Over Thanksgiving break we were treated to a panoply of cloud types from the mountaintop view of Queen Wilhelmina State Park Lodge. The graphic below was the best of a number of compelling illustrations that helped to sort out types of clouds seen:
I love visualizations like this one, and I can imagine compiling more like this one — a good visualization of the new “tree of life” — as well as a really nice rendering of the periodic table into a things you need to know book/portfolio.
EDIT: I forgot to note that Ethnologue is a great resource for language information.
Last night I needed to compile a folder (directory) of text files into a single file with the file name as a header. This simple
bash script did the work:
% for f in *.txt; do echo "# $f"; cat "$f"; done > ../legends.txt
The hash sign ahead of the filename reveals that I compiled the document as a markdown text. I couldn’t quite figure out how to insert newlines into the script above, so I ended up using some regex to do that: finding instances of the hash tag and inserting a new line before it and then finding instances of .txt and inserting a newline after it. And then, finally, removing the
.txt extension altogether. From there, I converted the document to HTML that I could format more clearly.
As seen here, I entered the script directly at the command line, but it could also, I suppose be saved thus:
#! /usr/bin/env bash for f in *.txt; do echo "# $f"; cat "$f"; done
I’m not sure how to direct the output into a file within a
bash script. I usually just do that at the command line. (I know, I know: I need to learn bash scripting. I’ll get there.)
While I was pretty happy to get both Python 3 and R working in Jupyter notebooks, I had no idea that you could use both in the same notebook. Check out this presentation by Myles Gartland where he explains the power of
%R in Jupyter notebook: Youtube.
Running parallel to Jockers’ attempts to “plot” texts via sentiment analysis, Indico Data Solutions has released a Python package
plotlines as well as a Jupyter notebook of documentation and sample code.
Neither indico nor plotlines turned up in a
port search so my next step was to try
pip. My first attempt revealed that I was still using the Python 2.7 version of
pip, and I needed both to get the version for Python 3.4 but also make sure it was the active version:
sudo port install py34-pip sudo port select -- pip pip34
And, then, to the matter at hand:
sudo pip install -U indicoio
port install py34-jupyter
Note: you may need to prepend
sudo to install software on your setup.
But the new command
jupyter notebook only returned
-bash: jupyter: command not found for me. I tried various alternatives, but got nowhere until I returned to
ipython notebook. Presto. And even better, now I have this:
Getting the R there is considerably simpler now, while in the R shell:
install.packages(c('rzmq','repr','IRkernel','IRdisplay'), repos = c('http://irkernel.github.io/', getOption('repos'))) IRkernel::installspec()
See iRkernel for more information.