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% Packages
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\usepackage{seqsplit}           % Splits long words.
%\usepackage{opensans}          % Can't make this work so far. Shame. Would be lovely.
\usepackage[normalem]{ulem}     % For underlining links
% Most of the following are not required for the majority
% of cheat sheets but are needed for some symbol support.
\usepackage{amsmath}            % Symbols
\usepackage{MnSymbol}           % Symbols
\usepackage{wasysym}            % Symbols
%\usepackage[english,german,french,spanish,italian]{babel}              % Languages

% Document Info
\author{BarplotNorm}
\pdfinfo{
  /Title (r-commands.pdf)
  /Creator (Cheatography)
  /Author (BarplotNorm)
  /Subject (R Commands Cheat Sheet)
}

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% Commands
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% Header and Footer
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\fancyhead{} % Set header to blank
\fancyfoot{} % Set footer to blank
\fancyhead[L]{
\noindent
\begin{multicols}{3}
\begin{tabulary}{5.8cm}{C}
    \SetRowColor{DarkBackground}
    \vspace{-7pt}
    {\parbox{\dimexpr\textwidth-2\fboxsep\relax}{\noindent
        \hspace*{-6pt}\includegraphics[width=5.8cm]{/web/www.cheatography.com/public/images/cheatography_logo.pdf}}
    }
\end{tabulary}
\columnbreak
\begin{tabulary}{11cm}{L}
    \vspace{-2pt}\large{\bf{\textcolor{DarkBackground}{\textrm{R Commands Cheat Sheet}}}} \\
    \normalsize{by \textcolor{DarkBackground}{BarplotNorm} via \textcolor{DarkBackground}{\uline{cheatography.com/203294/cs/43288/}}}
\end{tabulary}
\end{multicols}}

\fancyfoot[L]{ \footnotesize
\noindent
\begin{multicols}{3}
\begin{tabulary}{5.8cm}{LL}
  \SetRowColor{FootBackground}
  \mymulticolumn{2}{p{5.377cm}}{\bf\textcolor{white}{Cheatographer}}  \\
  \vspace{-2pt}BarplotNorm \\
  \uline{cheatography.com/barplotnorm} \\
  \end{tabulary}
\vfill
\columnbreak
\begin{tabulary}{5.8cm}{L}
  \SetRowColor{FootBackground}
  \mymulticolumn{1}{p{5.377cm}}{\bf\textcolor{white}{Cheat Sheet}}  \\
   \vspace{-2pt}Not Yet Published.\\
   Updated 31st January, 2025.\\
   Page {\thepage} of \pageref{LastPage}.
\end{tabulary}
\vfill
\columnbreak
\begin{tabulary}{5.8cm}{L}
  \SetRowColor{FootBackground}
  \mymulticolumn{1}{p{5.377cm}}{\bf\textcolor{white}{Sponsor}}  \\
  \SetRowColor{white}
  \vspace{-5pt}
  %\includegraphics[width=48px,height=48px]{dave.jpeg}
  Measure your website readability!\\
  www.readability-score.com
\end{tabulary}
\end{multicols}}




\begin{document}
\raggedright
\raggedcolumns

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% from this page to resize cheat sheet text:
% www.emerson.emory.edu/services/latex/latex_169.html
\footnotesize % Small font.


\begin{tabularx}{17.67cm}{x{2.6352 cm} x{5.4351 cm} x{3.6234 cm} x{4.7763 cm} }
\SetRowColor{DarkBackground}
\mymulticolumn{4}{x{17.67cm}}{\bf\textcolor{white}{Basic Math}}  \tn
% Row 0
\SetRowColor{LightBackground}
\seqsplit{`exp(x)`} & Exponential & \seqsplit{`sum(x)`} & Sum \tn 
% Row Count 2 (+ 2)
% Row 1
\SetRowColor{white}
\seqsplit{`log(x)`} & Natural log & \seqsplit{`cumsum(x)`} & Cumulative Sum \tn 
% Row Count 4 (+ 2)
% Row 2
\SetRowColor{LightBackground}
\seqsplit{`max(x)`} & Largest element & \seqsplit{`ceil(x)`} & Round up \tn 
% Row Count 6 (+ 2)
% Row 3
\SetRowColor{white}
\seqsplit{`min(x)`} & Smallest element & \seqsplit{`floor(x)`} & Round down \tn 
% Row Count 8 (+ 2)
% Row 4
\SetRowColor{LightBackground}
`x \%\% y` & Modulo &  &  \tn 
% Row Count 10 (+ 2)
\hhline{>{\arrayrulecolor{DarkBackground}}----}
\end{tabularx}
\par\addvspace{1.3em}

