

The production methods for the three ingredient types and the standard ingredient mix were evaluated using primary data and assessed using a life cycle assessment on four significant environmental impacts: global warming potential, land use, water consumption, and marine eutrophication (when there’s too many nutrients in an ecosystem and it causes issues like algal blooms).Īs is often the case, there was not a clear ‘winner’ in terms of which would have the lightest environmental impact, but instead it pointed to tradeoffs between them, and the need for more research. Bakery by-products from food manufacturing plants.Food waste from retail outlets processed into a feed ingredient.Food waste from retail outlets fed to black soldier fly larvae, processed into meal.for a detailed guide, check out pandas’ official guide (it’s very updated - last refreshed in 2022), here.Unfortunately, swapping all this food waste back into the feed chain is not so simple – farmers need to consider what’s healthiest for their livestock, it must be consistently available, cost-efficient, and we also need to understand the environmental impacts, benefits, and tradeoffs of how that waste would get turned into the feed.Īs part of its No Food Left Behind series, WWF, in partnership with Quantis, Penn State University, and with support and data sharing from several other farms, universities, and retailers, explored three different pathways of transforming food waste into feed for egg-laying hens and compared them to standard feed production. Also check out my 6-week online course: The Junior Data Scientist’s First Month video course.
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This was the second episode of my pandas tutorial series. And as per usual: the count() function is the last piece of the puzzle.Ĭonclusion (pandas groupby, count, sum, min, max, etc.).That’s why the bracket frames go between the parentheses.) (That was the groupby() part.) Then on this subset, we applied a groupby pandas method… Oh, did I mention that you can group by multiple columns? Now you know that, too! 😉 (Syntax-wise, watch out for one thing: you have to put the name of the columns into a list.First, we filtered for the users of country_2 with article_read.
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Let’s start with our zoo dataset! (If you want to download it again, you can find it at this link.) We have loaded it by using: pd.read_csv('zoo.csv', delimiter = ',')


The theory is not too complicated, right? Or a different aggregation method would be to count the number of the values in the animal column, which is 4. …then a simple aggregation method is to calculate the sum of the water_need values, which is 100 + 350 + 670 + 200 = 1320. Let me make this clear! If you have a pandas DataFrame like… animal Aggregation is the process of turning the values of a dataset (or a subset of it) into one single value.
