# Load the gdata package
library(gdata)
library(readxl)
# Import the spreadsheet: att
at<-read_excel("attendance.xls")
att<-read.xls("attendance.xls")

# Print the column names
colnames(att)

# Print the first 6 rows
head(att,n=6)

# Print the last 6 rows
tail(att,n=6)

# Print the structure
str(att)
dim(att)

# Create remove
remove<-c(3,56:59)

# Create att2
att2<-att[-remove,]

# Create remove
remove<-c(3,5,7,9,11,13,15,17)

# Create att3
att3<-att2[,-remove]

library(dplyr)
# Subset just elementary schools: att_elem
att_elem<-att3[,c(1,6,7)]

# Subset just secondary schools: att_sec
att_sec<-att3[,c(1,8,9)]

# Subset all schools: att4
att4<-att3[,c(1:5)]

# Define cnames vector
cnames <- c("state", "avg_attend_pct", "avg_hr_per_day", "avg_day_per_yr", "avg_hr_per_yr")

# Assign column names of att4
colnames(att4) <- cnames

# Remove first two rows of att4: att5
att5<-att4[-c(1,2),]

# View the names of att5
colnames(att5)

glimpse(att5)

# Remove all periods in state column
att5$state<-str_replace_all(att5$state,"\\.","")

# Remove white space around state names
att5$state<-str_trim(att5$state)

# View the head of att5
head(att5)

# Change columns to numeric using dplyr
example <- mutate_each(att5, funs(as.numeric), -state)

# Define vector containing numerical columns: cols

# Change columns to numeric using dplyr
dim(att5)
i<-c(1:5)
cols<-c(2:5)
# Use sapply to coerce cols to numeric
att5[, cols] <- sapply(att5[,cols],as.numeric)