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+## Exercise 7
+
+# PART 1
+# Replicate the head function
+# define a variable with the file to return lines from
+# a variable representing the number of lines to be returned form the top of the indicted file
+
+setwd("/Users/johi/Desktop/Courses/Biocomputing/Biocomp_tutorial9/")
+
+get_head <- function(filename, num_rows) {
+  data <- read.table(file = filename, sep= ",", header = TRUE, stringsAsFactors = FALSE)
+  head_rows <- data[1:num_rows, ]
+  return(print(head_rows))
+}
+
+get_head("wages.csv", 10)
+
+# PART 2
+
+iris_data <- read.table(file = "iris.csv", sep= ",", header = TRUE, stringsAsFactors = FALSE)
+
+# Print the last 2 rows in the last 2 columns to the R terminal
+print(tail(iris_data[, (ncol(iris_data)-1):ncol(iris_data)], 2))
+
+# Get the number of observations for each species included in the data set
+nrow(iris_data[iris_data$Species == "setosa", ])
+nrow(iris_data[iris_data$Species == "versicolor", ])
+nrow(iris_data[iris_data$Species == "virginica", ])
+
+# Get rows with Sepal.Width > 3.5
+iris_data[iris_data$Sepal.Width > 3.5, ]
+
+# Write the data for the species setosa to a comma-delimited file named ‘setosa.csv’
+write.table(x = iris_data[iris_data$Species == "setosa", ], file = "setosa.csv", sep = ",", col.names = TRUE)
+
+# Calculate the mean, minimum, and maximum of Petal.Length for observations from virginica
+petal_len <- iris_data[iris_data$Species == "virginica", ][, "Petal.Length"]
+
+mean(petal_len)
+min(petal_len)
+max(petal_len)