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IntelliJ: How to auto-highlight variables like in Eclipse
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Using 2016.2 and this doesn't work at all. The setting was on by default, but it's not highlighting the variable my cursor is on (unless it is somehow the same colour as the non-highlight?)
– Adam
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Convert the values in a column into row names in an existing data frame
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As of 2016 you can also use the tidyverse.
library(tidyverse)
samp %>% remove_rownames %>% column_to_rownames(var="names")
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How to use IntelliJ IDEA to find all unused code?
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My 2 cents: on IntelliJ 2016.3.4 the option is under Analyze > Run Inspection By Name. -- My 5 cents: if you're working on a big project and you're running the feature for the whole project, I suggest you to do it before lunch or at the end of th...
port forwarding in windows
...onnectivity. So, this is the correct solution. See also netfxharmonics.com/2016/03/nginx
– David Betz
Jan 15 '19 at 15:45
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Create SQLite Database and table [closed]
... SQLite can be in inserting and retrieving records: technical-recipes.com/2016/using-sqlite-in-c-net-environments
– AndyUK
Apr 15 '17 at 9:10
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Subtract one day from datetime
...btract the number of days you want from a datetime.
SELECT GETDATE() - 1
2016-12-25 15:24:50.403
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How to set IntelliJ IDEA Project SDK
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ultimate 2016.1 but never mind i fixed it :) thanks anyway
– HasS
May 10 '16 at 9:52
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How to convert 'binary string' to normal string in Python3?
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@lyomi In 2016 (and its nearly the end) people still use ascii. There are many many 'legacy' products and systems (including specifications), but there are also lots of reasons why you might be creating a 'binary string' where you don'...
Apply style to parent if it has child with css [duplicate]
.../1014861/… the :has() pseudoclass no longer works with any browser as of 2016. Just so people don't get frustrated at this not working.
– Ryan Smith
Jun 28 '16 at 19:21
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numpy matrix vector multiplication [duplicate]
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>>> np.einsum('ji,i->j', a, b)
array([16, 6, 8])
As of mid 2016 (numpy 1.10.1), you can try the experimental numpy.matmul, which works like numpy.dot with two major exceptions: no scalar multiplication but it works with stacks of matrices.
>>> np.matmul(a, b)
array([16, 6,...