From Data to Insights

Theory

Suggested Conceptual Reading & Discussion

• Mason, L. (2018). Ideologues without issues: The polarizing consequences of ideological identities. Public Opinion Quarterly, 82(S1), 866-887.

Code: Live Demo & Hands-on Lab

Student Group Live Demo (Group 3)

• Topic: Data Acquisition & Column Inspection (reading ANES data, .shape, .info(), .describe(), column subsetting).
• Review the Live Demo Guidelines & Schedule.

The Data Science Pipeline

Application

Tip

To run Python scripts in VS Code, follow 📘 Running Python Scripts in VS Code.

Working with Data

• Let's open and run 04_data_exploration_columns.py in VS Code:
  • Course Materials
• Practice reading data files with pandas, inspecting dataset structure (.shape, .info(), .columns), calculating summary statistics (.describe()), and selecting columns.

Get Ready for Next Session: Think. Explore. Practice.

Think

• What are the empirical distributions of your key variables? Think about what a histogram or bar chart of your DV and IV should look like, and watch out for non-substantive response categories (e.g., "Don't know" or refused).
• How will you filter your survey sample to ensure your empirical analysis focuses on the relevant target population?
• Suggested Reading: Barber, M., & Pope, J. C. (2019). Does Party Trump Ideology? Disentangling Party and Ideology in America. American Political Science Review, 113(1), 38–54. - An outstanding example of using survey data and clean graphical displays to disentangle competing political identities.

Explore

• Live Demo (Group 4): Filtering Survey Rows & Univariate Charts (boolean masks, .value_counts(), distributions with Altair). Group 4 prepares a 10–15 min demonstration and shares the handout on WhatsApp before class (groups can book a meeting with the instructor to get direction).
• The class should review the course materials (05_data_exploration_rows.py) and the Altair Simple Charts Documentation to follow along and lead the peer discussion.

Practice

• In your group project folder, create an exploratory Python script (exploration.py) to inspect your DV and IV using 04_data_exploration_columns.py.
• Looking Ahead: Milestone 3 - Exploration will be due in Session 6 (Nov 20 at 23:59).