# 01_Open_R



# The window that holds this file is the editor.
## Here you can create command files - like do files in STATA

# The window below is the console.
## There you will see the code and the answer as it is executed. 

# The window on the top right shows the data objects. 
## currently this should be empty, but if you type a = matrix(1,2,3), or b = 3 you can see these objects.

# The bottom right window shows file resources, packages, help files and Plots. 



# lets return to the console (bottom window), if you haven't done so type:
a = matrix(1,3,3)
b=3
# look at the object in the console by directly calling it.
b
a


# now click on a
# => it opens in the editor, you will have to close it or return to this file.
# => This is how you can browse data objects. 

# to run code from the file you have to highlight it and hit the "=>Run" button on top. Try this on the next line:
c= b*a

# this is also how you can run multiple commands such as:
d= a
e= d*c
f= a-e
dim(f)

# sometimes we want functions that are not loaded
g= inv(c)
# ups error-message: a package is missing. (I googled it: its "matlib")
# to install a new package, 
## 0.) if you don't know the name of the package you need, tell google what you want to do "in r", e.g. "machine learning in R" 
## 1.) Once you know the name of the package go to the resources window and find "packages." 
## 2.) If the package is not there click "install" and search for the package: e.g. "matlib"
## 3.) hit install. 
## 4.) now matlib will apear in the list of installed packages and you can click on it to load it.



# alternatively the following lines do the same:
install.packages("matlib")
library(matlib)

#ok, now back to our inverse:
g= inv(c)
# hmm, are these now our matrix algebra limitations? Let's try this:
h= matrix(c(1, 2, 3, 2, 4, 5, 3, 4, 6), nrow=3, ncol=3)
i= inv(h)
j = h*i
## any guess what j might be?
## use %*% for matrix multiplication
l= h%*%i


## Lastly, Random Number.m
m= runif(1)
## and random vectors
n= runif(12)

## Random Number between 1 and 100
o<- sample(1:100, 1)
o
p<- sample(1:100, 7)
p


















## you can run code directly from the console