# Create a matrix with 5 rows and three columns 
# named pokemons
# Feed the following data: 
# c(120, 100, 40, 50, 80, 36, 40, 10, 25, 30,
# 3, 1, 1, 1, 2)
# Leave the default byrow argument

pokemons = matrix(c(120, 100, 40, 50, 80, 36, 40, 10, 25, 30,
 3, 1, 1, 1, 2), nrow=5, ncol=3)

# Rename our row names as "Blastoise", "Moltres", "Pikachu", "Pidgey"
# and Charmeleon and our columns as "HP", "Level", "Stage"

dimnames(pokemons) = list(c("Blastoise", "Moltres", "Pikachu", "Pidgey","Charmeleon")
                    ,c("HP", "Level", "Stage"))
                    
# Create a new pokemon in a single row matrix - this pokemon should 
# be Dragonite with 150 HP, level 50 and stage 3 
# store it in an object named dragonite

# hint: don't forget the dimnames!

dragonite = matrix(c(150,50,3), nrow=1, ncol=3)
dimnames(dragonite)=list(c("Dragonite"),c("HP","Level","Stage"))

# Add dragonite to our pokemons matrix - 
# write the new object in a full_pokemons named 
# variable

# Hint: rbind might come in handy...

full_pokemons = rbind(pokemons,dragonite)
#full_pokemons

# Calculate the difference between Dragonite HP 
# and Pikachu HP - store it in an object named
# dif_hp 

dif_hp = (full_pokemons["Dragonite","HP"] - full_pokemons["Pikachu","HP"])
#dif_hp

# Create an object called attack_power where you multiply the HP by
# the level and the stage of each Pokemon in a new variable

attack_power = (full_pokemons[,"Level"]*full_pokemons[,"HP"]*full_pokemons[,"Stage"])
#attack_power

# Add the attack power to the full_pokemons matrix, store it in an object
# called full_pokemons_attack_pwr

# Hint: cbind might come in handy!

full_pokemons_attack_pwr = cbind(full_pokemons,attack_power)
#full_pokemons_attack_pwr

# Check which pokemons has the lowest attack power 
# store it in a variable called low_attack_pkmn

# Hint: which might come in handy!

low_attack_pkmn = which(full_pokemons_attack_pwr[,"attack_power"] == min(full_pokemons_attack_pwr[,"attack_power"]))
low_attack_pkmn

# Create the following matrix in R: 
# [1, 0, 0, 0]
# [0, 1, 0, 0]
# [0, 0, 1, 0]
# [0, 0, 0, 1]

# Store the object in a identity_matrix object 

identity_matrix = matrix(c(1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1), nrow=4, ncol=4)
#identity_matrix

# Create a matrix of 10 rows and 4 columns 
# called log_values with the logarithm 
# with the following vector as input: 
# 1:5 

# apply the logarithm to every element of the matrix

log_values = matrix(c(log(1:5)),nrow=10, ncol=4)

# Compute the dot product between identity_matrix 
# and log_values 

# Hint: One of the matrixes must come first in the 
# calculation!
# save the returning object in a dot_log object

dot_log = log_values%*%identity_matrix
dot_log