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How do I replace NA values with zeros in an R dataframe?
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See my comment in @gsk3 answer. A simple example:
> m <- matrix(sample(c(NA, 1:10), 100, replace = TRUE), 10)
> d <- as.data.frame(m)
V1 V2 V3 V4 V5 V6 V7 V8 V9 V10
1 4 3 NA 3 7 6 6 10 6 5
2 9 8 9 5 10 NA 2 1 7 2
3 1 1 6 3 6 ...
Equation for testing if a point is inside a circle
If you have a circle with center (center_x, center_y) and radius radius , how do you test if a given point with coordinates (x, y) is inside the circle?
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Callback functions in C++
...s of the standard algorithms library <algorithm> use callbacks. For example the for_each algorithm applies an unary callback to every item in a range of iterators:
template<class InputIt, class UnaryFunction>
UnaryFunction for_each(InputIt first, InputIt last, UnaryFunction f)
{
for (...
How do function pointers in C work?
I had some experience lately with function pointers in C.
11 Answers
11
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Simultaneously merge multiple data.frames in a list
...icate of this one so I answer here, using the 3 sample data frames below:
x <- data.frame(i = c("a","b","c"), j = 1:3, stringsAsFactors=FALSE)
y <- data.frame(i = c("b","c","d"), k = 4:6, stringsAsFactors=FALSE)
z <- data.frame(i = c("c","d","a"), l = 7:9, stringsAsFactors=FALSE)
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How can we make xkcd style graphs?
Apparently, folk have figured out how to make xkcd style graphs in Mathematica and in LaTeX . Can we do it in R? Ggplot2-ers? A geom_xkcd and/or theme_xkcd?
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How to detect a Christmas Tree? [closed]
... so the first threshold is just a simple monochrome brightness test; any pixels with values above 220 on a 0-255 scale (where black is 0 and white is 255) are saved to a binary black-and-white image. The second threshold tries to look for red and yellow lights, which are particularly prominent in t...
promise already under evaluation: recursive default argument reference or earlier problems?
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Formal arguments of the form x=x cause this. Eliminating the two instances where they occur we get:
f <- function(x, T) {
10 * sin(0.3 * x) * sin(1.3 * x^2) + 0.001 * x^3 + 0.2 * x + 80
}
g <- function(x, T, f. = f) { ## 1. note f.
exp(-...
How to find the statistical mode?
In R, mean() and median() are standard functions which do what you'd expect. mode() tells you the internal storage mode of the object, not the value that occurs the most in its argument. But is there is a standard library function that implements the statistical mode for a vector (or list)?
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