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pyvis - Python Visualisation Course - c2sm - version 2

Format

The lectures consist of IPython Notebooks.

Audience

Python beginners who should have programming experience in other languages. Most examples and exercises are drawn from the field of Climate Reseach.

Duration

It's envisioned as a two day course.

How to use it

1 Obtain the course material

Clone the git repository:

git clone https://github.com/C2SM/pyvis.git

Alternatively, you can download the zip-archive and unpack.

2 Start jupyter notebook

In the computer room at ETH (HG E 26.1 or D 12)

Click for details
  • log in to Fedora (you may have to reboot the computer)
  • execute the following commands:
# If the terminal prompt shows "bash-4.4" instead of your username then execute
source /etc/bashrc

OR

#Add the following lines to your .bashrc file and restart the terminal
if [ -f /etc/bashrc ]; then
        . /etc/bashrc
fi

# Once you see your username in the terminal prompt then execute the following
conda activate /opt/kunden/chadha/conda/envs/pyvis
# go to the directory of the material
jupyter notebook

At IAC ETH (on linux computers)

Click for details
  • you can use the standard conda environment
  • execute the following commands:
module load conda/2018
source activate iacpy3_2018
# go to the directory of the material
jupyter notebook

See also the Python FAQ on the IAC wiki (restricted access).

On your personal computer

Click for details
source activate pyvis
# go to the directory of the material
jupyter notebook
  • Start jupyter - from Anaconda Navigator (Windows)

    • Open Anaconda Navigator
    • Make sure you are in the Home tab
    • Switch to pyvis environment; select 'pyvis' from the dropdown
    • Launch jupyter notebook
    • Go to the directory of the material

3 Hide Solutions

To hide the solutions a jupyter extension must be active. In the browser, on jupyter main page, click on Nbextensions. Then make sure Hide input has a tick.

4 Select the Course part

  • Part 0: very short introductions to Jupyter Notebooks, numpy, netCDF4, xarray, and pandas
  • Part 1: Introduction to matplotlib
  • Part 2: Some advanced feature of matplotlib and seaborn.
  • Part 3: Plotting georeferenced data with cartopy.
  • Part 4: Advanced exercises with plots contributed by the community.

What's New

Feedback

I would be very happy to hear from you (mail to [email protected]).

Particularly welcome are problem reports, errors, criticism.

License

Copyright (C) 2018 C2SM / Mathias Hauser / Tarun Chadha

This program is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.

This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.

You should have received a copy of the GNU General Public License along with this program. If not, see [http://www.gnu.org/licenses/].

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