A real data set in Python: read a CSV, count, average and find the biggest, draw a bar chart, clean messy data and check it with test cases, then build a dashboard.
Read a CSV file into a list of dictionaries, then count, filter, total and average it.
Read a CSV file into a list of dictionaries, one per row, then pick out the rows you want.
Add up a column, divide for the average, and keep the biggest so far, one row at a time.
Draw a bar chart from counts, then clean messy data and check your code with test cases.
Count every genre at once with a dictionary, then draw each count as a bar of
Real data is messy. Write a function that cleans one value, check it with test cases, and skip the rows it cannot fix.
Put the data behind a small app, then ask a real API for live data (optional).
Read the table with pandas and put it behind a Gradio app: choose a genre, see its songs as a table and a bar chart.
Ask a real weather service for the week's forecast, read the JSON it sends back, and fall back to a saved copy when there is no connection.
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