1) R Basics 1.1) Arithmetics: +,-, *,^, %% 1.2) Data types 1.3) Vectors: names(), sum(), selection vector 1.4) Matrices: matrix(), colnames(), rownames(), dimnames(), cbind(), rbind(), matrix arithmetics 1.5) Factors: factor(), levels(), summary(), selection, comparison 1.6) DataFrames: head(), tail(), str(), summary(), data.frame(), selection, subset(), order(), 1.7) Lists: create list, slice list, concat list
2) R Intermediate 2.1) Relational Operators: ==, !=, >, <
For simple arithmetics use:
For matrix arithmetics use %*% or %/ % , else all elements are calculated and the arithmetic is not the usual matrix one.
Numerics : 4.5
Integers : 4
Boolean : TRUE, FALSE, T, F
Characters : 'this is a text', 'abc'
Vectors, Matrices, Factors and Lists are made using the basic data types.
To find the type of a variable use: class(variable_name)
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var <- 4.1
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class(var)
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myvec <- c(1,3,5.5); myvec
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Naming the vector by :
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names(myvec) <- c('a','b','c'); myvec
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Summing the elements of a vector:
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sum(myvec)
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Select a vector index:
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myvec[2] # counting starts from 1 not 0!
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myvec[c(1,2)] # multiple select
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myvec[1:2] # slicing
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myvec[c('a','b')] # by name
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Selection by vector comparison:
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poker_vector <- c(140, -50, 20, -120, 240);
selection <- poker_vector > 0;
selection
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winnings_vector <- poker_vector[selection]; winnings_vector
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matrix(1:9, byrow = TRUE, nrow =3) # byrow : fill by rows , nrow = # rows
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create a matrix using vectors:
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new_hope <- c(460.998, 314.4);
empire_strikes <- c(290.475, 247.900);
return_jedi <- c(309.306, 165.8);
star_wars_matrix = matrix(c(new_hope,empire_strikes,return_jedi), nrow=3,
byrow=TRUE);
star_wars_matrix
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Name your columns, rows
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colnames(star_wars_matrix) <- c("US", "non-US");
rownames(star_wars_matrix) <- c("A New Hope", "The Empire Strikes Back", "Return of the Jedi");
star_wars_matrix
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Summing rows and cols:
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colSums(star_wars_matrix)
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rowSums(star_wars_matrix)
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box_office_all <- c(461, 314.4, 290.5, 247.9, 309.3, 165.8);
movie_names <- c("A New Hope","The Empire Strikes Back","Return of the Jedi");
col_titles <- c("US","non-US")
#### NAME USING VECTOR NAMES
star_wars_matrix <- matrix(box_office_all, nrow = 3, byrow = TRUE,
dimnames = list(movie_names, col_titles));
star_wars_matrix
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Adding columns and rows : cbind(), rbind()
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worldwide_vector <- rowSums(star_wars_matrix);
all_wars_matrix <- cbind(star_wars_matrix, worldwide_vector)
all_wars_matrix
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box_office_2 <- c(474, 552, 310, 338, 380, 468);
movie_names_2 <- c("The Phantom Menace","Attack of the Clones","Revenge of the Sith");
col_titles_2 <- c("US","non-US")
star_wars_matrix_2 <- matrix(box_office_2, nrow = 3, byrow = TRUE,
dimnames = list(movie_names_2, col_titles_2));
star_wars_all <- rbind(star_wars_matrix,star_wars_matrix_2);
star_wars_all
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Selecting elements of matrix
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star_wars_all[1,2] #1st row, 2nd column
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star_wars_all[ ,2] # ALL rows from 2nd column
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star_wars_all[1, ] # 1st row, all columns
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star_wars_all[1:2,] #slicing
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mean(star_wars_all[1:2,])
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Arithmetics with matrices
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star_wars_all *2 # multiply all elements by 2
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gender_vector <- c("Male", "Female", "Female", "Male", "Male");
factor_gender_vector <- factor(gender_vector);
factor_gender_vector
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There are two types of categorical variables nominal and ordinal. You can use arguments in the factor function to define the levels of an ordinal variable.
For example:
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animals_vector <- c("Elephant", "Giraffe", "Donkey", "Horse")
temperature_vector <- c("High", "Low", "High","Low", "Medium")
factor_animals_vector <- factor(animals_vector)
factor_animals_vector
factor_temperature_vector <- factor(temperature_vector, order = TRUE, levels = c("Low", "Medium", "High"))
factor_temperature_vector
# in R terminal this shows also the levels :
# for the nominal it states: Levels: Donkey Elephant Giraffe Horse
# while for the ordinal : Levels: Low < Medium < High
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You can change the names of the levels by levels() function:
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survey_vector <- c("M", "F", "F", "M", "M")
factor_survey_vector <- factor(survey_vector)
factor_survey_vector
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but I want 'Male' and 'Female' !
