Change of Format

As you may have heard, the Governor announced that CUNY and SUNY will be in an instructional recess from March 12 to March 18 and then beginning on the 19th, we'll be online for the rest of the semester. In addition to the Slack channel that I created, I have a Zoom account that I will use to set up virtual meetings. We won't need to have a virtual meeting each week, but it will give us an opportunity to interact with each other as we work through Python coding and your visualization projects.

About This Course

The “data revolution” has transformed the way we understand and interact with the world around us. The availability of large datasets, progress in computer hardware and software, and use of the web to share data and acquire it from numerous sources (including social network services, libraries, city governments, non-profits, etc.) has created many new possibilities in many fields across the social and behavioral sciences. These developments have also led to the emergence of a number practices with regard to data analysis and communication.

End of Semester

All work submitted to me by the end of the day on Friday, 5/22, will be considered on time. Send your work earlier, if you can. I'll hold at least one zoom office hours during exam week if there is interest.

For W 4/29

We'll take one last look at our classification model.


For M 4/27

Here's the Colab notebook:

We'll finish Step II of the classification project, preparing the data, and begin Step III, computing the model.

The project overview is here:

For M 4/20

Here's the Colab notebook:

We'll be looking at Step II of the classification project, preparing the data.

The project overview is here:

Classification Project

Here are the resources for the classification project with the IBM team.

For W 4/15

Assignment 7

1. Read in the NYC traffic data into a DataFrame.

2. Verify that the file was read correctly.

3. Use graphs to explore three of the variables and how they related to the target variable (INJURED).

4. Create one new computed variable to measure some factor that you think might be related to the target.

5. Create a graph for that variable and how it relates to the target. Interpret the results.

Monday, April 6

We'll discuss logistic regression and examine the code for creating and interpreting a model.



Subscribe to Data Analytics and Data Visualization in the Social and Behavioral Sciences RSS