Data Analysis in R at TU München

Flashcards and summaries for Data Analysis in R at the TU München

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Study with flashcards and summaries for the course Data Analysis in R at the TU München

Exemplary flashcards for Data Analysis in R at the TU München on StudySmarter:

Creating a sequnce with replicate function

Exemplary flashcards for Data Analysis in R at the TU München on StudySmarter:

Numerics: Create a sequence

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replicatinge each entry of the input vector at the time

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Names - Properties

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Setting names - two alternatives

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Numerics: Create a sequnce with 20 values

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Which parameter allows to ignore missing values?

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Working with missing values

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Modify the third entry

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Accessint the thrid entry in a vector

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Creating an A,b,c,d,e vector

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How are atomic vectors usually created?

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Exemplary flashcards for Data Analysis in R at the TU München on StudySmarter:

Data Analysis in R

Creating a sequnce with replicate function
rep() replicates a vector a certain number of times and concatenates them
rep(c(TRUE, FALSE), times = 5)
—–> TRUE FALSE TRUE FALSE TRUE FALSE TRUE FALSE TRUE FALSE

Data Analysis in R

Numerics: Create a sequence
seq(from = 1, to 10, by = .3)

Data Analysis in R

replicatinge each entry of the input vector at the time
rep(c(TRUE,FALSE), each = 5)
——> TRUE TRUE TRUE TRUE TRUE FALSE FALSE FALSE FALSE FALSE FALSE

Data Analysis in R

Names - Properties
names don´t have to be unique, but should preferably be, as subsetting by names will only return the first match
x<- c(a = 1, a = 2, b = 3) x["a"] not all elements need to have names c(a = 1,2,3) ##a ##1 2 3

Data Analysis in R

Setting names - two alternatives
x <- c(a = 1, b = 2, c = 3) x OR names(x) <- c("A","B", "c") x

Data Analysis in R

Numerics: Create a sequnce with 20 values
seq(from = 1, to 10, length.out = 20)

Data Analysis in R

Which parameter allows to ignore missing values?
mean(v, na.rm = TRUE)

Data Analysis in R

Working with missing values
missing values are specified with NA
Placeholders for the specific type and such are something like an unspecified value
if not taken care of, it can break computation

v <- c(1,3,5,NA)

Data Analysis in R

Modify the third entry
x[3] <- 'z'

Data Analysis in R

Accessint the thrid entry in a vector
x[3]

Data Analysis in R

Creating an A,b,c,d,e vector
x <- LETTERS[1:5]

Data Analysis in R

How are atomic vectors usually created?
with c() (from concatenation)

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