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authorleshe4ka46 <alex9102naid1@ya.ru>2025-11-15 16:30:38 +0300
committerleshe4ka46 <alex9102naid1@ya.ru>2025-11-18 14:05:14 +0300
commit2ade61411a014b3eed24bd2b382687d55233a9b5 (patch)
tree1b91eb11d38a0a053a7a806fedadb8c8a676738b /lab2
parent5aaff9711387ce1ea1ec8ee5c5b4ecd9e1ea3dd1 (diff)
R(Cluster)
Diffstat (limited to 'lab2')
-rw-r--r--lab2/Rplots.pdfbin5314 -> 0 bytes
-rw-r--r--lab2/abc.Rdatabin109 -> 0 bytes
-rwxr-xr-xlab2/intro.r48
-rwxr-xr-xlab2/main.r74
4 files changed, 0 insertions, 122 deletions
diff --git a/lab2/Rplots.pdf b/lab2/Rplots.pdf
deleted file mode 100644
index 7074237..0000000
--- a/lab2/Rplots.pdf
+++ /dev/null
Binary files differ
diff --git a/lab2/abc.Rdata b/lab2/abc.Rdata
deleted file mode 100644
index c40c2da..0000000
--- a/lab2/abc.Rdata
+++ /dev/null
Binary files differ
diff --git a/lab2/intro.r b/lab2/intro.r
deleted file mode 100755
index 037210e..0000000
--- a/lab2/intro.r
+++ /dev/null
@@ -1,48 +0,0 @@
-#!/usr/bin/env Rscript
-
-v <- c(1:10, seq(11, 20, by = 2))
-
-typeof(1)
-typeof(1L)
-typeof(v)
-typeof(as.integer(v))
-head(v)
-str(v)
-plot(v)
-
-
-save.image(file = "abc.Rdata")
-
-v <- seq(1, 10, by = 0.5)
-v
-
-load("abc.Rdata")
-
-v
-
-
-v <- c("a", "b", "c", "b", "a")
-
-f <- factor(v)
-
-func <- function(x, y = 0) {
- return((x * x) + y)
-}
-
-func(y = 3, 5)
-
-
-m <- matrix(c(1:6, 11:13), nrow = 3, ncol = 3, byrow = TRUE)
-m
-
-m[2:3, 1:2]
-
-df <- data.frame(a = c(1:5), b = c("a", "b", "c", "d", "e"))
-
-df$a
-df$b
-
-df[df$a > 2, ]
-
-
-q("no") \ No newline at end of file
diff --git a/lab2/main.r b/lab2/main.r
deleted file mode 100755
index f468363..0000000
--- a/lab2/main.r
+++ /dev/null
@@ -1,74 +0,0 @@
-#!/usr/bin/env Rscript
-
-zip_income <- read.table("zipIncome.txt", header = TRUE, sep = "|")
-
-names(zip_income) <- c("zipCode", "income")
-
-head(zip_income)
-tail(zip_income)
-
-overall_mean <- mean(zip_income$income)
-overall_median <- median(zip_income$income)
-
-summary(zip_income)
-
-cat("Mean income:", overall_mean, "\n")
-cat("Median income:", overall_median, "\n")
-
-
-dim(zip_income)
-names(zip_income)
-
-unique(zip_income$zipCode)
-
-colSums(is.na(zip_income))
-
-zip_income_clean <- na.omit(zip_income)
-
-colSums(is.na(zip_income_clean))
-
-zip_income$income[is.na(zip_income$income)] <- -100
-zip_income$zipCode[is.na(zip_income$zipCode)] <- 99
-write.table(zip_income,
- file = "zip_income_clean.txt", # output filename
- sep = "|",
- row.names = FALSE
-)
-
-s1 <- c(seq(1, 10, by=1), seq(16, 25, by=1))
-
-df <- data.frame(x = seq(1, 20), y = s1)
-
-print(df)
-plot(df)
-
-model <- lm(y ~ x, data = df)
-summary(model)
-
-plot(df$x, df$y)
-abline(model, col = "red")
-
-plot(density(zip_income$income))
-
-hist(zip_income$income)
-
-library(lattice)
-densityplot(zip_income$income)
-densityplot(log(zip_income$income))
-
-x <- rnorm(10)
-y <- rnorm(10,2)
-
-t.test(x, y)
-
-# ----------------------------------
-
-zip_income <- read.table("zipIncome.txt", header = TRUE, sep = "|")
-
-names(zip_income) <- c("zipCode", "income")
-
-model <- lm(income ~ factor(zipCode), data = zip_income)
-summary(model)
-
-plot(zip_income$zipCode, zip_income$income)
-abline(model, col = "red")