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Python for Data Work

A practical on-ramp to data work in Python: the language basics you need, pandas, plotting, and reproducible workflows.

  • Beginner
  • 3h 35m
  • 4 modules
  • 12 lessons
  • 31.4k students
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Taught by Tomas Berg · Python, pandas, System design, Distributed systems

Cover image for Python for Data Work

What you’ll learn

  • Write practical Python

    Use the data types, comprehensions, and file handling that data work leans on daily.

  • Work with dataframes

    Load, clean, filter, and aggregate tabular data with pandas without fighting the API.

  • Visualise findings

    Produce charts that communicate a result rather than merely displaying numbers.

  • Make it reproducible

    Manage environments and turn a notebook into something that runs the same way twice.

Course content

4 modules · 3h 35m

  1. 01Python Foundations for DataThe subset of Python that data work actually uses, taught in the order you will need it.25m
    1. 1.1Lists, dicts, and the types you will useFree8m
    2. 1.2Comprehensions and iteration10m
    3. 1.3Reading files and CSVs7m
  2. 02pandas EssentialsThe dataframe workflow: loading, cleaning, reshaping, and summarising tabular data.1h 14m
    1. 2.1Series, dataframes, and indexing31m
    2. 2.2Cleaning messy data32m
    3. 2.3groupby and aggregation11m
  3. 03Visualising DataTurning a result into a chart someone can read, and knowing which chart to reach for.1h 13m
    1. 3.1Plotting with matplotlib31m
    2. 3.2Statistical plots with seaborn36m
    3. 3.3Choosing the right chart6m
  4. 04Reproducible WorkflowsMaking the analysis run again next month, on someone else’s machine, with the same result.44m
    1. 4.1Working effectively in notebooks23m
    2. 4.2Virtual environments and dependencies9m
    3. 4.3Automating a recurring data job12m
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