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\author{Niki (worlddoit)}
\pdfinfo{
  /Title (r-ml-library.pdf)
  /Creator (Cheatography)
  /Author (Niki (worlddoit))
  /Subject (r ml library Cheat Sheet)
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\noindent
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    {\parbox{\dimexpr\textwidth-2\fboxsep\relax}{\noindent
        \hspace*{-6pt}\includegraphics[width=5.8cm]{/web/www.cheatography.com/public/images/cheatography_logo.pdf}}
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\begin{tabulary}{11cm}{L}
    \vspace{-2pt}\large{\bf{\textcolor{DarkBackground}{\textrm{r ml library Cheat Sheet}}}} \\
    \normalsize{by \textcolor{DarkBackground}{Niki (worlddoit)} via \textcolor{DarkBackground}{\uline{cheatography.com/170195/cs/36005/}}}
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\noindent
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  \mymulticolumn{2}{p{5.377cm}}{\bf\textcolor{white}{Cheatographer}}  \\
  \vspace{-2pt}Niki (worlddoit) \\
  \uline{cheatography.com/worlddoit} \\
  \end{tabulary}
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  \mymulticolumn{1}{p{5.377cm}}{\bf\textcolor{white}{Cheat Sheet}}  \\
   \vspace{-2pt}Not Yet Published.\\
   Updated 11th December, 2022.\\
   Page {\thepage} of \pageref{LastPage}.
\end{tabulary}
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  \mymulticolumn{1}{p{5.377cm}}{\bf\textcolor{white}{Sponsor}}  \\
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  \vspace{-5pt}
  %\includegraphics[width=48px,height=48px]{dave.jpeg}
  Measure your website readability!\\
  www.readability-score.com
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\begin{multicols*}{3}

\begin{tabularx}{5.377cm}{X}
\SetRowColor{DarkBackground}
\mymulticolumn{1}{x{5.377cm}}{\bf\textcolor{white}{Intro}}  \tn
\SetRowColor{white}
\mymulticolumn{1}{x{5.377cm}}{Additional material about top libraries for Machine Learning in R.% Row Count 2 (+ 2)
} \tn 
\hhline{>{\arrayrulecolor{DarkBackground}}-}
\SetRowColor{LightBackground}
\mymulticolumn{1}{x{5.377cm}}{(**Basics)}  \tn 
\hhline{>{\arrayrulecolor{DarkBackground}}-}
\end{tabularx}
\par\addvspace{1.3em}

\begin{tabularx}{5.377cm}{X}
\SetRowColor{DarkBackground}
\mymulticolumn{1}{x{5.377cm}}{\bf\textcolor{white}{1. XML}}  \tn
\SetRowColor{white}
\mymulticolumn{1}{x{5.377cm}}{{\bf{You can read a xml file in R using the "XML" package.}} \newline % Row Count 2 (+ 2)
`install.packages("XML")`\{\{noshy\}\} \newline % Row Count 3 (+ 1)
`\# Also load the other required package.`\{\{noshy\}\} \newline % Row Count 5 (+ 2)
`library("methods")`\{\{noshy\}\} \newline % Row Count 6 (+ 1)
`\# Give the input file name to the function.`\{\{noshy\}\} \newline % Row Count 8 (+ 2)
`result \textless{}- xmlParse(file = "input.xml")`\{\{noshy\}\} \newline % Row Count 9 (+ 1)
`\# Exract the root node form the xml file.`\{\{noshy\}\} \newline % Row Count 11 (+ 2)
`rootnode \textless{}- xmlRoot(result)`\{\{noshy\}\} \newline % Row Count 12 (+ 1)
`\# Find number of nodes in the root.`\{\{noshy\}\} \newline % Row Count 13 (+ 1)
`rootsize \textless{}- xmlSize(rootnode)`\{\{noshy\}\}% Row Count 14 (+ 1)
} \tn 
\hhline{>{\arrayrulecolor{DarkBackground}}-}
\SetRowColor{LightBackground}
\mymulticolumn{1}{x{5.377cm}}{(*Additional) Resources: \{\{popup="https://www.r-bloggers.com/2021/04/15-essential-packages-in-r-for-data-science/"\}\}1\{\{/popup\}\}, \{\{popup="https://www.tutorialspoint.com/r/r\_xml\_files.htm"\}\}2\{\{/popup\}\}}  \tn 
\hhline{>{\arrayrulecolor{DarkBackground}}-}
\end{tabularx}
\par\addvspace{1.3em}

