I feel like there is a better way than this: To achieve this: Is there a way to do it that avoids the callback? Answer use cumcount(), see docs here If you want orderings starting at 1
Tag: group-by
Pandas get topmost n records within each group
Suppose I have pandas DataFrame like this: which looks like: I want to get a new DataFrame with top 2 records for each id, like this: I can do it with numbering records within group after groupby: which looks like: then for the desired output: Output: But is there more effective/elegant approach to do this? And also is there more
Pandas dataframe get first row of each group
I have a pandas DataFrame like following: I want to group this by [“id”,”value”] and get the first row of each group: Expected outcome: I tried following, which only gives the first row of the DataFrame. Any help regarding this is appreciated. Answer If you need id as column: To get n first records, you can use head():
Pandas ‘count(distinct)’ equivalent
I am using Pandas as a database substitute as I have multiple databases (Oracle, SQLÂ Server, etc.), and I am unable to make a sequence of commands to a SQL equivalent. I have a table loaded in a DataFrame with some columns: In SQL, to count the amount of different clients per year would be: And the result would be How