Jupyter Notebook Tips and Tricks
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!
Assuming you are on a Mac
Install Miniconda (if you haven't already)
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 and accept the defaults source ~/.bashrc conda update conda
Create a new conda environments
The following commands are how I set up both my conda config and the enviroments that I use.
Add conda-forge to your automatic channels, and the second line makes it so that you don't have to confirm that you want to install when you do things like
conda install numpy.
conda config --add channels conda-forge conda config --set always_yes yes
This following block is bash -- I recommend pasting in the commands one at a time to see what's happening.
# set the environment name here envname='dspy3' packages=' altair anaconda-client black bqplot ipyvolume ipywebrtc ipywidgets jupyter jupyter_contrib_nbextensions jupyterlab matplotlib mkl mpld3 notebook numpy pandas pip pivottablejs pyparsing qgrid scikit-learn scipy seaborn statsmodels vaex vega vega_datasets yapf ' conda create -n $envname python=3 $packages source activate $envname # Pause here, double check that this pip is the correct one which pip # the correct one will say something like... # $ which pip # /Users/username/miniconda3/envs/dspy3/bin/pip python -m pip install pyhive[presto] sql_magic SQLAlchemy nbdime papermill # lets the notebook extension (like ToC2) be enabled. # Might not be needed! # jupyter nbextension enable --py --sys-prefix widgetsnbextension # This sets the name of the kernel that you want to select from the Kernel menu python -m ipykernel install --user --name $envname --display-name "$envname"
If you see an error message that says something about the iopub_data_rate_limit when you're trying to plot, try starting the notebook/lab with the following modified commands:
# Run to get a notebook jupyter notebook --NotebookApp.iopub_data_rate_limit=10000000 # Run to get lab jupyter lab --NotebookApp.iopub_data_rate_limit=10000000
# jupyter labextension install bqplot