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Questions - group-by

How to Create View based on Column values

I have a table: +------+----------+----------+-------+ | id | location | variable | value | +------+----------+----------+-------+ | 1 | loc1 | outside | 30.6 | | 2 | loc1 | inside ...
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user117911

sql

sql-server

group-by

Votes: 0

Answers: 1

Latest Answer

You can use conditional aggregation (depending on the current model represents the whole dataset) like SELECT location, MAX(CASE WHEN variable='outside' THEN value END) AS outside, MAX(...
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Barbaros Özhan

How to use groupBy in Pandas to sum total revenue of a customer

I'm working with a database but I'm having a problem with only one thing The part I want to show is in the image below: This database includes each customer and their respective plan, indicated by th...
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Agenor

python

python-3.x

pandas

dataframe

group-by

Votes: 0

Answers: 5

Latest Answer

You can aggregate the results by using groupby function. df.groupby('id').agg({'revenue':'sum'})
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Rutuja Kardile

Max and Group by functions in SQL Server

my sql got a bit rusty and I was wondering if there is a simple solution for my ask. I'm trying to get two unique UUIDs with with MAX ModifiedTime. Below is my code that I tried to simplify as much as...
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user7948585

sql

group-by

max

common-table-expression

Votes: 0

Answers: 3

Latest Answer

Sub-query and inner join takes care of this. SELECT t1.uuid ,t1.Description ,t1.IsHLVE ,t1.modifiedtime FROM tblConstructSecureIntelProjectIncidents as t1 INNER JOIN ( SELECT ...
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Edward Radcliffe

Pandas group by multiple custom aggregate function on multiple columns

Given data: grp data1 data2 data3 a 2 1 2 a 4 6 3 b 3 2 1 b 7 3 5 Expected output: grp sum(data1) sum(data2)/sum(data1) sum(data3)/sum(data1) a 6 1.166666667 0.83 a 10 0.5 ...
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Parshant garg

python

pandas

group-by

aggregate

Votes: 0

Answers: 2

Latest Answer

You could do: df2 = df.groupby('grp').sum() df2.update(df2.drop(columns='data1').div(df2['data1'], axis=0)) or more classically: df2 = df.groupby('grp').sum() df2[['data2', 'data3']] = df2[['data2', ...
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mozway

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