Office Hours
Sunday, Tuesday 8;30-9:15 PM (Might change). Office Hour Link
Overview
Big Data is changing how we interact with and understand the environment. Yet analyzing Big Data requires new tools and methods. Students will learn to use Python programming to analyze and visualize large environmental and earth’s systems data sets in ways that Excel is not equipped to do. This will include both time series and spatial analyses with programming occurring interactively during class and assignments designed to strengthen methods and results. Students will learn to write code in Python, plot, map, sub-select, clean, organize, and perform statistical analyses on large global scale data sets, using the data in analysis, and take any data set no matter how large or complicated.
Class Information
Professor: Brian Mailloux, bmaillou@barnard.edu
Syllabus: BigData-Syllabus_2024_spring_v1
The syllabus and assignments might change as we go.
My good friend Mark Bakker does a similar introductory class to us that he calls Exploratory Computing with Python. This class is really the inspiration for me and I took a lot from him. He has some great tutorials and videos and information and I use it all the time.
Useful Links
NYC Pyladies and Pyladies
This is the Python Tutorial (very thick)
This is the google course
This is a nice intro to python class
Growth Mindset
As we are learning something new. Remember that we believe in a growth mindset. Watch the video! And take the Growth Mindset quiz.
The information was very helpful and this was a good project to understand pandas better. It would be helpful to have in the packet how to reset the x tick marks to custom values, such as months of the year.
I think it would be helpful to explain what a nan is when it first pops up in the notes during class. It helped me to understand what nan’s represent and what kinds of errors can produce a nan.
I really liked the reverse classroom set up of this course. Previously, I hadn’t taken a class formatted like that and I though it was a really effective way to learn coding
I love how this class built on the analysis we’ve been learning throughout the semester. The residual plot was powerful and cool to do for the first time. The comments in the class code were very helpful.