Published: Feb. 28, 2019

When I first got into bioinformatics one of the things I needed to learn quickly was how to graph with very large tabels of data. Below are some of my favorite websites for learning how to graph big data.

 

A great webstie with instructions on using R

https://datacarpentry.org/R-ecology-lesson/index.html (Links to an external site.)

Some great websties with instructions on using python for big data and graphing.SomeLinks to an external site.

Use this to learn the python package pandas (like excel for big data).

https://nikgrozev.com/2015/12/27/pandas-in-jupyter-quickstart-and-useful-snippets/ (Links to an external site.)Links to an external site.

Fancier plotting can be achieved with plotly or bokah 

https://plot.ly/pandas/ (Links to an external site.)Links to an external site.

https://bokeh.pydata.org/en/latest/ (Links to an external site.)Links to an external site.

 

Specific to those in BioFrontiers on the compute cluster Fiji:

To use Rstudio on fiji, use a web browser to go to  fiji-viz.colorado.edu and click on Rstudio. 

 

Setting up a FANCY jupyter notebook on fiji.

Step 0:

Log into Fiji on the command line and do this:

http://bficores.colorado.edu/biofrontiers-it/cluster-computing/fiji/jupyterhub

Step1:

also run these line on the command line 

pip3 install hide_code
pip3 install plotly
pip3 install ipywidgets
pip3 install jupyter_contrib_nbextensions
pip3 install jupyter_nbextensions_configurator
jupyter contrib nbextension install --user

jupyter nbextension install --user --py widgetsnbextension

jupyter nbextension enable --user --py widgetsnbextension

Then log off the fiji on the command line!

Step 2:

Start a new server on fiji-viz.colorado.edu

Step 3:

Start a new notebook

step 4: use the control panel button to log off the server

step 5: restart the server, on the home page you will have a new tab called Nbextentions, click that and turn on extensions you want

step 6: Start a new notebook with the "New" button. Name it by clicking on the name. 

BTW, if you want to do the R lesson in the jupyter notebook instead the starting file is here.

#df=pandas.read_csv("https://raw.githubusercontent.com/kbroman/kbroman.github.io/master/datac...")