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Expand Up @@ -44,7 +44,7 @@
"- [How Charts Lie](https://www.amazon.com/gp/product/0393358429) (Alberto Cairo).\n",
" Similar to Chapter 7 of Calling Bullshit, but the entire book is devoted to\n",
" visualisations.\n",
"- [The Functional Art](http://www.thefunctionalart.com/p/about-book.html) (Alberto\n",
"- [The Functional Art](https://thefunctionalart.blogspot.com/p/about-book.html) (Alberto\n",
" Cairo) and [Show Me the Numbers](http://www.perceptualedge.com/library.php) (Stephen\n",
" Few). Authoritative References if you want to become a data viz pro. Alberto Cairo has\n",
" an [interesting blog accompanying the book](http://www.thefunctionalart.com/). *Show\n",
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2 changes: 1 addition & 1 deletion src/epp_topics/projects/setup/objectives_materials.ipynb
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Expand Up @@ -27,7 +27,7 @@
"\n",
"Download the [slides](projects-setup.pdf).\n",
"\n",
"Link to the [getting started section of the documentation](https://econ-project-templates.readthedocs.io/en/latest/getting_started/index.html)."
"Link to the [getting started section of the documentation](https://econ-project-templates.readthedocs.io/en/stable/getting-started/)."
]
}
],
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4 changes: 2 additions & 2 deletions src/epp_topics/projects/setup/screencast/script.md
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Expand Up @@ -10,9 +10,9 @@ Give a brief motivation what the templates help to do:

## Where to get help (show docs)

[Customising the template for your needs](https://econ-project-templates.readthedocs.io/en/stable/getting_started/index.html#customising-the-template-for-your-needs)
[Customising the template for your needs](https://econ-project-templates.readthedocs.io/en/stable/customising-the-template/)

## Create a github repo
## Create a github repogetting_started/index.html#customising-the-template-for-your-needs

- Go to https://github.com/OpenSourceEconomics/econ-project-templates
- Click on "Use this template"+
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2 changes: 1 addition & 1 deletion src/epp_topics/projects/setup/screencast/slides.md
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Expand Up @@ -33,4 +33,4 @@ Janoś Gabler and Hans-Martin von Gaudecker

# Getting started

[Getting started page of the documentation](https://econ-project-templates.readthedocs.io/en/stable/getting_started/index.html)
[Getting started page of the documentation](https://econ-project-templates.readthedocs.io/en/stable/getting_started/)
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Expand Up @@ -25,7 +25,7 @@ We will cover the following topics:
## Installing mamba

Go to
[https://github.com/conda-forge/miniforge#download](https://github.com/conda-forge/miniforge#download)
[https://github.com/conda-forge/miniforge?tab=readme-ov-file#unix-like-platforms-macos-linux--wsl](https://github.com/conda-forge/miniforge?tab=readme-ov-file#unix-like-platforms-macos-linux--wsl)
and Download the Linux x86_64 version of the installer in your Downloads folder.

![0_download](0_download.png)
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Expand Up @@ -27,7 +27,7 @@ you have an Intel processor.
## Installing mamba

1. Go to
[https://github.com/conda-forge/miniforge#download](https://github.com/conda-forge/miniforge#download)
[https://github.com/conda-forge/miniforge?tab=readme-ov-file#unix-like-platforms-macos-linux--wsl](https://github.com/conda-forge/miniforge?tab=readme-ov-file#unix-like-platforms-macos-linux--wsl)
and download the **OS X x86_64** version (for Intel processors) or the **OS X arm64**
version (for Apple processors) of the installer in your Downloads folder.

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Expand Up @@ -35,7 +35,7 @@ shells and conda environments.
## Installing mamba

1. Go to
[https://github.com/conda-forge/miniforge#download](https://github.com/conda-forge/miniforge#download)
[https://github.com/conda-forge/miniforge?tab=readme-ov-file#windows](https://github.com/conda-forge/miniforge?tab=readme-ov-file#windows)
and Download the Windows x86_64 version of the installer in your Downloads folder.

![0_download](0_download.png)
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Expand Up @@ -28,7 +28,7 @@
"\n",
"Download the [slides](scientific_computing-randomness.pdf).\n",
"\n",
"- This [Blogpost](https://albertcthomas.github.io/good-practices-random-number-generators/) explains some of the reasons behind our best practices.\n",
"- This [Blogpost](https://blog.scientific-python.org/numpy/numpy-rng/) explains some of the reasons behind our best practices.\n",
"- If you find the \"legacy\" version of the NumPy random number generator somewhere (i.e., calling `np.random.seed`. E.g., LLMs are trained on lots of data using that...), a clear exposition of why you want to use the suggested version can be found [here](https://builtin.com/data-science/numpy-random-seed).\n",
"\n",
"## Quiz\n"
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