[Administrative note: If you learned Python years ago, then you might not even know how much Python has changed, and what techniques you're missing out on . My upcoming 8-hour "python --update" course will help you understand everything from structured pattern matching to asyncio, it is free to LernerPython members. For more info, go to https://LernerPython.com/python-update.]
Algae has been in the news quite a bit lately – but when Marketplace had a story about it earlier this week (https://www.marketplace.org/story/2026/07/06/how-algae-can-crater-lake-eries-economy), they weren't talking about the Reflecting Pool in Washington, DC. Rather, they were talking about Lake Erie, and its harmful algal bloom.
The report was about how parts of Lake Erie are bright green during parts of the summer. The reason? Cyanobacteria, a form of bacteria that lives in the water, and which grows via photosynthesis, something that we normally associate with plants. (Note: Cyanobacteria is not a plant. But it is still referred to as "algae," and the green, paint-like substance it creates and leaves on the water is known as "algal bloom.")
The problem with the cyanobacteria isn't the color (although it probably doesn't help). The issue is that the cyanobacteria produce microcystin, a liver toxin – which is not something you want in the drinking-water supply for cities like Toledo. When the bloom dies, its decomposition by other bacteria consumes the water's oxygen, creating low-oxygen dead zones that can suffocate fish.
One major factor in the harmful algal bloom is runoff from the nearby Maumee River. That river passes through Ohio farmland, where it picks up phosphorus. That phosphorus is carried to the lake, where it accelerates the cyanobacteria's growth.
This week, we'll look at data from the Maumee River, which is checked three times each day (!) for phosphorus and other substances that contribute to the harmful algal bloom. We'll also look at measurements of the harmful algal bloom from Lake Erie.
Data and five questions
This week, we have two pieces of complementary data:
First, we have the many measurements taken on the Maumee River, provided by the National Center for Water Quality research (https://ncwqr-data.org/HTLP/Portal.) From their site, you can select the Maumee station, and click on "download."
Then we'll look at data about Lake Erie itself, with algal bloom measurements taken by the National Oceanic and Atmospheric Administration. You can download that from
Paid subscribers, both to Bamboo Weekly and to my LernerPython+data membership program (https://LernerPython.com) get all of the questions and answers, as well as downloadable data files, downloadable versions of my notebooks, one-click access to my notebooks, and invitations to monthly office hours.
Learning goals for this week include Dates and times and joins.
Here are my five questions for this week. I'll be back tomorrow with my solutions and explanations:
- Read the Maumee River data into a Pandas data frame. Keep only the "Value" columns, and rename the columns to use the text in square brackets. So "Value [FLOW] Flow (cfs)" would become just FLOW. How many samples were there, on average, per year? Has that frequency changed over time?
- The dissolved-phosphorus column (SRP) has many negative values, plus rows flagged "below detection". What do you think could and should be done with those values?