Bamboo Weekly
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Your product? Claim it to see where they come fromAbout Bamboo Weekly
Bamboo Weekly is a newsletter of weekly data-analysis exercises using Python and Pandas. Each issue is built around a real-world dataset tied to current events, such as Nobel Prize winners, election financing, data centers, AI security incidents and hurricane season. Subscribers attempt the problems on their own, and detailed solutions follow a day or so later, with Thursday walkthroughs and Jupyter notebooks.
Issues list the skills they target, including pivot tables, multi-indexes, PyArrow, Polars, working with APIs, handling JSON and BSON files, cleaning, grouping, joins, dates and times, plotting with Plotly and agentic coding. The publication also runs Pandas office hours where readers can ask questions.
Bamboo Weekly is written by Reuven M. Lerner and is a LernerPython product, published on Ghost. Readers quoted on the site include working data analysts and job seekers who use the exercises as regular, deliberate practice to keep their Pandas skills current.
Best for
- Data analysts improving Pandas skills
- Python users wanting regular deliberate practice
- Job seekers sharpening data-analysis skills
Pros
- Exercises use real datasets based on current events
- Detailed solutions with walkthroughs and Jupyter notebooks
- Covers Pandas, Polars, PyArrow, Plotly and more
- Live Pandas office hours for questions
Cons
- Recent issues are marked as paid content
- Focused on Python; no other languages mentioned
Bamboo Weekly FAQ
- What does each week include?
- A set of data-analysis exercises on a real-world dataset, followed by detailed solutions with walkthroughs and Jupyter notebooks.
- Which tools and topics are covered?
- Mainly Python and Pandas, plus topics such as Polars, PyArrow, Plotly, APIs, JSON, cleaning, grouping, joins and dates and times.
- Who writes Bamboo Weekly?
- It is written by Reuven M. Lerner and is a LernerPython product.
- Is there live support?
- Yes, there are Pandas office hours where subscribers can ask questions about Pandas.
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