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README.md

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## Getting started
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The course uses Python 3 and some data analysis packages such as Pandas, Numpy and Matplotlib. To install the required libraries, we highly recommend Anaconda or miniconda (<https://www.anaconda.com/download/>) or another Python distribution that includes the scientific libraries (this recommendation applies to all platforms, so for both Window, Linux and Mac).
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The course uses Python 3 and some data analysis packages such as Pandas, Numpy and Matplotlib. To install the required libraries, we highly recommend using conda (https://conda-forge.org/download/), which allows you to install the required scientific libraries (this recommendation applies to all platforms, so for both Windows, Linux and Mac).
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For detailed instructions to get started on your local machine , see the [setup instructions](./docs/setup.md).
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docs/_config.yml

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title: Data manipulation, analysis and visualisation in Python
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logo:
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description: Specialist course Doctoral schools of Ghent University
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description: Transferable Skills course - Doctoral School of Ghent University
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show_downloads: true
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theme: jekyll-theme-minimal

docs/contributing.md

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### Ask a question ⁉️
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Trying out the material and got stuck? Post your question as an [issue on GitHub](https://github.com/jorisvandenbossche/course-python-data/issues). While we cannot offer user support, we'll try to do our best to address it, as questions often lead to the discovery of bugs.
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Trying out the material and got stuck? Post your question as an [issue on GitHub](https://github.com/plovercode/course-python-data/issues). While we cannot offer user support, we'll try to do our best to address it, as questions often lead to the discovery of bugs.
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Want to ask a question in private? Contact the course maintainer by [email](jorisvandenbossche@gmail.com).
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### Propose an idea 💡
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Have an idea for to improve the course? Take a look at the [issue list](https://github.com/jorisvandenbossche/course-python-data/issues) to see if it isn't included or suggested yet. If not, suggest your idea as an [issue on GitHub](https://github.com/jorisvandenbossche/course-python-data/issues/new).
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Have an idea to improve the course? Take a look at the [issue list](https://github.com/plovercode/course-python-data/issues) to see if it isn't included or suggested yet. If not, suggest your idea as an [issue on GitHub](https://github.com/plovercode/course-python-data/issues/new).
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### Report a bug 🐛
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Using the course and discovered a bug or a typo? That's annoying! Don't let others have the same experience and report it as an [issue on GitHub](https://github.com/jorisvandenbossche/Have an idea for to improve the course? Take a look at the [issue list](https://github.com/jorisvandenbossche/course-python-data/issues) to see if it isn't included or suggested yet. If not, suggest your idea as an [issue on GitHub](https://github.com/jorisvandenbossche/course-python-data/issues/new).
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/issues/new) so we can fix it. A good bug report makes it easier for us to do so, so please include:
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Using the course and discovered a bug or a typo? That's annoying! Don't let others have the same experience and report it as an [issue on GitHub](https://github.com/plovercode/course-python-data/issues/new) so we can fix it. A good bug report makes it easier for us to do so, so please include:
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* Your operating system name and version (e.g. Mac OS 10.13.6).
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* Any details about your local setup that might be helpful in troubleshooting.
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Some notes to take into account:
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- The course material is developed in the [course-python-data](https://github.com/jorisvandenbossche/course-python-data) repository. When updating course material, edit the notebooks in the [course-python-data](https://github.com/jorisvandenbossche/course-python-data) repository, the other ones (the ones used in the tutorial) are generated automatically.
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- The course material is developed in the [course-python-data](https://github.com/plovercode/course-python-data) repository. When updating course material, edit the notebooks in the [course-python-data](https://github.com/plovercode/course-python-data) repository, the other ones (the ones used in the tutorial) are generated automatically.
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- the exercises are cleared using the `nbtutor` notebook extension: <https://github.com/jorisvandenbossche/nbtutor>
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docs/index.md

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tackle commonly encountered data handling tasks in order to increase the overall efficiency. These skills are both useful for data cleaning as well as
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feature engineering.
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The course has been developed as a course for the Specialist course Doctoral schools of Ghent University, but can be taught to others upon request.
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The course has been developed as a course for the Transferable Skills course - Doctoral School of Ghent University, but can be taught to others upon request.
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## Course info
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For detailed instructions to get started on your local machine, see the [setup instructions](./setup.html).
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In case you do not want to install everything and just want to try out the course material, use the environment setup by
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Binder [![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/jorisvandenbossche/DS-python-data-analysis/HEAD) and open de notebooks
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Binder [![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/plovercode/DS-python-data-analysis/HEAD) and open de notebooks
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rightaway (inside the `notebooks` directory).
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## Slides
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For the course slides, click [here](https://jorisvandenbossche.github.io/DS-python-data-analysis/slides.html).
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For the course slides, click [here](https://plovercode.github.io/DS-python-data-analysis/slides.html).
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## Contributing
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docs/setup.md

