Data Analysis with Python

Already know basic Python? Learn to answer real questions with data using pandas and matplotlib, and finish with an evidence-based report of your own.

6 weeks · 60-minute weekly sessions · Runs free in Google Colab

How It Works

From Code to Data

Load a real dataset, inspect it, and answer factual questions about it with code.

→Load and explore a CSV with pandas in Google Colab
→Figure out what one row actually represents
→Filter, sort, and count to answer your first questions

Cleaning & New Columns

Fix a messy dataset and build columns that make comparisons fair.

→Handle missing values, duplicates, and numbers stored as text
→Normalize raw totals into per-pupil figures, rates, and percents
→Write down and justify every cleaning decision

Summarizing & Comparing

Summarize groups and pick the number that tells the truth.

→Build summary tables with groupby and merge
→Mean vs. median, and how one outlier can mislead
→Compare groups and state what the numbers show

Visualization

Pick the right chart for the question and make it honest.

→Bar, histogram, line, and scatter plots with matplotlib
→Titles that state a finding, not just the variables
→Fix misleading charts, then get your capstone dataset

From Analysis to Argument

Turn numbers and charts into a claim backed by evidence.

→Correlation vs. causation, confounders, and small samples
→Structure a report: question, data, findings, claim, limitations
→One-on-one check-in on your capstone question

Capstone Presentations

Present your findings and submit your data-driven report.

→Analyze real Washington K-12 data from OSPI
→Five-minute presentation with your key charts and claim
→Give and get feedback from your peers

Ready to join?

Free for every student. Questions? Email [email protected].