A few (hopefully) useful tips and tricks to using the Jupyter Notebook with an eye to pragmatic usage. This is not, in any way, an exhaustive demonstration of the features of the Jupyter notebook. Further, you can go through these notebooks on your own, but I usually demonstrate using them and give lots of information verbally.
If you have any suggestions, edits, or corrections, please open an issue or let me know some other way. Best of luck!
cd ~/Downloads
wget https://repo.continuum.io/miniconda/Miniconda3-latest-MacOSX-x86_64.sh
bash Miniconda3-latest-MacOSX-x86_64.sh
# go through the licensing
source ~/.bashrcconda update conda
# This adds the conda-forge channel below the defaults library
conda config --append channels conda-forge
packages='jupyter
notebook
ipywidgets
jupyter_contrib_nbextensions
pyparsing
matplotlib
mkl
mpld3
seaborn
pip
pandas
scikit-learn
scipy
numpy
statsmodels
tqdm'
conda create -q --name py2 python=2 $packages
# Only including r in py3 because conda install r and py2 don't work.
# If you need it, force
conda create -q --name py3 --channel r r r-irkernel r-recommended r-essentials rpy2 python=3 $packages -y
source activate py3
# Install the matplotlib style library
# https://github.com/ipython/ipython/issues/8873#issuecomment-146185652
ipython kernel install --display-name py3 --name py3Add this (modify it first) to your .bashrc
export initials='jbw'
minimalnb () {
# Usage: minimalnb [exploratory_data_analysis]
# Will download the most up-to-date minimal notebook named with:
# today's date, your initials, and [an optional phrase].
# The example would yield a file in the current directory named:
# 2016-08-17_jbw_exploratory_data_analysis.ipynb
curl -H 'Accept: application/vnd.github.v3.raw' -L \
https://api.github.com/repos/jbwhit/jupyter-tips-and-tricks/contents/templates/minimal.ipynb \
-o `date +%Y-%m-%d`_${initials}_$1.ipynb
}