54 lines
1.5 KiB
R
54 lines
1.5 KiB
R
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# Creating a matrix for demonstration
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matrix_data <- matrix(1:9, nrow=3, byrow=TRUE)
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print("Original Matrix:")
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print(matrix_data)
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# Using apply on a matrix
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# -----------------------
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# Sum of each row
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row_sums <- apply(matrix_data, 1, sum)
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print("Sum of each row:")
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print(row_sums)
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# Sum of each column
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col_sums <- apply(matrix_data, 2, sum)
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print("Sum of each column:")
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print(col_sums)
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# Creating a list for demonstration
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list_data <- list(a = 1:5, b = 6:10, c = 11:15)
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print("Original List:")
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print(list_data)
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# Using lapply on a list
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# ----------------------
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# Compute the mean of each element in the list
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list_means <- lapply(list_data, mean)
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print("Mean of each list element:")
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print(list_means)
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# Using sapply on a list
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# ----------------------
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# sapply simplifies the result to a vector or matrix if possible
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list_means_simplified <- sapply(list_data, mean)
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print("Simplified mean of each list element:")
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print(list_means_simplified)
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# Using vapply on a list
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# ----------------------
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# vapply allows for specifying the type of return value, making it safer than sapply
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list_means_vapply <- vapply(list_data, mean, numeric(1))
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print("Vapply mean of each list element:")
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print(list_means_vapply)
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# Creating a vector and factor for demonstration
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vector_data <- c(1, 2, 3, 4, 5, 6)
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factor_data <- gl(2, 3, labels = c("Group1", "Group2"))
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# Using tapply on a vector
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# ------------------------
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# Apply a function over subsets of a vector
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group_means <- tapply(vector_data, factor_data, mean)
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print("Mean of vector elements by group:")
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print(group_means)
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