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2024-03-12 17:30:08
The groupby last function should work in this use case, as long as you can confirm that your data is being entered chronologically you can just do import pandas df = pandas.DataFrame(columns=['item',...
Tags: python dataframe group-by
2024-03-12 23:30:04
Here is how you can use your query as a subquery and perform the grouping SELECT Name,ID,MaxStatus FROM ( SELECT Name,ID,Status,MAX(Status) OVER(PARTITION BY Name) AS MaxStatus FROM [dbo].[TaskStat...
Tags: sql group-by partition
2024-03-13 16:00:05
If you want to sample N rows with about the same probability to sample each group, you could oversample per group then sample again: import math N = 4 out = (df.groupby('ID').sample(n=math.ceil(N/df...
Tags: python pandas group-by

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