\begin{tabularx}{17.67cm}{x{8.635 cm} x{8.635 cm} }
\SetRowColor{DarkBackground}
\mymulticolumn{2}{x{17.67cm}}{\bf\textcolor{white}{Control Flow}}  \tn
% Row 0
\SetRowColor{LightBackground}
`for (variable in sequence) \{...\}` & for-loop. If the loop body contains only a single line, the curly brackets can be omitted. \tn 
% Row Count 5 (+ 5)
% Row 1
\SetRowColor{white}
`while (condition) \{...\}` & while-loop \tn 
% Row Count 7 (+ 2)
% Row 2
\SetRowColor{LightBackground}
`if (i \textgreater{} 5) \{`\{\{nl\}\}`  ...`\{\{nl\}\} `else \{`\{\{nl\}\}`  ...`\{\{nl\}\}`\}` & if-else-block \tn 
% Row Count 11 (+ 4)
% Row 3
\SetRowColor{white}
`foo = function(arg1, arg2, ...) \{`\{\{nl\}\}`  ...`\{\{nl\}\}`  return(var)`\{\{nl\}\}`\}` & function \tn 
% Row Count 15 (+ 4)
\hhline{>{\arrayrulecolor{DarkBackground}}--}
\end{tabularx}
\par\addvspace{1.3em}

\begin{tabularx}{17.67cm}{x{6.5626 cm} x{10.7074 cm} }
\SetRowColor{DarkBackground}
\mymulticolumn{2}{x{17.67cm}}{\bf\textcolor{white}{Vectors}}  \tn
% Row 0
\SetRowColor{LightBackground}
\mymulticolumn{2}{x{17.67cm}}{{\bf{Creating Vectors}}} \tn 
% Row Count 1 (+ 1)
% Row 1
\SetRowColor{white}
`c(2, 4, 6)` & Join elements into a vector \tn 
% Row Count 3 (+ 2)
% Row 2
\SetRowColor{LightBackground}
`2:6` & An integer sequence (end inclusive!) \tn 
% Row Count 5 (+ 2)
% Row 3
\SetRowColor{white}
`seq(2,3, by=0.5)` & Complex sequence (s. np.linspace) \tn 
% Row Count 7 (+ 2)
% Row 4
\SetRowColor{LightBackground}
`rep(1:2, 3)` & Repeat vector \tn 
% Row Count 8 (+ 1)
% Row 5
\SetRowColor{white}
`rep(1:2, 3:4)` & Repeat each element \tn 
% Row Count 9 (+ 1)
% Row 6
\SetRowColor{LightBackground}
\mymulticolumn{2}{x{17.67cm}}{{\bf{Functions}}} \tn 
% Row Count 10 (+ 1)
% Row 7
\SetRowColor{white}
`sort(x)` & Return x sorted. \tn 
% Row Count 11 (+ 1)
% Row 8
\SetRowColor{LightBackground}
`rev(x)` & Return x reversed. \tn 
% Row Count 12 (+ 1)
% Row 9
\SetRowColor{white}
`unique(x)` & See unique values. \tn 
% Row Count 13 (+ 1)
% Row 10
\SetRowColor{LightBackground}
`length(x)` & Length of x. \tn 
% Row Count 14 (+ 1)
% Row 11
\SetRowColor{white}
\mymulticolumn{2}{x{17.67cm}}{{\bf{Selecting Vector Elements}}} \tn 
% Row Count 15 (+ 1)
% Row 12
\SetRowColor{LightBackground}
\mymulticolumn{2}{x{17.67cm}}{{\emph{By Position}}} \tn 
% Row Count 16 (+ 1)
% Row 13
\SetRowColor{white}
`x{[}4{]}` & The fourth element \tn 
% Row Count 17 (+ 1)
% Row 14
\SetRowColor{LightBackground}
`x{[}-4{]}` & All but the fourth. \tn 
% Row Count 18 (+ 1)
% Row 15
\SetRowColor{white}
`x{[}2:4{]}` & Elements two to four \tn 
% Row Count 19 (+ 1)
% Row 16
\SetRowColor{LightBackground}
`x{[}-(2:4){]}` & All elements except 2 to four \tn 
% Row Count 21 (+ 2)
% Row 17
\SetRowColor{white}
`x{[}c(1, 5){]}` & Elements one and five. \tn 
% Row Count 22 (+ 1)
% Row 18
\SetRowColor{LightBackground}
\mymulticolumn{2}{x{17.67cm}}{{\emph{By Value}}} \tn 
% Row Count 23 (+ 1)
% Row 19
\SetRowColor{white}
`x{[}x == 10{]}` & All elements equal to 10 \tn 
% Row Count 24 (+ 1)
% Row 20
\SetRowColor{LightBackground}
`x{[}x  \textless{} 10{]}` & All elements less than 10. \tn 
% Row Count 26 (+ 2)
% Row 21
\SetRowColor{white}
`x{[}x \%in\% c(1, 2, 5){]}` & Elements in the given set. \tn 
% Row Count 28 (+ 2)
% Row 22
\SetRowColor{LightBackground}
\mymulticolumn{2}{x{17.67cm}}{{\emph{Named Vectors}}} \tn 
% Row Count 29 (+ 1)
% Row 23
\SetRowColor{white}
`x{[}'apple'{]}` & Element with name 'apple'. \tn 
% Row Count 31 (+ 2)
\hhline{>{\arrayrulecolor{DarkBackground}}--}
\end{tabularx}
\par\addvspace{1.3em}

