#
# Unit 8 - Data frames 
#
# Replacing values
#

# Loading data 
setwd("c:/R")
employees <- read.csv("employees.csv")
print(employees)

# Examine this questions: 
# Add 1000 to the salaries of all women. 


# If we need to replace one value 
# in a data frame 
employees <- read.csv("employees.csv")
print(employees[1,2])
# as usual, first row index, then column index
employees[1,2] <- 999
print(employees[1,2])
print(employees)

employees[1,c("SALARY")] <- 20000
print(employees[1,c("SALARY")])
print(employees)

# Replacing a column 
employees <- read.csv("employees.csv")
employees$ID <- 10:19
print(employees)

# Also possible 
# Note the comma. 
employees <- read.csv("employees.csv")
employees[,c("ID")] <- 15:24
print(employees)


# What if we specify a single replacing value? 
employees <- read.csv("employees.csv")
employees$SALARY <- 2000
print(employees)


# Replacing a row
employees <- read.csv("employees.csv")
print(employees)
employees[2,] <- c(7777, "Yasmin", "Lee", 2, 15, 1000.72)
print(employees)

# Keep an eye on 
# suitable lengths. 
employees <- read.csv("employees.csv")
print(employees)
employees[2,] <- 1:3
print(employees)

employees <- read.csv("employees.csv")
print(employees)
employees[2,] <- 1:5
print(employees)


# Back to replacing values in columns
employees <- read.csv("employees.csv")
employees$SALARY <- 20000
print(employees)


employees <- read.csv("employees.csv")
employees$SALARY <- 5 * 1000 
print(employees)

employees <- read.csv("employees.csv")
print(employees$SALARY)
employees$SALARY <- 2 * employees$SALARY
print(employees$SALARY)


# We can replace values in a column 
# by condition
# Notice: NO SORUPRISE HERE WHATSOEVER! 
# AND HOW WOULD WE DO THIS USING A FOR LOOP? 
employees <- read.csv("employees.csv")
print(employees)
employees$SALARY[employees$EDUC > 15] <- 20000 
print(employees)


# Also possible 
# Note the comma. 
employees <- read.csv("employees.csv")
employees[,c("SALARY")][employees$EDUC > 15] <- 20000 
print(employees)

# Would this work? 
employees <- read.csv("employees.csv")
employees[employees$EDUC > 15,c("SALARY")] <- 20000 
print(employees)


# Finally let us examine again the 
# questions which opened this lesson. 
# Add 1000 to the salaries of all women. 
employees <- read.csv("employees.csv")
print(employees[employees$GENDER == 2, c("SALARY")])
employees[employees$GENDER == 2, c("SALARY")] <- (employees[employees$GENDER == 2, c("SALARY")]
                                                  + 
                                                  1000) 
print(employees[employees$GENDER == 2, c("SALARY")])

# Now examine this code. 
# Defining these ranges of salaries:  
#     - (0,5000]      --- "A"
#     - (5000,10000]  --- "B"
#     - (10000,15000] --- "C"
#     - (15000,20000] --- "D"
#  Add 1000 to all women whose salaries 
#  is in ranges A and D.