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  2. Compare if two dataframe objects in R are equal?

    stackoverflow.com/questions/10592148

    It is not clear what it means to test if two data frames are "value equal" but to test if the values are the same, here is an example of two non-identical dataframes with equal values: a <- data.frame(x = 1:10) b <- data.frame(y = 1:10) To test if all values are equal: all(a == b) # TRUE

  3. (=) is a Assignment operator while (==) is a Equal to operator. (=) is used for assigning the values from right to left while (==) is used for showing equality between values. Example:

  4. Numeric comparison difficulty in R - Stack Overflow

    stackoverflow.com/questions/2769510

    55. I'm trying to compare two numbers in R as a part of a if-statement condition: In this particular instance, a = 0.58 and b = 0.08... and yet (a-b) >= 0.5 is false. I'm aware of the dangers of using == for exact number comparisons, and this seems related: all.equal((a - b), 0.5) is true. The only solution I can think of is to have two ...

  5. Add a less than or equal to symbol to R string. 0. add symbol to just one axis label in R. 161.

  6. The operators <- and = assign into the environment in which they are evaluated. The operator <- can be used anywhere, whereas the operator = is only allowed at the top level (e.g., in the complete expression typed at the command prompt) or as one of the subexpressions in a braced list of expressions.

  7. From here: The operators <- and = assign into the environment in which they are evaluated. The operator <- can be used anywhere, whereas the operator = is only allowed at the top level (e.g., in the complete expression typed at the command prompt) or as one of the subexpressions in a braced list of expressions. answered Feb 16, 2010 at 8:56.

  8. cut_number(): Makes n groups with (approximately) equal numbers of observation; cut_interval(): Makes n groups with equal range; cut_width(): Makes groups of width; My go-to is cut_number() because this uses evenly spaced quantiles for binning observations. Here's an example with skewed data.

  9. I need to filter/subset a dataframe using values in two columns to remove them. In the examples I want to keep all the rows that are not equal (!=) to both replicate "1" and treatment "a". However, either subset and filter functions remove all replicate 1 and all treatment a. I could solve it by using which and then indexing, but it is not the ...

  10. sum is used to add elements; nrow is used to count the number of rows in a rectangular array (typically a matrix or data.frame); length is used to count the number of elements in a vector. You need to apply these functions correctly. Let's assume your data is a data frame named "dat". Correct solutions:

  11. R doesn't expect further input past your first evaluation, unless you feed it a Boolean & for vectors. You may want to modify this, but here's one attempt at a functional programming approach: testEqual <- function(x, y) ifelse(x == y, x, FALSE) all(!!Reduce(testEqual, list(1:10, 1:10))) # True.