\begin{tabularx}{17.67cm}{x{7.7715 cm} x{9.4985 cm} }
\SetRowColor{DarkBackground}
\mymulticolumn{2}{x{17.67cm}}{\bf\textcolor{white}{Tables}}  \tn
% Row 0
\SetRowColor{LightBackground}
`table(data)` & get absolute frequencies of values \tn 
% Row Count 2 (+ 2)
% Row 1
\SetRowColor{white}
`as.numeric(tab); as.vector(tab)` & Extract values and their absolute frequencies from table \tn 
% Row Count 5 (+ 3)
% Row 2
\SetRowColor{LightBackground}
\seqsplit{`tab/length(data)`} & Compute relative frequencies \tn 
% Row Count 7 (+ 2)
\hhline{>{\arrayrulecolor{DarkBackground}}--}
\end{tabularx}
\par\addvspace{1.3em}

\begin{tabularx}{17.67cm}{x{9.1531 cm} x{8.1169 cm} }
\SetRowColor{DarkBackground}
\mymulticolumn{2}{x{17.67cm}}{\bf\textcolor{white}{Matrices}}  \tn
% Row 0
\SetRowColor{LightBackground}
`m = matrix(x, nrow = 3, ncol = 3)` & Create a matrix from vector `x` \tn 
% Row Count 2 (+ 2)
% Row 1
\SetRowColor{white}
`t(m)` & transpose \tn 
% Row Count 3 (+ 1)
% Row 2
\SetRowColor{LightBackground}
`m \%*\% n` & Matrix multiplication \tn 
% Row Count 5 (+ 2)
% Row 3
\SetRowColor{white}
`solve(m, n)` & Find x in `m * x = n` \tn 
% Row Count 7 (+ 2)
% Row 4
\SetRowColor{LightBackground}
`det(m)` & Determinant \tn 
% Row Count 8 (+ 1)
% Row 5
\SetRowColor{white}
`eigen(m)` & Find eigen vectors and values \tn 
% Row Count 10 (+ 2)
\hhline{>{\arrayrulecolor{DarkBackground}}--}
\end{tabularx}
\par\addvspace{1.3em}

\begin{tabularx}{17.67cm}{x{8.635 cm} x{8.635 cm} }
\SetRowColor{DarkBackground}
\mymulticolumn{2}{x{17.67cm}}{\bf\textcolor{white}{Data sets}}  \tn
% Row 0
\SetRowColor{LightBackground}
\seqsplit{Data=data.frame(price=c(11},20,14,15), number=c(40,50,60,20)) & Create a data set \tn 
% Row Count 3 (+ 3)
% Row 1
\SetRowColor{white}
\mymulticolumn{2}{x{17.67cm}}{{\bf{Interacting with data sets}}} \tn 
% Row Count 4 (+ 1)
% Row 2
\SetRowColor{LightBackground}
`col\_1 = data\$col\_1\_name` & Access column data \tn 
% Row Count 6 (+ 2)
% Row 3
\SetRowColor{white}
`Data{[}1,2{]}; Data{[},2{]}; Data{[}{[}1{]}{]}` & Access data with index notation \tn 
% Row Count 8 (+ 2)
% Row 4
\SetRowColor{LightBackground}
\mymulticolumn{2}{x{17.67cm}}{{\bf{I/O}}} \tn 
% Row Count 9 (+ 1)
% Row 5
\SetRowColor{white}
`data = read.csv("file.csv", header=FALSE, sep="")` & Read csv (function arguments similar to that used in pandas) \tn 
% Row Count 12 (+ 3)
% Row 6
\SetRowColor{LightBackground}
`write.csv(data, "data.csv", row.names=FALSE, sep=" ")` & Write data set as csv \tn 
% Row Count 15 (+ 3)
% Row 7
\SetRowColor{white}
\mymulticolumn{2}{x{17.67cm}}{{\bf{Filter}}} \tn 
% Row Count 16 (+ 1)
% Row 8
\SetRowColor{LightBackground}
`df{[}df\$kids == "Jack",{]}` & Filter data frame \tn 
% Row Count 18 (+ 2)
% Row 9
\SetRowColor{white}
`subset(df,  kids== "John" \& Grade == 1.3)` & Filter multiple columns \tn 
% Row Count 21 (+ 3)
% Row 10
\SetRowColor{LightBackground}
`subset(df, kids \%in\% c("Jack", "John"))` & Filter a column with multiple values \tn 
% Row Count 24 (+ 3)
% Row 11
\SetRowColor{white}
`unique(housing{[}, c("State", "region"){]})` & Extract unique rows \tn 
% Row Count 27 (+ 3)
% Row 12
\SetRowColor{LightBackground}
\mymulticolumn{2}{x{17.67cm}}{{\bf{Sort}}} \tn 
% Row Count 28 (+ 1)
% Row 13
\SetRowColor{white}
`housing{[}order(housing\$Home.Value), {]}` & Order data frame in ascending order \tn 
% Row Count 30 (+ 2)
\end{tabularx}
\par\addvspace{1.3em}

