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Python pandas Filtering out nan from a data selection of a column of strings
...NaN:
In [87]:
nms
Out[87]:
movie name rating
0 thg John 3
1 thg NaN 4
3 mol Graham NaN
4 lob NaN NaN
5 lob NaN NaN
[5 rows x 3 columns]
In [89]:
nms = nms.dropna(thresh=2)
In [90]:
nms[nms.name.notnull()]
Out[90]:
movie name rating
0...
Delete files older than 3 months old in a directory using .NET
...o know (using C#) how I can delete files in a certain directory older than 3 months, but I guess the date period could be flexible.
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How do I choose grid and block dimensions for CUDA kernels?
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3 Answers
3
Active
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Check if two unordered lists are equal [duplicate]
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463
Python has a built-in datatype for an unordered collection of (hashable) things, called a set. I...
What is the bower (and npm) version syntax?
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342
In a nutshell, the syntax for Bower version numbers (and NPM's) is called SemVer, which is sho...
Remove ActiveRecord in Rails 3
Now that Rails 3 beta is out, I thought I'd have a look at rewriting an app I have just started work on in Rails 3 beta, both to get a feel for it and get a bit of a head-start. The app uses MongoDB and MongoMapper for all of its models and therefore has no need for ActiveRecord. In the previous ver...
How to round to 2 decimals with Python?
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answered Dec 8 '13 at 18:20
roliszrolisz
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Is there an R function for finding the index of an element in a vector?
... function match works on vectors :
x <- sample(1:10)
x
# [1] 4 5 9 3 8 1 6 10 7 2
match(c(4,8),x)
# [1] 1 5
match only returns the first encounter of a match, as you requested. It returns the position in the second argument of the values in the first argument.
For multiple matching, ...
Numpy argsort - what is it doing?
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Returns the indices that would sort an array.
2 is the index of 0.0.
3 is the index of 0.1.
1 is the index of 1.41.
0 is the index of 1.48.
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Convert column classes in data.table
...rter)]
str(dtnew)
Classes ‘data.table’ and 'data.frame': 10 obs. of 3 variables:
$ ID : Factor w/ 2 levels "A","B": 1 1 1 1 1 2 2 2 2 2
$ Quarter: chr "1" "2" "3" "4" ...
$ value : num -0.838 0.146 -1.059 -1.197 0.282 ...
Using lapply and as.character:
dtnew <- dt[, lapply(....
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