Tangy is building your next step
Shaping the lesson around what you want to make.
Tangy is building your next step
Shaping the lesson around what you want to make.
Computer Science
You already know the basic Python building blocks, so this course will use them immediately instead of reteaching syntax. You will build a reusable study-session analysis that reads a CSV, cleans real-world data, answers useful questions with pandas, and produces a clear report with charts. The finished project is a runnable Python script that accepts your study-session CSV and outputs summaries of time spent, subjects, completion rates, and trends, plus saved visualizations you can show.
Build it yourself, get guided when you are stuck, and leave with proof you can actually show.
From CSV File to First Findings
3 lessonsUse familiar Python variables, functions, and control flow to create the project, load tabular data, and produce its first useful analysis.
Clean Data and Ask Better Questions
4 lessonsTurn imperfect rows into trustworthy data, then use filtering, new columns, and grouping to answer concrete questions about the learner's study habits.
Build a Reliable Analysis Pipeline
4 lessonsOrganize the growing analysis into reusable steps and add date-based and comparative findings without introducing a second major framework.
Show the Results Clearly
3 lessonsTurn the trustworthy analysis into a small report with visual evidence, then polish the command and outputs so the project is ready to run or demonstrate.
Public lesson
Tasks
In your terminal, run:
mkdir -p study-session-analysis/data
cd study-session-analysis
mkdir -p study-session-analysis/data
cd study-session-analysis
Tasks
Check that you are in the new folder:
pwd
pwd
The final part of the printed path should be:
study-session-analysis
study-session-analysis
Tasks
Inside study-session-analysis/data, create a file named sessions.csv with this content:
date,subject,minutes,focus_score,notes
2026-07-20,React,45,4,Built a card component
2026-07-21,CSS,30,3,Practiced selectors
2026-07-22,Python,25,5,Reviewed file handling
date,subject,minutes,focus_score,notes
2026-07-20,React,45,4,Built a card component
2026-07-21,CSS,30,3,Practiced selectors
2026-07-22,Python,25,5,Reviewed file handling
The first row is the header: it names the information each later row contains.
Tasks
Check the file from the project folder:
cat data/sessions.csv
cat data/sessions.csv
You should see the header and three study sessions.
Tasks
Create a file named analyze.py in the project folder. Start with this skeleton:
DATA_FILE = "TODO"
print("Study-session analysis starting")
print(f"Analyzing: {DATA_FILE}")
DATA_FILE = "TODO"
print("Study-session analysis starting")
print(f"Analyzing: {DATA_FILE}")
Tasks
Replace "TODO" with the relative path to your CSV file. Do not use an absolute path from your computer; the project should still work if the whole folder is moved.
Your finished file should contain the correct path in a line shaped like this:
DATA_FILE = "your-relative-path-here"
DATA_FILE = "your-relative-path-here"
The two print lines are already provided because they are simple command-line status messages. Your part is connecting the program to the file you created.
Tasks
From inside study-session-analysis, run:
python analyze.py
python analyze.py
If your computer uses python3 for Python, run:
python3 analyze.py
python3 analyze.py
The output should clearly identify both the program and the file, similar to:
Study-session analysis starting
Analyzing: data/sessions.csv
Study-session analysis starting
Analyzing: data/sessions.csv
The exact first line must be:
Study-session analysis starting
Study-session analysis starting
The second line must contain:
data/sessions.csv
data/sessions.csv
Find the bug
Something's wrong — can you spot it?
If you see TODO, the path in analyze.py has not been replaced yet. If you see a file-not-found error, check that:
study-session-analysissessions.csvdata/sessions.csvTasks
Your project should now have this shape:
study-session-analysis/
├── analyze.py
└── data/
└── sessions.csv
study-session-analysis/
├── analyze.py
└── data/
└── sessions.csv
Run the program once more after checking the structure. It is ready for the next step when it prints the starting message and the CSV path without an error.
4 modules · 14 lessons
From CSV File to First Findings
Clean Data and Ask Better Questions
Build a Reliable Analysis Pipeline
Show the Results Clearly
Learn by building your own version.
Remix this public project to open the workspace, follow the guided build, and let the AI mentor teach you through the work instead of doing it for you.