\begin{tabularx}{17.67cm}{x{8.635 cm} x{8.635 cm} }
\SetRowColor{DarkBackground}
\mymulticolumn{2}{x{17.67cm}}{\bf\textcolor{white}{Data sets (cont)}}  \tn
% Row 14
\SetRowColor{LightBackground}
`housing{[}order(housing\$Home.Value, decreasing = TRUE), {]}` & order data frame in descending order \tn 
% Row Count 3 (+ 3)
% Row 15
\SetRowColor{white}
\mymulticolumn{2}{x{17.67cm}}{{\bf{Meta}}} \tn 
% Row Count 4 (+ 1)
% Row 16
\SetRowColor{LightBackground}
`dim(df)` & Check the dimensions of a data frame \tn 
% Row Count 6 (+ 2)
% Row 17
\SetRowColor{white}
`colnames(d)` & Return the column names \tn 
% Row Count 8 (+ 2)
% Row 18
\SetRowColor{LightBackground}
\mymulticolumn{2}{x{17.67cm}}{{\bf{Manipulate data}}} \tn 
% Row Count 9 (+ 1)
% Row 19
\SetRowColor{white}
`Data\_Frame\_New \textless{}- Data\_Frame{[}-c(1), -c(1){]}` & Remove columns and/or rows from data frame \tn 
% Row Count 12 (+ 3)
% Row 20
\SetRowColor{LightBackground}
`rbdind(df\_1, df\_2)` & Combine data frames vertically \tn 
% Row Count 14 (+ 2)
\hhline{>{\arrayrulecolor{DarkBackground}}--}
\end{tabularx}
\par\addvspace{1.3em}

\begin{tabularx}{17.67cm}{x{8.9804 cm} x{8.2896 cm} }
\SetRowColor{DarkBackground}
\mymulticolumn{2}{x{17.67cm}}{\bf\textcolor{white}{I/O}}  \tn
% Row 0
\SetRowColor{LightBackground}
`write(data, "mydata.dat")` & Write data as binary. \tn 
% Row Count 2 (+ 2)
% Row 1
\SetRowColor{white}
\seqsplit{`scan("mydata.dat")`} & Read binary data. \tn 
% Row Count 3 (+ 1)
% Row 2
\SetRowColor{LightBackground}
`getcwd()` & Current working directory \tn 
% Row Count 5 (+ 2)
\hhline{>{\arrayrulecolor{DarkBackground}}--}
\end{tabularx}
\par\addvspace{1.3em}

\begin{tabularx}{17.67cm}{x{8.635 cm} x{8.635 cm} }
\SetRowColor{DarkBackground}
\mymulticolumn{2}{x{17.67cm}}{\bf\textcolor{white}{Random Numbers}}  \tn
% Row 0
\SetRowColor{LightBackground}
`sample(1:3,prob=c(1/6,1/3,1/2),replace=TRUE,20)` & Draw 20 balls, labeled from 1 to 3, from box with replacement. \tn 
% Row Count 4 (+ 4)
% Row 1
\SetRowColor{white}
`r\textless{}distr. ID\textgreater{}`(n, params) & Draw `n` numbers from distribution `\textless{}distr. ID\textgreater{}` with parameters `params` \tn 
% Row Count 8 (+ 4)
% Row 2
\SetRowColor{LightBackground}
\mymulticolumn{2}{x{17.67cm}}{{\emph{(see {\bf{Distributions in R}} for more details)}}} \tn 
% Row Count 9 (+ 1)
\hhline{>{\arrayrulecolor{DarkBackground}}--}
\end{tabularx}
\par\addvspace{1.3em}

\begin{tabularx}{17.67cm}{x{5.8718 cm} x{11.3982 cm} }
\SetRowColor{DarkBackground}
\mymulticolumn{2}{x{17.67cm}}{\bf\textcolor{white}{Characteristics of data sequences}}  \tn
% Row 0
\SetRowColor{LightBackground}
`mean(x)` & Arithmetic mean of the data sequence \tn 
% Row Count 2 (+ 2)
% Row 1
\SetRowColor{white}
`var(x)` & Variance \tn 
% Row Count 3 (+ 1)
% Row 2
\SetRowColor{LightBackground}
`median(x)` & Median \tn 
% Row Count 4 (+ 1)
% Row 3
\SetRowColor{white}
`quantile(x, type=7)` & Quantile. `type=7` is the default computation algorithm, i.e. the function returns the value at position `k=1+p(n-1)`, if this is an integer. Otherwise, R computes a weighted mean of the two neighboring integers \tn 
% Row Count 13 (+ 9)
% Row 4
\SetRowColor{LightBackground}
`quantile(x, type=1)` & General inverse function of the ECDF (smallest p-quantile). Largetst p-quantile can be obtained indirectly by slightly increasing p \tn 
% Row Count 19 (+ 6)
% Row 5
\SetRowColor{white}
`summary(x)` & Overview of important measures \tn 
% Row Count 21 (+ 2)
% Row 6
\SetRowColor{LightBackground}
`cov(x,y)` & Covariance \tn 
% Row Count 22 (+ 1)
% Row 7
\SetRowColor{white}
`cor(x,y)` & Correlation \tn 
% Row Count 23 (+ 1)
\hhline{>{\arrayrulecolor{DarkBackground}}--}
\end{tabularx}
\par\addvspace{1.3em}

