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57 changes: 17 additions & 40 deletions content/en/modules/python_visualization/index.md
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Expand Up @@ -5,7 +5,7 @@ type: "modules" # DON'T TOUCH THIS ! :)
title: "Introduction to data visualization in Python"

# Your project GitHub repository URL
github_repo:
github_repo: https://github.com/school-brainhack/module_python_visualization

# If you are working on a project that has website, indicate the full url including "https://" below or leave it empty.
website:
Expand Down Expand Up @@ -36,64 +36,41 @@ If you have any questions regarding the module content please ask them in the re
to the server and would like to join, please send us an email at school [dot] brainhack [at] gmail [dot] com.

## Resources

This module is built around one Jupyter notebook and one set of exercises, all available in the [module repository](https://github.com/school-brainhack/module_python_visualization).

## Original lecture
This module was presented by Jacob Vogel during the QLSC 612 course in 2020, and the associated notebook is available [here](https://github.com/neurodatascience/course-materials-2020/blob/master/lectures/14-may/01-data-visualization/python_visualization_for_data.ipynb). (Note: if you did the BIDS module, the dataset to download is the same - ds000228! A few functions now throw warnings, you can ignore these, or fix them if you like.)

The video of the presentation is available below (1h09):
<iframe width="560" height="315" src="https://www.youtube.com/embed/lJyFWTT7sCY" title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture" allowfullscreen></iframe>

## Tutorial

* Download the jupyter notebook (save raw version from Github), or start a new jupyter notebook
* Watch the video and run the cells in the notebook

## Exercice

For this next part, we will refer to the following [notebook](https://github.com/brainhackorg/school/blob/master/content/en/modules/python_visualization/python_visualization_intro_rmv_answ.ipynb).
## Exercise

For example purposes, we will make use of a phenotypic dataset from the ABIDE II consortium. This amazing international multi-site dataset contains data from individuals diagnosed with Autism Spectrum Disorder (ASD) and healthy controls. We will use a version of the phenotypic [data](http://fcon_1000.projects.nitrc.org/indi/abide/abide_II.html) from a single site (Kennedy Krieger Institute). To download the dataset, click on the link and then 'Kennedy Krieger Institute' on the right-hand side. Then, Downloads -> Phenotypic File. You will need an NITRC account - if you don't have one, you can create one in a few minutes [here](https://www.nitrc.org/account/register.php).
In the exercise notebook (`exercise_visu_en.ipynb`), you will have to create static and interactive visualization to explore the phenotypic and fMRI data from the **ADHD200** dataset available through nilearn.

1. **Read through the notebook running all the cells**
2. **Complete the exercises in the notebook**
The exercise is structured as follows:
1. **Part 1 : Exploring phenotypic data**: you will visualize some clinical and demographic variables of the ADHD200 dataset.
2. **Part 2 : Exploring fMRI data**: you will explore the functional fMRI data from the ADHD200 dataset through visualizations.

**Exercise 1** Create a figure with a single axes and replot the second scatterplot to group by sex instead of dx_group.
**Important**: follow the parameter specifications given in each question exactly — the exercise uses automated grading that compares results to reference values.

Set the figure size to a ratio of 8 (wide) x 5 (height)
Use the colors red and gray
Set the opacity of the points to 0.5
Label the axes
Add a legend

**Exercise 2** Using a pairwise plot, compare the distributions of age, viq, and piq with respect to dx_group.

Set a palette
Set style to ticks
Set context to paper
Suppress the dx_group variable from being on the plot

**Exercise 3** Using a violin plot separate out viq as a function of sex and dx_group.

Different dx_group should be on each half of each violin
The x-axis should reflect the different sex categories.

**Exercise 4** Play around and make an interactive plot using plotly and your project data if you have any.

* Follow up with your local TA(s) to validate you completed the exercises correctly.
* :tada: :tada: :tada: you completed this training module! :tada: :tada: :tada:
Follow up with your local TA(s) to validate you completed the exercises correctly.

## More resources

- Other great resources to get started with plotting in python:
- [dartbrains](https://dartbrains.org/content/Introduction_to_Plotting.html)
- [dartbrains](https://dartbrains.org/Introduction_to_Plotting/)
- [neurohackademy](https://github.com/neurohackademy/visualization-in-python/blob/master/visualization-in-python.ipynb)
- [PythonDataScienceHandbook](https://nbviewer.jupyter.org/github/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/04.00-Introduction-To-Matplotlib.ipynb)
- [matplolib tutorial - rougier](https://github.com/rougier/matplotlib-tutorial)

<iframe width="560" height="315" src="https://www.youtube.com/embed/FwM_6oZo_2g" title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture" allowfullscreen></iframe>

- Interactive plotting
- Interactive plotting:
- [Interactive plots and the spectrum of data visualization](https://www.youtube.com/watch?v=FwM_6oZo_2g&t=1s)
- [Plotly](https://plotly.com/python/)
- [Bokeh](https://docs.bokeh.org/en/latest/index.html)
- [Altair](https://altair-viz.github.io/)

- Gallery
- Gallery:
- [seaborn gallery](https://seaborn.pydata.org/examples/index.html)
- [Python Graph Gallery](https://python-graph-gallery.com/)
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