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levels(factor_survey_vector) <- c('Female', 'Male')
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factor_survey_vector
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Summary of factors
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summary(survey_vector)
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summary(factor_survey_vector)
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Selection
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factor_survey_vector[1]
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factor_survey_vector[2]
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Comparison of factors
Comparison does not work for nominal factors, but works fine for ordinal!!
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factor_survey_vector[1]>factor_survey_vector[2] ## NA! Doesn't work for
## nominal factors!
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speed_vector <- c("Fast", "Slow", "Slow", "Fast", "Ultra-fast")
factor_speed_vector <- factor(speed_vector, ordered = TRUE,
levels = c("Slow", "Fast", "Ultra-fast"))
compare_them <- factor_speed_vector[2]>factor_speed_vector[5]
# Is data analyst 2 faster than data analyst 5?
compare_them
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mtcars; # dataframe included in R
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Quick look at dataframe head(), tail(), str() [structure]
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head(mtcars,2)
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tail(mtcars,4)
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str(mtcars) # means structure
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summary(mtcars) # returns summary statistics
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Creating a data.frame()
You can create a dataframe using simple vectors by calling the data.frame() function
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planets <- c("Mercury", "Venus", "Earth", "Mars", "Jupiter", "Saturn", "Uranus", "Neptune");
type <- c("Terrestrial planet", "Terrestrial planet", "Terrestrial planet", "Terrestrial planet", "Gas giant", "Gas giant", "Gas giant", "Gas giant")
diameter <- c(0.382, 0.949, 1, 0.532, 11.209, 9.449, 4.007, 3.883);
rotation <- c(58.64, -243.02, 1, 1.03, 0.41, 0.43, -0.72, 0.67);
rings <- c(FALSE, FALSE, FALSE, FALSE, TRUE, TRUE, TRUE, TRUE);
# Create the data frame:
planets_df <- data.frame(planets, type, diameter, rotation, rings)
planets_df # indexes the rows and names the columns by the name of vector
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Slicing a data frame
As with matrices you can use [1,2], [1, ], [1:3, ] etc
OR USE THE NAME OF THE COLUMN!!!
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planets_df[1:3,1]
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planets_df[3:8, "diameter"]
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planets_df$diameter # this returns a vector with the elements of the column
## similar to planets_df[ ,"diameter"]
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Selection of df entries using selector vector
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selection_rings <- planets_df$rings
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planets_with_rings <- planets_df[selection_rings, ] # all columns,
#rows with True
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planets_with_rings
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Subset()
Use the subset function to select entries from a df
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planets_with_rings_2 <- subset(planets_df, subset = rings == TRUE);
planets_with_rings_2
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Order
the order() function returns the hierarchical order in a vector:
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a<- c(100, 150, 101)
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order(a)
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This can be used in data frames. For example order the planet df with the largest planet in the top.
To do this use the order function with the decreasing = TRUE argument to make a vector and then pass it in the df :
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positions <- order(planets_df$diameter, decreasing=TRUE)
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largest_first_df <- planets_df[positions, ]
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largest_first_df
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In [149]:
vec <- 1:10;
mat <- matrix(1:9, byrow=TRUE, ncol=3)
mdf <- mtcars[1:10,]
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my_list <- list(vec, mat, mdf)
my_list
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Update the names(my_list) to name the object your list holds:
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names(my_list) <- c("vector", "matrix", "dataframe")
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my_list
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Select elements from list
To select from the list use the double bracket [[ ]]
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my_list[[1]] # returns the object 1 (ie the vector)
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my_list[[2]]
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my_list[[1]][2] #from the list the 1st object (vec),
# from that the 2nd element
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Append to list
To append an info in the list use the c() function. To also name the new item when concatinating use the syntax :
c(list, name=new_var)
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year <- 1980
my_list_2 <- c(my_list, myyear=year)
my_list_2
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3>5
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FALSE == TRUE
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FALSE < TRUE # TRUE = 1, FALSE = 0
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"Hello" > "Goodbye" # alphabetical order (G < H < I ...)
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For vectors:
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linkedin <- c (10,20,30,40,60)
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linkedin > 30
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facebook <- c(10,50,20,56) # check the warning
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linkedin<facebook
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