",
+    "```{image} ./images/xarray-split-apply-combine.jpeg\n",
+    "```\n",
     "\n",
     "Based on the above figure, you can understand the split-apply-combine process performed by `groupby`. In detail, the steps of this process are:\n",
     "\n",
diff --git a/core/xarray/dask-arrays-xarray.ipynb b/core/xarray/dask-arrays-xarray.ipynb
@@ -7,7 +7,10 @@
    "source": [
     "# Dask Arrays with Xarray\n",
     "\n",
-    "```{image} images/dask_horizontal.svg\n:width: 30%\n:align: left\n```\n",
+    "```{image} images/dask_horizontal.svg\n",
+    ":width: 30%\n",
+    ":align: left\n",
+    "```\n",
     "\n",
     "\n",
     "The scientific Python package known as Dask [@https://doi.org/10.25080/Majora-7b98e3ed-013] provides Dask Arrays: parallel, larger-than-memory, n-dimensional arrays that make use of blocked algorithms. They are analogous to Numpy arrays, but are distributed. These terms are defined below:\n",
@@ -36,7 +39,9 @@
     "| [Introduction to Xarray](xarray-intro) | Necessary | Familiarity with Xarray Data Structures |\n",
     "\n",
     "\n",
-    "- **Time to learn**: *30-40 minutes*\n"
+    ":::{tip icon=false} ⏱️ Time to learn\n",
+    "30-40 minutes\n",
+    ":::"
    ]
   },
   {
diff --git a/core/xarray/enso-xarray.ipynb b/core/xarray/enso-xarray.ipynb
@@ -44,9 +44,9 @@
     "| [Introduction to Xarray](xarray-intro) | Necessary | {cite:t}`hoyer2017xarray` |\n",
     "| [Computation and Masking](computation-masking) | Necessary | |\n",
     "\n",
-    "\n",
-    "\n",
-    "- **Time to learn**: 20 minutes"
+    ":::{tip icon=false} ⏱️ Time to learn\n",
+    "20 minutes\n",
+    ":::"
    ]
   },
   {
diff --git a/core/xarray/xarray-intro.ipynb b/core/xarray/xarray-intro.ipynb
@@ -50,7 +50,9 @@
     "| [Datetime](../datetime/datetime) | Helpful | Familiarity with time formats and the `timedelta` object |\n",
     "| [Understanding of NetCDF](../data-formats/netcdf-cf) | Helpful | Familiarity with metadata structure |\n",
     "\n",
-    "- **Time to learn**: 40 minutes"
+    ":::{tip icon=false} ⏱️ Time to learn\n",
+    "40 minutes\n",
+    ":::"
    ]
   },
   {
diff --git a/foundations/getting-started-github.md b/foundations/getting-started-github.md
@@ -22,3 +22,7 @@ We cover the following topics:
 - [Reviewing pull requests](github/review-pr) on GitHub
 - [Git workflows](github/git-workflows), recommended practices for collaborative work
 - [Contributing](github/contribute-to-pythia) to Project Pythia via GitHub
+
+:::{note icon=false} ⏱️ Time to learn (cumulative)
+6 hours
+:::
diff --git a/foundations/getting-started-jupyter.md b/foundations/getting-started-jupyter.md
@@ -13,3 +13,7 @@ Project Jupyter [@https://doi.org/10.1109/MCSE.2021.3059263] is a project and co
 Jupyter lets us create expressive, interactive computational narratives, and execute them on a wide variety of computing platforms from a local laptop to a remote supercomputer.
 
 In this section, we will first go over the key [components of the Jupyter ecosystem](jupyter-components.md) and discuss local vs. remote execution. Next we will give an [overview of JupyterLab](jupyterlab.ipynb), which is our recommended software environment for scientific analysis and visualization. Then we take a deeper dive into creating and running [Jupyter notebooks](jupyterlab-notebooks.ipynb) with Python code in JupyterLab. Finally we give some references for working with [Markdown](markdown.md) to create expressive formatted text in notebooks.
+
+:::{note icon=false} ⏱️ Time to learn (cumulative)
+1 hour 30 minutes
+:::
diff --git a/foundations/getting-started-python.md b/foundations/getting-started-python.md
@@ -2,6 +2,10 @@
 
 **_New Python users, start here!_**
 
+:::{note icon=false} ⏱️ Time to learn (cumulative)
+2 hours
+:::
+
 ## Topics
 
 - [Quickstart: Zero to Python](quickstart): For the impatient among us: run your first Python code in the cloud!
diff --git a/foundations/github/basic-git.md b/foundations/github/basic-git.md
@@ -22,7 +22,9 @@
 | [Cloning and forking a repository](github-cloning-forking.md) | Recommended |                              |
 | [Configuring your GitHub account](github-setup-advanced.md)   | Recommended |                              |
 
-- **Time to learn**: 45 minutes
+:::{tip icon=false} ⏱️ Time to learn
+45 minutes
+:::
 
 ---
 
diff --git a/foundations/github/contribute-to-pythia.md b/foundations/github/contribute-to-pythia.md
@@ -25,7 +25,9 @@
 | [Reviewing pull requests](review-pr.md)                        | Recommended |       |
 | [Git workflows](git-workflows.md)                              | Necessary   |       |
 
-- **Time to learn**: 30 minutes
+:::{tip icon=false} ⏱️ Time to learn
+30 minutes
+:::
 