\begin{tabularx}{17.67cm}{x{7.0807 cm} x{10.1893 cm} }
\SetRowColor{DarkBackground}
\mymulticolumn{2}{x{17.67cm}}{\bf\textcolor{white}{Distributions in R}}  \tn
% Row 0
\SetRowColor{LightBackground}
\mymulticolumn{2}{x{17.67cm}}{{\bf{General usage}}} \tn 
% Row Count 1 (+ 1)
% Row 1
\SetRowColor{white}
`d\textless{}distr. ID\textgreater{}(params)` & density function \tn 
% Row Count 3 (+ 2)
% Row 2
\SetRowColor{LightBackground}
`q\textless{}distr. ID\textgreater{}(params)` & quantile function. Always computes the smallest quantile \tn 
% Row Count 6 (+ 3)
% Row 3
\SetRowColor{white}
`p\textless{}distr. ID\textgreater{}(params)` & cumulative distribution function \tn 
% Row Count 8 (+ 2)
% Row 4
\SetRowColor{LightBackground}
`r\textless{}distr. ID\textgreater{}(params)` & random variate generation \tn 
% Row Count 10 (+ 2)
% Row 5
\SetRowColor{white}
\mymulticolumn{2}{x{17.67cm}}{{\bf{Distributions}}} \tn 
% Row Count 11 (+ 1)
% Row 6
\SetRowColor{LightBackground}
`dbinom(x, size=p, prob=p)` & Binomial \tn 
% Row Count 13 (+ 2)
% Row 7
\SetRowColor{white}
`dchisq(x, df, ncp=0)` & Chi-squared \tn 
% Row Count 15 (+ 2)
% Row 8
\SetRowColor{LightBackground}
`dexp(x, rate=1)` & Exponential \tn 
% Row Count 17 (+ 2)
% Row 9
\SetRowColor{white}
`dgamma(x, shape=r, rate=l)` & Gamma \tn 
% Row Count 19 (+ 2)
% Row 10
\SetRowColor{LightBackground}
`dgeom(x, prob=p)` & Geometric \tn 
% Row Count 21 (+ 2)
% Row 11
\SetRowColor{white}
`dnbinom(x, size, prob)` & Negative binomial \tn 
% Row Count 23 (+ 2)
% Row 12
\SetRowColor{LightBackground}
`dnorm(x, mean=0, sd=1)` & Normal \tn 
% Row Count 25 (+ 2)
% Row 13
\SetRowColor{white}
`dpois(x, lambda)` & Poisson \tn 
% Row Count 27 (+ 2)
% Row 14
\SetRowColor{LightBackground}
`dt(x, df, ncp)` & t-distribution \tn 
% Row Count 28 (+ 1)
% Row 15
\SetRowColor{white}
`dunif(x, min=0, max=1)` & Uniform \tn 
% Row Count 30 (+ 2)
\hhline{>{\arrayrulecolor{DarkBackground}}--}
\end{tabularx}
\par\addvspace{1.3em}

