added day 1 script

Scripts/day1_20240916.R

@@ -0,0 +1,151 @@
+# this does not work, because read_tsv is not defined
+read_tsv("foo.bar")
+
+# load the library with read_tsv
+library("tidyverse")
+
+# this does not work, because the file is not there
+read_tsv("foo.bar")
+
+# this doesnt work, because iris.tsv is not in ExampleProject
+read_tsv("iris.tsv")
+
+# we use the TAB key
+read_tsv("../Datasets/iris.tsv")
+
+# yeah, but this did not do anything much
+# put the content of the file in a variable
+iris_ds <- read_tsv("../Datasets/iris.tsv")
+
+# achieving the same with two very different functions / commands
+plot(iris_ds$Sepal.Length, iris_ds$Sepal.Width)
+library(ggplot2)
+ggplot(iris_ds, aes(x = Sepal.Length, y = Sepal.Width)) + geom_point()
+
+
+
+# numeric vectors
+a <- 5
+b <- c(1.7, pi, 5, 10, 7e-3)
+
+# character vector
+myname <- "January"
+
+a <- a * 2
+
+b * 2
+b * a
+log10(b)
+b^a
+a + b
+
+myname * a
+
+# creating a vector containing a missing value (not available, NA)
+b <- c(1.7, pi, 5, 10, NA, 7e-3)
+b * 10
+
+# special value: Infinity, Inf
+weird <- 1/0
+
+# special value: minus infinity, -Inf
+weird * -1
+
+# special value: not a number (NaN)
+weird * 0
+0/0
+
+length(b)
+i <- length(b)
+i
+
+## the following doesn't work because we don't have foo and bar variables!
+t.test(foo, bar)
+
+res <- t.test(foo, bar)
+res$p.value
+
+1:5
+seq(1, 5)
+
+seq(1, 5, length.out = 10)
+?seq
+
+# exercise 1.3
+students <- c("Anna", "Bernie", "Claudia", "David")
+sel <- c(3, 2)
+
+students[3]
+students[2]
+# INCORRECT!
+students[3, 2]
+
+students[c(3, 2)]
+
+students[c(3, 3, 2, 3, 2)]
+# equivalent:
+sel <- c(3, 3, 2, 3, 2)
+students[sel]
+
+sel <- c(3, 2)
+students[sel]
+students[sel] <- c("Arthur",
+                   "Beate")
+
+# factors
+stu_f <- factor(students)
+stu_chr <- as.character(stu_f)
+as.numeric(stu_f)
+
+
+
+# example values for five samples
+samples   <- c(1, 10, 20, 21, 7, 5)
+samples_n <- length(samples)
+
+# calculate standard deviation of samples manually
+samples_mean <- mean(samples)
+samples_devs <- samples - samples_mean
+
+# samples variance
+samples_var  <- sum(samples_devs^2) / (samples_n - 1)
+
+# sd is sqrt(variance)
+samples_sd   <- sqrt(samples_var)
+
+# alternative: use the built-in function
+samples_sd <- sd(samples)
+
+
+# exercise 1.4
+
+days <- 1:10
+area_1 <- 0.01
+
+area <- area_1 * 2^(days - 1)
+
+# base R graphics
+plot(days, area, xlab="Days", ylab="Area in m²",
+     ylim=c(0, 1))
+abline(h=0.5)
+
+# ggplot graphics
+df <- data.frame(days = days, area = area)
+ggplot(df, aes(x = days, y = area)) + 
+  geom_point() +
+  geom_hline(yintercept =  0.5)
+
+
+days <- 1:10
+area_day_1 <- 0.01
+
+areas_double <- area_day_1 * 2^(days - 1)
+areas_one_and_a_half <- area_day_1 * 1.5^(days - 1)
+
+plot(days, areas_double, col="red", type="l", ylim = c(0, 1))
+lines(days, areas_one_and_a_half, col="blue")
+abline(h=0.5, col="grey")
+
+
+ls("package:ggplot2")
+