Update for week of 12/12 - 12/16

Planning.md

@@ -34,6 +34,7 @@ I will give myself the whole 2016-Q4 to work on this goal. It seems like a long
 * **Week of 11/21 - 11/25**: (Thanksgiving - Half week) On the Job learning for scikit-learn (pipeline, learning curve) + BIDS matplotlib review + Data School: writing pythonic code + Test Driven Development for Scientist blog post
 * **Week of 11/28 - 12/2**: BIDS Ipython notebook, BIDS functions/modules, BIDS: advanced string, BIDS testing driven development, Jeff Knupp's Unit Testing, Software Carpentry on Testing with Python
 * **Week of 12/5 - 12/9**: BIDS Numpy, BIDS Advanced Interaction, Simeon Franklin's higher order function, Jeff Knupp's "improve your python series": yield/generator, decorator, drastically improve python understanding of execution code, loop like a native (really good)
+* **Week of 12/12 - 12/16**: During the weekend (12/9), add more newer topics (logging, command-line tool, and building packages) for 2017. No active learning for this week, but wrap up by reviewing materials for a blog post
 
 [Software Development Skills For Data Scientists]: http://treycausey.com/software_dev_skills.html
 [Pandas Plotting Documentation]:http://pandas.pydata.org/pandas-docs/version/0.18.1/visualization.html

README.md

@@ -13,6 +13,8 @@ By now, I have a pretty good working knowledge of the R language. There are obvi
 
 To me, the appeal of Python is not necessarily the Data Analysis part, R is already doing a great job on this. Rather, the appeal of using Python for data work is that you have a higher chance to see how data plays a role within the whole integrated technology stack. Knowing Python is likely to make me a better **end-to-end** Data Scientist and better Software Engineer.
 
+Here is a great [reddit answer] that explains the intersection and disjoint union of the two languages beautifully.
+
 ## Deliberate Practice
 
 I am a huge believer in learning by doing, and there are a lot of opportunities on the job where I can hone my Python skills through Deliberate Practice:
@@ -166,6 +168,7 @@ Once mastered all the above, the next natural step is to create public work that
 [Teach Yourself Programming in 10 years]:http://norvig.com/21-days.html
 [Plateau of Productivity]:http://pbpython.com/plateau-of-productivity.html
 
+[reddit answer]:https://www.reddit.com/r/Python/comments/2tkkxd/considering_putting_my_efforts_into_python/
 [Language war]:http://www.dataschool.io/python-or-r-for-data-science/
 [advanced R materials]:http://adv-r.had.co.nz/
 [basic web applications in Flask]:https://github.com/robert8138/flask-google-calendar-api-project