https://github.com/LibCrowds/notebooks

Computational analysis of LibCrowds data
https://github.com/LibCrowds/notebooks

Last synced: 2 months ago
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Computational analysis of LibCrowds data

• Host: GitHub
• URL: https://github.com/LibCrowds/notebooks
• Owner: LibCrowds
• License: mit
• Created: 2018-05-24T21:17:24.000Z (over 6 years ago)
• Default Branch: master
• Last Pushed: 2018-07-16T23:48:09.000Z (over 6 years ago)
• Last Synced: 2024-08-03T05:01:40.739Z (6 months ago)
• Language: Jupyter Notebook
• Homepage: https://mybinder.org/v2/gh/libcrowds/notebooks/master?urlpath=lab
• Size: 23 MB
• Stars: 2
• Watchers: 1
• Forks: 1
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

Awesome Lists containing this project

README

        
# LibCrowds Notebooks

> Computational analysis of LibCrowds data.

The Jupyter notebooks contained in this repository explore the data created

via the LibCrowds platform. To work with interactive versions of the notebooks,

visit the following URL:

https://mybinder.org/v2/gh/libcrowds/notebooks/master?urlpath=lab

The notebooks are located in the `/notebooks` folder.

## Contents

1. [An Introduction to the LibCrowds Annotations Data Model](https://nbviewer.jupyter.org/github/LibCrowds/notebooks/blob/master/notebooks/intro_to_the_libcrowds_data_model.ipynb)

2. [An Introduction to Analysing In the Spotlight Data Using Python](https://nbviewer.jupyter.org/github/LibCrowds/notebooks/blob/master/notebooks/intro_to_analysing_its_data_using_python.ipynb)

3. [An Introduction to Visualising In the Spotlight Data Using Python](https://nbviewer.jupyter.org/github/LibCrowds/notebooks/blob/master/notebooks/intro_to_visualising_its_data_using_python.ipynb)

4. [Visualising In the Spotlight Data Over Time](https://nbviewer.jupyter.org/github/LibCrowds/notebooks/blob/master/notebooks/visualising_its_data_over_time.ipynb)

## Build setup

``` bash

# clone with submodules

git clone https://github.com/LibCrowds/notebooks --recursive

# change directory

cd notebooks

# install dependencies

pip install -r requirements.txt

# raise memory limit (on Windows replace "export" with "set")

export NODE_OPTIONS=--max-old-space-size=4096

# install Jupyter extensions

jupyter labextension install @jupyter-widgets/jupyterlab-manager

jupyter labextension install @jupyterlab/plotly-extension

jupyter labextension install plotlywidget

# run

jupyter lab

```