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SQL - JOIN if specific column contains data matching two others


SQL - JOIN if specific column contains data matching two others

By : user2951176
Date : November 18 2020, 01:01 AM
To fix this issue Left outer joins take all rows of the first table along with rows of the second table, even if there is no matching row in the second table.
For exact matches, you can use:
code :
select * from table1 left outer join table2 on firstName || ' ' || lastName = fullName
select * from table1 left outer join table2 on concat_ws(' ', firstName, lastName) = fullName
select * from table1 left outer join table2 on fullName like firstName || '%' and fullName like '%' || lastName
select * from table1 left outer join table2 on fullName like concat(firstName, '%') and fullName like concat('%', lastName)


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Add specific value to a data.frame column by matching a pattern

Add specific value to a data.frame column by matching a pattern


By : jca
Date : March 29 2020, 07:55 AM
I wish this help you I'm only really posting this since Tyler said "if you wanted a one liner data.table would likely do it" and I knew it was definitely possible with a one liner in base. I am also assuming match had been renamed to mat.
code :
  pattern$new_val <- c("Y", "X")[(pattern$pattern %in% mat)+1]
  pattern
#  pattern val new_val
#1       A   1       X
#2       B   1       Y
#3       C   2       X
#4       D   2       Y
what is the fastest way to join several tables matching specific column values in MySQL

what is the fastest way to join several tables matching specific column values in MySQL


By : user3758151
Date : March 29 2020, 07:55 AM
wish helps you For kicks try it with a covered index (a composite of id,col1) So 1 index make it primary composite. No other indexes.
Then run analyze table xxx (3 times total, once per table)
data frame set value based on matching specific row name to column name

data frame set value based on matching specific row name to column name


By : Fouzia Said
Date : March 29 2020, 07:55 AM
this one helps. We can use sapply to loop through rownames of df and use grepl to check which column has that row name and convert the value to 1 for those.
code :
df[] <- t(sapply(rownames(df), function(x) as.numeric(grepl(x, colnames(df)))))
df

#     x.var1.t1 x.var2.t1 x.var1.t4 x.var3.t1 x.var3.t7
#var1         1         0         1         0         0
#var2         0         1         0         0         0
#var3         0         0         0         1         1
#var4         0         0         0         0         0
df[] <- +t(sapply(rownames(df), grepl, colnames(df)))
How to find the lowest value in a data frame matching specific criterias and return a specific column

How to find the lowest value in a data frame matching specific criterias and return a specific column


By : user2895788
Date : March 29 2020, 07:55 AM
it should still fix some issue This does away with the apply and the getRecommendation function. R is vectorized so we should try to think column-wise as much as we can.
code :
comparison <- merge(effective.costs, predicted.costs, by = c("user", "month"))

comparison%>%
  mutate(net_savings = calculated_costs-costs)%>%
  group_by(user, month)%>%
  filter(net_savings == min(net_savings))%>%
  slice(1) #for ties
How to JOIN two SQL tables to get a specific additional data based on matching id's

How to JOIN two SQL tables to get a specific additional data based on matching id's


By : user3470584
Date : March 29 2020, 07:55 AM
Does that help I haven't done a JOIN query in a long time, so I'm pretty rusty. What I have: a table called triggers and users. Initially, I just had a query that selected all of the information from the triggers table. This includes a user_id. Well, instead of just showing a user_id, I thought it would make sense to turn the user_id into the username. , for sql code you need only
code :
SELECT
    t.*,
    u.id,
    u.username
FROM  triggers AS t
LEFT JOIN  users AS u ON t.user_id = u.id
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