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Summary FULL GUIDE - Programming with R
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All functions required for the workbooks and assignments clearly explained in one document! The order of the document is sorted per week.
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Praktische informatie programmeren met RImport data
Make sure the data is in a .csv file and put it in a dataframe:
df1 <- read.csv("C:/Users/Jeroen/Downloads/Rstudio/Module 3/students1.csv",
stringsAsFactors = FALSE)
NOTE: R uses / in the path, not the Windows OS default \
Useful keyboard shortcuts (first Windows, then Mac):
- Als je iets niet kunt vinden, check Stackoverflow
- Alleen code in de editor, linksboven wordt opgeslagen.
- Namen van Objects/Variables kunnen niet beginnen met een cijfer. 1fruit kan niet.
fruit2 wel.
- Objects kunnen gemaakt worden op twee manieren
- x=12
- x <- 12
- Check what objects are stored in the environment by using
ls()
- Remove your objects by using
rm()
- Short key voor het pijltje is Alt + - (minus teken)
- Data types for objects:
, - Characters/Strings,
- Characters maak je net als in Python met “ “
- Doubles (int/float)
- Boolean (True/Flase)
- Een True statement maak je met X <- 2 == 2
- Een False statement maak je met X <- 2 == 3
- Factor: this data type is for categorial data: Left / Right, Male / Female, VWO,
HAVO, MAVO.
- When you add character vectors to a data frame, they are
automatically converted into factors!. Unless.. you use:
stringAsFactor = FALSE
- The categories in a factor vector are often referred to as levels
- Op deze pagina vind je veel cheat sheets voor programmeren met R
- Als je data wilt importeren, moet je / gebruiken in de path specification ipv de default
\ op Windows OS.
- Je kunt de geïmporteerde df1 en df2 combineren onder de objectnaam ‘students’
dmv het volgende commando:
students <- rbind(df1, df2)
- Als je wilt bekijken welke data types er in de dataset zitten, kun je een kijkje
nemen met het volgende commando: str(students)
- Je kunt kijken naar de dataset structure doormiddel van het volgende commando:
head(students). Hiermee krijg je de eerste 5 regels te zien.
- Vectors: is een set sequence van data elementen met hetzelfde data type
- List/generic vectors: is een set sequence van data elementen met die verschillende
data types kan bevatten.
Functions
- Functions with ‘...’ arguments (= components of a function) in them can take in any
data type and or additional input without claiming an error.
- C-function: combines/concatenates homogeneous data elements into a vector:
friend_names <- c("Bertha", "Herbert", "Alice", "Nathaniel")
- if you combine heterogeneous data types into a vector, it will convert
them to the most reasonable data type, often that is character.
However, if there are no characters in the vector, it will turn to
numeric → booleans become 1 and 0.
- Class-function: To see what data types are in a certain vector you can use
class(friend_names)
- Als je ‘L’ achter de numeric values zet in een vector, dan kun je van float values,
numeric/int values maken
- Je kunt ook vectors maken met een vaste interval doormiddel van de sequence
functie: dec_frac_seq <- seq(from = 10, to = 3, by = -0.2)
- Als de je stappen van 1 wilt, dan kun je ook het volgende commando met de
‘:’ gebruiken: seq <- 28:112
- ‘by’ indiceert de grootte van de stappen in de sequence.
- Met mean(variabel_x) kun je het gemiddelde van een functie zoals een vector of een
sequence berekenen.
- Net als in Excel zijn gebruikt R vergelijkbare termen voor fucnties:
, - sum(ages_numeric)
- min(ages_numeric)
- Smallest value in de vector/sequence
- max(ages_numeric)
- Largest value in de vector/sequence
- prod(ages_numeric)
- Product of the vector/sequence
- median(ages_numeric)
- abs(ages_numeric)
- Absolute values of a vector/sequence
- sqrt(ages_numeric)
- Square root
- round(variable_x, digits = 2)
- round the data elements in the vector to 2 digits
- cos, sin, tan, log, expontential
- cos(ages_numeric)
- sin(ages_numeric)
- tan(ages_numeric)
- log(ages_numeric)
- exp(ages_numeric)
- Indexing can be done in vectors via two ways. Either counting from 0 from
the start [25, 35, 42] OR similarly from the back with a minus sign [-3, -6, -
10]
my_vector[28] → index nr 29 from the e.g. 100 data elements
my_vector[-1] → index nr 99 from the e.g. 100 data elements → 100, 99, 98
…
- If you want to select certain letters from string u can use subtract
Substr(“stringx”, start = 2, stop = 4)
- If you want to replace certain letters from a string use the chartr() function
chartr("r", "R", bird_name) → “raven” now becomes “Raven”
- You can capitalize the whole string by using the toupper()
toupper(bird_name) → RAVEN
- Combine vectors into a table/matrix
- rbind(friend_names, weight_numeric) → combine rows
- cbind(friend_names, weight_numeric) → combine collumns
- Combine vectors into a data frame by using the Data frame function. It is
important to specify each vector to a column/variable in the data frame.
- friends <- data.frame(names = friend_names, ages = friend_ages,
stringsAsFactors = FALSE)
- When you add character vectors to a data frame, they are
automatically converted into factors!. Unless.. you use:
stringAsFactor = FALSE
- This means you can only add data elements to de factor vector
that are identical to one of the existing levels (= categories).
- If you try to replace/add a non-identical data element it
will result in an N/A
, - Combine vectors into a list
- friends_list <- list(names = friend_names, ages = friend_ages)
- Check number of rows or# columns in a matrix/df
- nrow(matrix)
- ncol(matrix)
- Check the length of a vector: length(friend_names)
- Check for missing values with
is.na(friend_names)
- Omit/remove missing values
na.omit(friend_names)
- You can also perform operations on vectors, for example adding 5 (years)
to each data element in the vectore ages_numeric
- ages_numeric
five_years_older <- ages_numeric + 5L
- Als je een specifiek deel van één kolom/variabele uit je data frame wilt
pakken, gebruik je ‘$’ om de kollom/variabele te selecteren en ‘[10:20]’ om de
gewenste rijen te selecteren
- students$DataYear[10:20]
- If you want to index the whole vector that makes up the column in the
data frame or list/vector in a list, you can also use ‘[[ ]]’ OR type the name
of the column in [“ “]
students[[2]] → show the 2nd column/variable in the data
frame ‘students’
students[“DataYear”] → shows the vector
- Wil je een specifiek deel van meerdere kolommen in combinatie met
meerdere rijen pakken, dan gebruik je de ‘ , ‘ tussen de gewenste rijen en
kolommen. Zie hier wederom het gebruik van c-functie om de kolommen aan
te geven.
- students[21:30, c(2, 4, 5)]
- Selecting a specific part/subset of you vector. kun je de volgende twee
commandos uitvoeren. Zie wederom het gebruik van de c-functie hier. Maar
nu binnen de [ ]
- friend_names[c(1, 3)] → selecteer data element 1 en 3
- friend_names[-c(1, 3)] → selecteer alles, behalve data element 1 en
3 met het ‘-’ teken
- Replace a specific subset in your data frame
- my_df$fruits[3] <- "a new fruit"
- OR adjust the whole vector
my_df$fruits <- c(“apple”, “bannana”, “raspberry”)
- Replacing factor columns needs to be done a little different. First you
convert the column/variable into characters, then you adjust them. If you want
them to change back to levels, you can use the factor() function
- my_df$fruits <- as.character(my_df$fruits)
my_df$fruits[1] <- "raspberry"
factor(my_df$fruits)
- Delete a column from a data frame by selecting the column and setting the
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