The way how the categories are forged, renders information invisible that might have been valuable for political debates. When drinking qulity water is used to clean cars, this can be problematized, however the combination of practices into categories (however necessery) hampers to state how much water is used in particular practices. The data here can only be read in a mingle of watering a garden, providing water to animals, washing a car or the living room, which might be assigned different importances and values in political negotiations on water spendings.
The document doesn't give information on the definitions of the seven categories that are represented in the table. It might be interesting to find out, how the broad bundles of practices have been made -- why is the toilet flush not subsumed under body care, why is car cleaning in the same category as garden watering? The categorizations made might come from the urge to find broad enough categories to make graphics and tables readable (opposed to a fine-grained detailed table with hundreds of different practices that use water). But they might also emerge from contraints in measurment, if the spended water is measured with counters intstalled at different water valves in the house. That would fit very plausible to the categorizations as for example watering a garden and cleaning a car is most probably both done with a water valve outside, if existing and accessible. It would be interesting, wether queries have been made to configure the list of practices that are mentioned and how they are clustered or wether they result from mere considerations of what valve is most propably used for what.
The category that evades my ways of making sense of the data and imagining their crafting-process is that of "small business" in the last row. If it would be different water valves, this would not make sense, unless this number just points to workshop-watervalves which would not include tea-cooking in the kitchen of creative workers in home office for example.
The dataset shows how households, including per definition given in the datasheet also small business enterprises (with less than 60.000 € profit per year according to the legal definition of the german term), use fresh water. It therefore assembles average data from German households over the course of the year 2021 and breaks it down to Liter per person per day.
Each row represents one usage-category for fresh water such as the usages "Bathing, showering", "toilett", "cleaning, garden and car cleaning" etc.. The rows already bundle diverse practices into these categories. In total, 7 categories are given.
The second collumn provides the percentage of the total water spendings that is attributable to the category, the third collumn presents the number of liters used per person per day for the mentionned activity.
From the footnote I draw, that the numbers in the third collumn are not part of the inquiry of BDEW, the data source, but product of a simple calculation of the percentage in collumn 2 with the liter/person and day-figure that the Statistisches Bundesamt gives for the water consuption (127 liter/person and day)