 ---
 
diff --git a/foundations/github/git-branches.md b/foundations/github/git-branches.md
@@ -29,7 +29,9 @@ Git "branches" are an important component of many Git and GitHub workflows. If y
 | [Configuring your GitHub account](github-setup-advanced.md)   | Recommended |                              |
 | [Basic version control with Git](basic-git.md)                | Necessary   |                              |
 
-- **Time to learn**: 30 minutes
+:::{tip icon=false} ⏱️ Time to learn
+30 minutes
+:::
 
 ---
 
diff --git a/foundations/github/git-workflows.md b/foundations/github/git-workflows.md
@@ -26,7 +26,9 @@ A workflow is a series of activities or tasks that must be completed sequentiall
 | [Pull requests](github-pull-request.md)          | Necessary   |       |
 | [Reviewing pull requests](review-pr.md)          | Recommended |       |
 
-- **Time to learn**: 60 minutes
+:::{tip icon=false} ⏱️ Time to learn
+60 minutes
+:::
 
 ---
 
diff --git a/foundations/github/github-advanced.md b/foundations/github/github-advanced.md
diff --git a/foundations/github/github-cloning-forking.md b/foundations/github/github-cloning-forking.md
diff --git a/foundations/github/github-issues.md b/foundations/github/github-issues.md
diff --git a/foundations/github/github-pull-request.md b/foundations/github/github-pull-request.md
diff --git a/foundations/github/github-repos.md b/foundations/github/github-repos.md
diff --git a/foundations/github/github-setup-advanced.md b/foundations/github/github-setup-advanced.md
diff --git a/foundations/github/review-pr.md b/foundations/github/review-pr.md
diff --git a/foundations/github/what-is-github.md b/foundations/github/what-is-github.md
diff --git a/foundations/overview.md b/foundations/overview.md
diff --git a/foundations/quickstart.ipynb b/foundations/quickstart.ipynb
diff --git a/foundations/why-python.md b/foundations/why-python.md
diff --git a/preamble/how-to-use.md b/preamble/how-to-use.md

Original file line number	Diff line number	Diff line change
`@@ -8,7 +8,9 @@`
`8`	`8`	`"source": [`
`9`	`9`	`"# Introduction to Cartopy\n",`
`10`	`10`	`"\n",`
`11`		- "```{image} ../../images/cartopy_logo.png\n:width: 600\n```"
	`11`	+ "```{image} ../../images/cartopy_logo.png\n",
	`12`	`+ ":width: 600\n",`
	`13`	+ "```"
`12`	`14`	`]`
`13`	`15`	`},`
`14`	`16`	`{`
`@@ -45,7 +47,9 @@`
`45`	`47`	`"\| ------------------------------ \| ---------- \| --------------------- \|\n",`
`46`	`48`	"\| [Matplotlib](../matplotlib.md) \| Necessary \| {cite:t}`Hunter:2007` \|\n",
`47`	`49`	`"\n",`
`48`		`- "- Time to learn: 30 minutes"`
	`50`	`+ ":::{tip icon=false} ⏱️ Time to learn\n",`
	`51`	`+ "30 minutes\n",`
	`52`	`+ ":::"`
`49`	`53`	`]`
`50`	`54`	`},`
`51`	`55`	`{`
Original file line number	Diff line number	Diff line change
`@@ -35,7 +35,9 @@`
`35`	`35`	`"\| [Numpy Basics](../numpy/numpy-basics) \| Necessary \| \|\n",`
`36`	`36`	`"\| [Datetime](../datetime.md) \| Necessary \| \|\n",`
`37`	`37`	`"\n",`
`38`		`- "- Time to learn: 50 minutes"`
	`38`	`+ ":::{tip icon=false} ⏱️ Time to learn\n",`
	`39`	`+ "50 minutes\n",`
	`40`	`+ ":::"`
`39`	`41`	`]`
`40`	`42`	`},`
`41`	`43`	`{`
Original file line number	Diff line number	Diff line change
`@@ -48,7 +48,9 @@`
`48`	`48`	`"\| [Python Quickstart](../../foundations/quickstart) \| Necessary \| Understanding strings \|\n",`
`49`	`49`	`"\| Basic Python string formatting \| Helpful \| Try this [Real Python string formatting tutorial](https://realpython.com/python-string-formatting/) \|\n",`
`50`	`50`	`"\n",`
`51`		`- "- Time to learn: 30 minutes"`
	`51`	`+ ":::{tip icon=false} ⏱️ Time to learn\n",`
	`52`	`+ "30 minutes\n",`
	`53`	`+ ":::"`
`52`	`54`	`]`
`53`	`55`	`},`
`54`	`56`	`{`
Original file line number	Diff line number	Diff line change
`@@ -36,7 +36,9 @@`
`36`	`36`	"\| [NumPy Basics](../numpy/numpy-basics) \| Necessary \| {cite:t}`harris2020array` \|\n",
`37`	`37`	"\| [Matplotlib Basics](matplotlib-basics) \| Necessary \| {cite:t}`Hunter:2007` \|\n",
`38`	`38`	`"\n",`
`39`		`- "- Time to learn: 30-40 minutes"`
	`39`	`+ ":::{tip icon=false} ⏱️ Time to learn\n",`
	`40`	`+ "30-40 minutes\n",`
	`41`	`+ ":::"`
`40`	`42`	`]`
`41`	`43`	`},`
`42`	`44`	`{`