Data + Python @ NYU Stern

THE BLOG: Undergrad Spring 2018

Make an appointment to talk about projects. Here is the link

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Interesting data and what we did March 27th 2018

Here are those two interesting data links that I saw:

Today, we did some more advanced plotting in Matplotlib. Histograms, Bubble/Scatter plots, and explored a lot of the optionality around it. Next class we finish this up by plotting statistics from a data set and how they vary over time. Then we start working on cleaning data.

Code here:

https://github.com/mwaugh0328/data_bootcamp_spring_2018


What we did the past week…Feb12-16 2018

Finished up Python Fundamentals 2. Slicing, if then, for loops, list comprehension, functions. Congrats! Sit back, relax, think about where you started and now where you are! Also talked about strategies to extract the name from the Poe Poem.

Code Practice 2 due today (Feb 16th). Email you Jupyter notebook to nyudatabootcamp At gmail.com


What we did the past week…2018

Totally defaulted on this…last couple of classes we’ve worked through Python Fundamentals 1 (great work) and are now in the middle of Python Fundamentals 2 (up to if/than statements). You should be a position to complete about half of code practice 2. Link to my code is here:

https://github.com/mwaugh0328/data_bootcamp_spring_2018/tree/master/week3

Next week for loops and list comprehension.

Final thought…the FT has a nice piece on data and statistics. In many ways the advice and principals talked about mesh well with the “ethos” of this course| harness data and communicate it in a simple, clear, understandable way. Link is here:

https://www.ft.com/content/ba4c734a-0b96-11e8-839d-41ca06376bf2


What we did today…Jan 30, 2018

  • Talked a little a bit about data today. In particular we looked at this graphic from the Economist magazine Following up on this discussion, please look through data mentality chapter.

  • Talked about how to turn in Code practice 1. Jupyter notebook, print a hard copy and hand it to me. Here is my mini-example of the format.

  • Worked through Python fundamentals 1. Basic calculations, assignments, print. Getting help with ? and the whos command to see what variables are in your enviornment.


What we did today…Jan 25, 2018

Got Anaconda installed! Yes! Opened up Jupyter and talked about its features. Then we briefly did some computation. Next class, we will delve into the details regarding basics of Python in Python fundamentals 1. Feel free to work through this on your own.


What we did today…Jan 23, 2018

We talked…a lot. I told you about the course (big ideas, course website, materials, the syllabus), who I am, and I asked about you!

We also tried to download Anaconda installation of python, but ran out of time. Next class we will get it done and start learning.


January 18, 2018: Welcome to Data Bootcamp…

Welcome to Data Bootcamp!

This is a very exciting course…the world is awash in data and being able to (i) harness, (ii) analyze, and (iii) communicate the analysis in a compelling way are must have skills for today and for the future. Employers are looking for them and you will be a better employee. And I’m looking forward to helping you acquire these skills.

In less than a week we will have our first meeting and get the semester started. I want to reach out to you about some features of this course to help you prepare for the semester ahead.

(1) Read the Syllabus. I’ve posted the syllabus for the upcoming semester at our course website:

https://nyu.data-bootcamp.com/undergrad_outline/

This has information about important dates, texts, grading, etc. Please take some time to go over this prior to our first class meeting.

(2) Make sure you have a laptop computer you can bring to class and install your own programs on. This is a must. We will be writing programs in every class.

(3) Take the online survey. This link below:

https://goo.gl/forms/ITdV9tuEwBrjbB053

has a survey for you to complete. Completing this will partially go towards your participation / professionalism grade.

(4) Explore the website. The website provides a bunch of information about the course, FAQ, data, code, etc.

I’m looking forward to meeting you all and a great semester!

mike