\begin{tabularx}{17.67cm}{x{8.635 cm} x{8.635 cm} }
\SetRowColor{DarkBackground}
\mymulticolumn{2}{x{17.67cm}}{\bf\textcolor{white}{Plotting}}  \tn
% Row 0
\SetRowColor{LightBackground}
\mymulticolumn{2}{x{17.67cm}}{{\bf{Basic plots}}} \tn 
% Row Count 1 (+ 1)
% Row 1
\SetRowColor{white}
`plot(data)` & Plot quick overview. \tn 
% Row Count 2 (+ 1)
% Row 2
\SetRowColor{LightBackground}
`plot(x, y, xlab="mu", ylab="Power", type="l", col="red", ylim=c(0,1), lwd=1.5)` & Plot data with custom style options \tn 
% Row Count 6 (+ 4)
% Row 3
\SetRowColor{white}
\mymulticolumn{2}{x{17.67cm}}{{\bf{Lines and curves}}} \tn 
% Row Count 7 (+ 1)
% Row 4
\SetRowColor{LightBackground}
`abline(a,b,col="red")` & Add a red line with intercept `a` and slope `b` to the plot. \tn 
% Row Count 10 (+ 3)
% Row 5
\SetRowColor{white}
`abline(v=a,col="red")` & add vertical line at `x=a` \tn 
% Row Count 12 (+ 2)
% Row 6
\SetRowColor{LightBackground}
`abline(h=b,col="red")` & add horizontal line at `y=b` \tn 
% Row Count 14 (+ 2)
% Row 7
\SetRowColor{white}
`lines(x, y, col="green", lwd=1.5)` & Add a generic line \tn 
% Row Count 16 (+ 2)
% Row 8
\SetRowColor{LightBackground}
`curve(sin,-pi,pi,add=TRUE)` & Draw a curve of a function over the specified interval \tn 
% Row Count 19 (+ 3)
% Row 9
\SetRowColor{white}
\mymulticolumn{2}{x{17.67cm}}{{\bf{Data visualization}}} \tn 
% Row Count 20 (+ 1)
% Row 10
\SetRowColor{LightBackground}
`plot.ecdf(data)` & Plot ECDF. \tn 
% Row Count 21 (+ 1)
% Row 11
\SetRowColor{white}
`barplot(x, main="Title", xlab="x label")` & Annotated barplot of absolute frequencies \tn 
% Row Count 24 (+ 3)
% Row 12
\SetRowColor{LightBackground}
`hist(data, prob=TRUE, breaks=30)` & Histogram of relative frequencies (30 bins). \tn 
% Row Count 27 (+ 3)
% Row 13
\SetRowColor{white}
`rug(data)` & 1D-plot \tn 
% Row Count 28 (+ 1)
% Row 14
\SetRowColor{LightBackground}
`boxplot(data1, data2, ... ,range=1.5)` & Plot boxplots of one or more data sequences in one window. `range` determines the extend of the whiskers. Default `range=1.5`, i.e. 1.5 x IQR \tn 
% Row Count 36 (+ 8)
\end{tabularx}
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\begin{tabularx}{17.67cm}{x{8.635 cm} x{8.635 cm} }
\SetRowColor{DarkBackground}
\mymulticolumn{2}{x{17.67cm}}{\bf\textcolor{white}{Plotting (cont)}}  \tn
% Row 15
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`qqnorm(x)` & QQ-Plot against standard normal distribution \tn 
% Row Count 3 (+ 3)
% Row 16
\SetRowColor{white}
`qqPlot(x, dist="unif",...)` & QQ-Plot against any R-standard distribution. Additional arguments such as `df`, `ncp` can also be specified. \tn 
% Row Count 9 (+ 6)
% Row 17
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`legend(x,y, legend=c("n=10"),col=c("red"), lty=1, cex=0.8)` & Add legend to plot as position `(x,y)` \tn 
% Row Count 12 (+ 3)
\hhline{>{\arrayrulecolor{DarkBackground}}--}
\end{tabularx}
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\begin{tabularx}{17.67cm}{x{8.635 cm} x{8.635 cm} }
\SetRowColor{DarkBackground}
\mymulticolumn{2}{x{17.67cm}}{\bf\textcolor{white}{Statistical hypothesis testing}}  \tn
% Row 0
\SetRowColor{LightBackground}
\mymulticolumn{2}{x{17.67cm}}{{\bf{One-Sample tests}}} \tn 
% Row Count 1 (+ 1)
% Row 1
\SetRowColor{white}
`t.test(x,mu=mu0,alt="less", \seqsplit{conf.level=1-alpha)`} & Performs one and two sample t-tests on vectors of data. \tn 
% Row Count 4 (+ 3)
% Row 2
\SetRowColor{LightBackground}
`power.t.test(n = 100, delta=0.1, sd=2, sig.level=0.1, type="one.sample", alt="one.sided")` & Compute the power of the one- or two- sample t test, or determine parameters to obtain a target power. \tn 
% Row Count 10 (+ 6)
% Row 3
\SetRowColor{white}
`binom.test(sum(x),n,p0,alt="greater", \seqsplit{conf.level=1-alpha)`} & Performs an exact test of a simple null hypothesis about the probability of success in a Bernoulli experiment. It might happen that the decision based on the p-value differs from that of the confidence interval. Choose the decision based on the p-value in such cases. \tn 
% Row Count 24 (+ 14)
% Row 4
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\mymulticolumn{2}{x{17.67cm}}{{\bf{Two-Sample tests}}} \tn 
% Row Count 25 (+ 1)
% Row 5
\SetRowColor{white}
