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Python visualization tutorial
Jupyter Notebook
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01_GettingStarted.ipynb
02_DataManipulation.ipynb
02_DataManipulation_solution.ipynb
03_Plotting.ipynb
03_Plotting_solution.ipynb
04_Altair.ipynb
05_Plotly.ipynb
06_MachineLearning.ipynb
06_MachineLearning_solution.ipynb
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README.md
requirements.txt

README.md

Usage

MyBinder

Go to: https://mybinder.org/v2/gh/JKU-ICG/python-visualization-tutorial/master Binder

MyBinder installs the dependencies specified inside of the requirements.txt for you.

Locally

Setup

In this example, we use Anaconda and Python 3.

Install Anaconda

Download the 3.7 version of Anaconda from: https://www.anaconda.com/download

Anaconda is a package distribution that contains the Conda package manager, but also a bunch of other frequently used packages, e.g.:

  • ipywidgets
  • jupyter and jupyterlab
  • matplotlib
  • numpy
  • pandas
  • scipy
  • seaborn

But: not plotly, we will install it later.

Conda Environments
Best practice is to create an environment per project.
Some commands to manage environments from: https://conda.io/docs/user-guide/tasks/manage-environments.html

conda create --name test_env python                 ... create a python environment named test_env
conda create --name jupyter_env jupyter python   ... create a python environment named jupyter_env with package jupyter

conda activate test_env                             ... activate environment test_env
conda env list                                      ... list all environments
conda list                                          ... list all packages available in environment (!= packages shipped with anaconda)
conda install numpy                                 ... install an additional package
conda install --yes --file requirements.txt         ... install packages listed in a requirements file
conda deactivate                                    ... leave conda enviroment
conda env remove --name test_env                    ... remove an environment from disk

Start

Checkout this repo and change into the folder:

git clone https://github.com/JKU-ICG/python-visualization-tutorial.git
cd python-tutorial-VA2018/

Create a new environemnt and install the packages needed in the tutorial:

conda create --name python-tutorial python
conda activate python-tutorial
conda install -c conda-forge  --yes --file requirements.txt 

Launch Jupyter :

jupyter notebook

Jupyter should open a new tab with url http://localhost:8888/ and display the tutorial files.

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