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How do I detect a click outside an element?
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community wiki
10 revs, 7 users 52%Eran Galperin
721
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Group by multiple columns in dplyr, using string vector input
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data = data.frame(
asihckhdoydkhxiydfgfTgdsx = sample(LETTERS[1:3], 100, replace=TRUE),
a30mvxigxkghc5cdsvxvyv0ja = sample(LETTERS[1:3], 100, replace=TRUE),
value = rnorm(100)
)
# get the columns we want to average within
columns = names(data)[-3]
library(dplyr)
df1 <- data %>%...
A semantics for Bash scripts?
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107
A shell is an interface for the operating system. It is usually a more-or-less robust programmi...
jQuery selector for inputs with square brackets in the name attribute
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answered Mar 2 '10 at 17:00
DancrumbDancrumb
22.5k66 gold badges5555 silver badges124124 bronze badges
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What do you call the -> operator in Ruby?
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240
In Ruby Programming Language ("Methods, Procs, Lambdas, and Closures"), a lambda defined using -...
How do you create nested dict in Python?
...ers
f.next()
# get first colum as keys
keys = (line.split(',')[0] for line in f)
# create empty dictionary:
d = {}
# read from file b.csv
with open(b_file) as f:
# gather headers except first key header
headers = f.next().split(',')[1:]
# iterate lines
for line in f:
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Why does the C# compiler go mad on this nested LINQ query?
...machine) and very long time to compile (actually I get IO exception after 10 minutes).
1 Answer
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Does uninstalling a package with “pip” also remove the dependent packages?
...ze # all the packages here are dependencies of specloud package
figleaf==0.6.1
nose==1.1.2
pinocchio==0.3
specloud==0.4.5
$ pip uninstall specloud
$ pip freeze
figleaf==0.6.1
nose==1.1.2
pinocchio==0.3
As you can see those packages are dependencies from specloud and they're still there, but no...
SVG gradient using CSS
...pe-rendering: crispEdges;
fill: url(#MyGradient);
}
<svg width="100" height="50" version="1.1" xmlns="http://www.w3.org/2000/svg">
<style type="text/css">
rect{fill:url(#MyGradient)}
</style>
<defs>
<linearGradient id="MyGradie...
Find the most common element in a list
...# print 'SL:', SL
groups = itertools.groupby(SL, key=operator.itemgetter(0))
# auxiliary function to get "quality" for an item
def _auxfun(g):
item, iterable = g
count = 0
min_index = len(L)
for _, where in iterable:
count += 1
min_index = min(min_index, where)
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