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### Option 1: You are already a git user
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As the course has been set up as a [git](https://git-scm.com/) repository managed on [Github](https://github.com/jorisvandenbossche/DS-python-data-analysis),
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As the course has been set up as a [git](https://git-scm.com/) repository managed on [Github](https://github.com/plovercode/DS-python-data-analysis),
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you can clone the entire course to your local machine. Use the command line to clone the repository and go into the course folder:
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```
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git clone https://github.com/jorisvandenbossche/DS-python-data-analysis.git
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git clone https://github.com/plovercode/DS-python-data-analysis.git
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cd DS-python-data-analysis
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```
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### Option 2: You are not a git user
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To download the repository to your local machine as a zip-file, click the `download ZIP` on the
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repository page <https://github.com/jorisvandenbossche/DS-python-data-analysis> (green button "Code"):
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repository page <https://github.com/plovercode/DS-python-data-analysis> (green button "Code"):
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![Download button](./static/img/download-button.png)
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As a good practice, we will create a new _conda environment_ to work with.
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The packages used in the course are enlisted in
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an [`environment.yml` file](https://raw.githubusercontent.com/jorisvandenbossche/DS-python-data-analysis/main/environment.yml). The file looks as follows:
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an [`environment.yml` file](https://raw.githubusercontent.com/plovercode/DS-python-data-analysis/main/environment.yml). The file looks as follows:
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```
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name: DS-python
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channels:
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- conda-forge
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dependencies:
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- python=3.12
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- python=3.13
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- geopandas
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- ...
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```

docs/slides.html

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# Data manipulation, analysis and visualisation in Python
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Specialist course Doctoral schools of Ghent University<br>
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27, 30 January and 3 February 2025
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Transferable Skills course - Doctoral School of Ghent University<br>
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19, 22 and 26 January 2026
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Joris Van den Bossche, Stijn Van Hoey
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https://github.com/jorisvandenbossche/DS-python-data-analysis
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https://github.com/plovercode/DS-python-data-analysis
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<img src="./static/img/logo_flanders+richtingmorgen.png" width="79%">
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<img src="./static/img/doctoralschoolsprofiel_hq_rgb_web.png" width="20%">
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# Who are you?
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Go to https://hackmd.io/J3eLIyKRQ_Kc3PRV4DLCwQ?both
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Go to https://hackmd.io/84p71jbvRheG6uz12h9ICg?both
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<iframe src="https://hackmd.io/J3eLIyKRQ_Kc3PRV4DLCwQ?both" height="400px" width="800px"></iframe>
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<iframe src="https://hackmd.io/84p71jbvRheG6uz12h9ICg?both" height="400px" width="800px"></iframe>
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---
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## Setting up a working environment
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For the setup instructions, see the [setup page](https://jorisvandenbossche.github.io/DS-python-data-analysis/setup.html).
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For the setup instructions, see the [setup page](https://plovercode.github.io/DS-python-data-analysis/setup.html).
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class: left, middle
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0. If not already downloaded the course material, installed conda and setup the environment, see [setup instructions section 1 and 2](https://jorisvandenbossche.github.io/DS-python-data-analysis/setup.html)
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1. Next, make sure to complete 3 and 4 of the [setup instructions](https://jorisvandenbossche.github.io/DS-python-data-analysis/setup.html).
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0. If not already downloaded the course material, installed conda and setup the environment, see [setup instructions section 1 and 2](https://plovercode.github.io/DS-python-data-analysis/setup.html)
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1. Next, make sure to complete 3 and 4 of the [setup instructions](https://plovercode.github.io/DS-python-data-analysis/setup.html).
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> If you succesfully done all steps, put up your `green sticky note` on your laptop screen...
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Next:
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- Surf to and fill in [the questionnaire](https://hackmd.io/J3eLIyKRQ_Kc3PRV4DLCwQ?both)
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- Surf to and fill in [the questionnaire](https://hackmd.io/84p71jbvRheG6uz12h9ICg?both)
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- In Jupyter Lab, start with the 'notebooks/00-jupyter_introduction.ipynb'.
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> Installation or setup issues? Put up your `red sticky note` on your laptop screen.
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![:scale 80%](./static/img/issuetracker.png)
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Report bugs, typo's, suggestions... as issues ([New issue](https://github.com/jorisvandenbossche/course-python-data/issues/new))
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Report bugs, typo's, suggestions... as issues ([New issue](https://github.com/plovercode/course-python-data/issues/new))
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or see the [contributing guidelines](https://github.com/jorisvandenbossche/course-python-data/blob/main/CONTRIBUTING.md)
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or see the [contributing guidelines](https://github.com/plovercode/course-python-data/blob/main/CONTRIBUTING.md)
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![:scale 100%](http://esq.h-cdn.co/assets/15/51/980x490/landscape-1450137389-john-cleese.JPG)
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### https://forms.gle/wmFH89ELcRKFYuWFA
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### https://forms.gle/J5i4VfCj8682sDjP7
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environment.yml

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- numpy
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- pandas=2.3
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- mplleaflet
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- ipympl

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