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generate days from date range
...) + (100 * c.a) + (1000 * d.a) ) DAY as Date
from (select 0 as a union all select 1 union all select 2 union all select 3 union all select 4 union all select 5 union all select 6 union all select 7 union all select 8 union all select 9) as a
cross join (select 0 as a union all select 1 union...
Postgres NOT in array
... edited Feb 26 '14 at 17:55
All Workers Are Essential
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answered Jul 30 '12 at 22:44
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Remove columns from dataframe where ALL values are NA
I'm having trouble with a data frame and couldn't really resolve that issue myself:
The dataframe has arbitrary properties as columns and each row represents one data set .
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Able to push to all git remotes with the one command?
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To push all branches to all remotes:
git remote | xargs -L1 git push --all
Or if you want to push a specific branch to all remotes:
Replace master with the branch you want to push.
git remote | xargs -L1 -I R git push R master
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Drop rows with all zeros in pandas data frame
I can use pandas dropna() functionality to remove rows with some or all columns set as NA 's. Is there an equivalent function for dropping rows with all columns having value 0?
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delete_all vs destroy_all?
...any tables. I want to delete this user and every record that has his ID in all tables.
4 Answers
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Set up git to pull and push all branches
I'd like to push and pull all the branches by default, including the newly created ones.
8 Answers
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Get the week start date and week end date from week number
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But you don't have to remember that table and just the formula, and actually you could use a slightly different one too the main need is to use a value that will make the remainder the correct number of days.
Here is a working example:
DECLARE @MondayDateFirstValue INT = 1
DECLARE @FridayDateFi...
What does “all” stand for in a makefile?
...s concerning Makefiles but for me it is still unclear for what the target "all" stands for and what it does.
4 Answers
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Simultaneously merge multiple data.frames in a list
...ch data.frame differs in terms of the number of rows and columns, but they all share the key variables (which I've called "var1" and "var2" in the code below). If the data.frames were identical in terms of columns, I could merely rbind , for which plyr's rbind.fill would do the job, but that'...