Clint Weathers ClintWeathers

The Main Idea

In theory, this gives me a few things:

The umph of my overbuilt desktop machine minus a few gig of ram and a couple cores
The ability to SSH/VNC/RDP in and just use my chromebook as a cheap thin client when Im out and about.
Experience dealing with the install and usage of Drill, Zeppelin, and some other tools.

So far I've:

	library(dplyr); library(magrittr)

	#To Create The Dataframe of Fake Orders

	set.seed(867.5309)

	onums <- paste("AA", as.integer(runif(20) * 1e8), sep = "")
	prices <- round((runif(20) * 1000), 2)
	orders <- as.data.frame(cbind(onums, prices))

	Most of this is just following the steps here:

	http://sherifsoliman.com/2016/01/11/theming-ipython-jupyter-notebook/

	On a recent Juypter version, open up the custom.css in your favorite editor which should be Sublime Text 3 or Vim and definitely not emacs.

	~/.jupyter/custom/custom.css (on my VM this lives in C:\Users\username\.ipython\profile_default\static\custom -- YMMV)

	Do a search for kernel_busy_icon

	# List unique values in a DataFrame column
	# h/t @makmanalp for the updated syntax!
	df['Column Name'].unique()

	# Convert Series datatype to numeric (will error if column has non-numeric values)
	# h/t @makmanalp
	pd.to_numeric(df['Column Name'])

	# Convert Series datatype to numeric, changing non-numeric values to NaN
	# h/t @makmanalp for the updated syntax!