`t.test(shoes\$A,shoes\$B,paired=FALSE, var.equal=TRUE)` & Example for an unpaired sample t-test \tn 
% Row Count 28 (+ 3)
% Row 6
\SetRowColor{LightBackground}
`var.test(x,y,conf.level=1-alpha)` & Performs an F test to compare the variances of two samples from normal populations. \tn 
% Row Count 33 (+ 5)
\end{tabularx}
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\begin{tabularx}{17.67cm}{x{8.635 cm} x{8.635 cm} }
\SetRowColor{DarkBackground}
\mymulticolumn{2}{x{17.67cm}}{\bf\textcolor{white}{Statistical hypothesis testing (cont)}}  \tn
% Row 7
\SetRowColor{LightBackground}
\mymulticolumn{2}{x{17.67cm}}{{\bf{GOF tests}}} \tn 
% Row Count 1 (+ 1)
% Row 8
\SetRowColor{white}
`shapiro.test(x)` & Performs the Shapiro-Wilk test of normality. \tn 
% Row Count 4 (+ 3)
% Row 9
\SetRowColor{LightBackground}
\seqsplit{`chisq.test(table(x)}, p=p\_0)` & Test for distribution with probabilities `p\_0`. If `p` is  not specified, R tests for a uniform distribution \tn 
% Row Count 10 (+ 6)
% Row 10
\SetRowColor{white}
\seqsplit{`chisq.test(table(x)}, p=p\_0, \seqsplit{simulate.p.value=TRUE)`} & Do not use Chi\textasciicircum{}2\textasciicircum{}-approximation to calculate the p-value \tn 
% Row Count 13 (+ 3)
% Row 11
\SetRowColor{LightBackground}
\seqsplit{`pwr.chisq.test(w=ncp}, df=s-1, sig.level=alpha, power=0.9)` & Determine the number of samples needed to reach the desired power at the given significance level \tn 
% Row Count 18 (+ 5)
% Row 12
\SetRowColor{white}
`ks.test(x, "pnorm", 0, 1)` & One-sample Kolmogorov-Smirnov test against hypothetical distribution \tn 
% Row Count 22 (+ 4)
% Row 13
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`lillie.test(x)` & Lilliefors \seqsplit{(Kolmogorov-Smirnov)} test for the composite hypothesis of normality \tn 
% Row Count 26 (+ 4)
% Row 14
\SetRowColor{white}
\mymulticolumn{2}{x{17.67cm}}{{\bf{Tests of independence}}} \tn 
% Row Count 27 (+ 1)
% Row 15
\SetRowColor{LightBackground}
`chisq.test(M)` & Chi\textasciicircum{}2\textasciicircum{}-test of independence. M hast to be a matrix! (contingency table) \tn 
% Row Count 31 (+ 4)
\end{tabularx}
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\begin{tabularx}{17.67cm}{x{8.635 cm} x{8.635 cm} }
\SetRowColor{DarkBackground}
\mymulticolumn{2}{x{17.67cm}}{\bf\textcolor{white}{Statistical hypothesis testing (cont)}}  \tn
% Row 16
\SetRowColor{LightBackground}
`fisher.test(M)` & Exact test of Fisher. If the table entries are too large, use \seqsplit{`simulate.p.value=TRUE`} \tn 
% Row Count 5 (+ 5)
% Row 17
\SetRowColor{white}
`runs.test(x)` & Runs test of independence. `x` hast to be a factor (use `as.factor()` if necessary) \tn 
% Row Count 10 (+ 5)
\hhline{>{\arrayrulecolor{DarkBackground}}--}
\end{tabularx}
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\begin{tabularx}{17.67cm}{x{5.0083 cm} x{12.2617 cm} }
\SetRowColor{DarkBackground}
\mymulticolumn{2}{x{17.67cm}}{\bf\textcolor{white}{Runs Test of Randomness}}  \tn
% Row 0
\SetRowColor{LightBackground}
`rle(x)` & Compute the lengths and values of runs of equal values in a vector . \tn 
% Row Count 3 (+ 3)
% Row 1
\SetRowColor{white}
\seqsplit{`rle(x)\$lengths`} & Vector containing the length of each run. \tn 
% Row Count 5 (+ 2)
% Row 2
\SetRowColor{LightBackground}
\seqsplit{`rle(x)\$values`} & Vector of the same length as lengths with the corresponding values. \tn 
% Row Count 8 (+ 3)
\hhline{>{\arrayrulecolor{DarkBackground}}--}
\end{tabularx}
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\begin{tabularx}{17.67cm}{x{8.635 cm} x{8.635 cm} }
\SetRowColor{DarkBackground}
\mymulticolumn{2}{x{17.67cm}}{\bf\textcolor{white}{Optimization}}  \tn
% Row 0
\SetRowColor{LightBackground}
`nlm(E2,0.5)` & Carries out a minimization of the function f using a Newton-type algorithm. May not give all solutions. The function must be vectorized \tn 
% Row Count 7 (+ 7)
% Row 1
\SetRowColor{white}
`E2vec=Vectorize(E2, \seqsplit{vectorize.args=c("n"))`} & vectorize a function. `vectorize.args`: explicitly state arguments to be vectorized. \tn 
% Row Count 12 (+ 5)
% Row 2
\SetRowColor{LightBackground}
\mymulticolumn{2}{x{17.67cm}}{{\bf{Distribution Fit}}} \tn 
% Row Count 13 (+ 1)
% Row 3
\SetRowColor{white}
`fitdistr(x, "Poisson")` & Maximum-likelihood fitting of univariate distributions, allowing parameters to be held fixed if desired. (`library(MASS)`) \tn 
% Row Count 20 (+ 7)
% Row 4
\SetRowColor{LightBackground}
\mymulticolumn{2}{x{17.67cm}}{{\bf{Regression}}} \tn 
% Row Count 21 (+ 1)
% Row 5
\SetRowColor{white}
`reg=lm(x\textasciitilde{}t)` & Fit a linear function `x=a+bt` \tn 
% Row Count 23 (+ 2)
% Row 6
\SetRowColor{LightBackground}
`summary(reg)` & Obtain further information about regression result \{\{nl\}\}{\bf{Important fields:}}\{\{nl\}\}- Residual standard error: sd of residuals (with normalization {\bf{`n-2`}}) \{\{nl\}\}-t value: Test null hypothesis "estimate is 0" with assumption of a normally distributed random mechanism\{\{nl\}\}-multiple R-squared: squared corr. coef. Null hypothesis r\textasciicircum{}2\textasciicircum{}=0 is tested with F-statistic \tn 
% Row Count 42 (+ 19)
\end{tabularx}
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\begin{tabularx}{17.67cm}{x{8.635 cm} x{8.635 cm} }
\SetRowColor{DarkBackground}
\mymulticolumn{2}{x{17.67cm}}{\bf\textcolor{white}{Optimization (cont)}}  \tn
% Row 7
\SetRowColor{LightBackground}
`reg=lm(x \textasciitilde{} t+ I(t\textasciicircum{}2))` & Fit a polynomial function. `I()`inhibits R from interpreting `t\textasciicircum{}2` as a formula \tn 
% Row Count 4 (+ 4)
% Row 8
\SetRowColor{white}
`form=x \textasciitilde{} \seqsplit{a/(1+exp(-b*(t-c)))`} \{\{nl\}\} `reg=nls(form, data=USPop, start=c(a=400,b=0.02,c=2000))` & perform non-linear least-squares regression \tn 
% Row Count 9 (+ 5)
% Row 9
\SetRowColor{LightBackground}
`plot(t,predict(reg))` & Plot regression result \tn 
% Row Count 11 (+ 2)
% Row 10
\SetRowColor{white}
\mymulticolumn{2}{x{17.67cm}}{{\bf{Root finding}}} \tn 
% Row Count 12 (+ 1)
% Row 11
\SetRowColor{LightBackground}
`res = uniroot(func, c(0,10))` & Searches interval for a root of the function `func`. `res\$root` and `res\$f.root` give the location of the root and the value of the function \tn 
% Row Count 19 (+ 7)
\hhline{>{\arrayrulecolor{DarkBackground}}--}
\end{tabularx}
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\begin{tabularx}{17.67cm}{x{2.5905 cm} x{14.6795 cm} }
\SetRowColor{DarkBackground}
\mymulticolumn{2}{x{17.67cm}}{\bf\textcolor{white}{Help}}  \tn
% Row 0
\SetRowColor{LightBackground}
\seqsplit{`?sqrt`} & Display documentation of the command `sqrt`` \tn 
% Row Count 2 (+ 2)
% Row 1
\SetRowColor{white}
\seqsplit{`?'\%\%'`} & use quotation marks for special characters \tn 
% Row Count 4 (+ 2)
\hhline{>{\arrayrulecolor{DarkBackground}}--}
\end{tabularx}
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\begin{tabularx}{17.67cm}{x{8.635 cm} x{8.635 cm} }
\SetRowColor{DarkBackground}
\mymulticolumn{2}{x{17.67cm}}{\bf\textcolor{white}{Miscellaneous}}  \tn
% Row 0
\SetRowColor{LightBackground}
\mymulticolumn{2}{x{17.67cm}}{{\bf{Printing}}} \tn 
% Row Count 1 (+ 1)
% Row 1
\SetRowColor{white}
`print("Text")` & Default print \tn 
% Row Count 2 (+ 1)
% Row 2
\SetRowColor{LightBackground}
`sprintf("Formatted \%s: \%.3f", object, mean)` & Formatted print \tn 
% Row Count 5 (+ 3)
% Row 3
\SetRowColor{white}
`(x=3)` & enclose an R command with brackets to directly print the result \tn 
% Row Count 9 (+ 4)
% Row 4
\SetRowColor{LightBackground}
`edit(x)` & Invoke text editor on R object \tn 
% Row Count 11 (+ 2)
% Row 5
\SetRowColor{white}
\mymulticolumn{2}{x{17.67cm}}{{\bf{Libraries}}} \tn 
% Row Count 12 (+ 1)
% Row 6
\SetRowColor{LightBackground}
`library(MASS)` & Load package MASS \tn 
% Row Count 13 (+ 1)
% Row 7
\SetRowColor{white}
`uniroot(f, interval)` & find 1D root \tn 
% Row Count 15 (+ 2)
% Row 8
\SetRowColor{LightBackground}
\mymulticolumn{2}{x{17.67cm}}{{\bf{Step functions}}} \tn 
% Row Count 16 (+ 1)
% Row 9
\SetRowColor{white}
`stepfunc(x,y)` & Given the vectors (x\textasciitilde{}1\textasciitilde{}, ...,x\textasciitilde{}n\textasciitilde{}) and (y\textasciitilde{}0\textasciitilde{},...,y\textasciitilde{}n\textasciitilde{}) (one value more!), returns an interpolating 'step' function \tn 
% Row Count 22 (+ 6)
% Row 10
\SetRowColor{LightBackground}
`knots(x)` & returns jump positions of stepfunction \tn 
% Row Count 24 (+ 2)
\hhline{>{\arrayrulecolor{DarkBackground}}--}
\end{tabularx}
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\end{document}