\begin{tabularx}{5.377cm}{X}
\SetRowColor{DarkBackground}
\mymulticolumn{1}{x{5.377cm}}{\bf\textcolor{white}{2. dplyr}}  \tn
\SetRowColor{white}
\mymulticolumn{1}{x{5.377cm}}{{\bf{dplyr}} is a grammar of data manipulation, providing a consistent set of verbs that help you solve the most common data manipulation challenges: \newline % Row Count 3 (+ 3)
`mutate()` \{\{noshy\}\} adds new variables that are functions of existing variables \newline % Row Count 5 (+ 2)
`select()` \{\{noshy\}\} picks variables based on their names. \newline % Row Count 7 (+ 2)
`filter()` \{\{noshy\}\} picks cases based on their values. \newline % Row Count 9 (+ 2)
`summarise()` \{\{noshy\}\} reduces multiple values down to a single summary. \newline % Row Count 11 (+ 2)
`arrange()` changes the ordering of the rows. \newline % Row Count 12 (+ 1)
These all combine naturally with `group\_by()` \{\{noshy\}\} which allows you to perform any operation "by group".  \newline % Row Count 15 (+ 3)
Example: \newline % Row Count 16 (+ 1)
`starwars \%\textgreater{}\%`\{\{noshy\}\} \newline % Row Count 17 (+ 1)
`  group\_by(species) \%\textgreater{}\%`\{\{noshy\}\} \newline % Row Count 18 (+ 1)
`  summarise( n = n(),  mass = mean(mass, na.rm = TRUE)`\{\{noshy\}\} \newline % Row Count 20 (+ 2)
`  ) \%\textgreater{}\%`\{\{noshy\}\} \newline % Row Count 21 (+ 1)
`  filter( n \textgreater{} 1, mass \textgreater{} 50)`\{\{noshy\}\}% Row Count 22 (+ 1)
} \tn 
\hhline{>{\arrayrulecolor{DarkBackground}}-}
\SetRowColor{LightBackground}
\mymulticolumn{1}{x{5.377cm}}{(*Additional) Resources: \{\{popup="https://www.r-bloggers.com/2021/04/15-essential-packages-in-r-for-data-science/"\}\}1\{\{/popup\}\}, \{\{popup="https://dplyr.tidyverse.org/"\}\}2\{\{/popup\}\}}  \tn 
\hhline{>{\arrayrulecolor{DarkBackground}}-}
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\par\addvspace{1.3em}

\begin{tabularx}{5.377cm}{X}
\SetRowColor{DarkBackground}
\mymulticolumn{1}{x{5.377cm}}{\bf\textcolor{white}{3. xgboost}}  \tn
\SetRowColor{white}
\mymulticolumn{1}{x{5.377cm}}{`library(xgboost)`\{\{noshy\}\} \newline % Row Count 1 (+ 1)
`\# load data`\{\{noshy\}\} \newline % Row Count 2 (+ 1)
`data(agaricus.train, package = 'xgboost')`\{\{noshy\}\} \newline % Row Count 4 (+ 2)
`data(agaricus.test, package = 'xgboost')`\{\{noshy\}\} \newline % Row Count 6 (+ 2)
`train \textless{}- agaricus.train`\{\{noshy\}\} \newline % Row Count 7 (+ 1)
`test \textless{}- agaricus.test`\{\{noshy\}\} \newline % Row Count 8 (+ 1)
`\# fit model`\{\{noshy\}\} \newline % Row Count 9 (+ 1)
`bst \textless{}- xgboost(data = train\$data, label = train\$label, max\_depth = 2, eta = 1, nrounds = 2, `\{\{noshy\}\} \newline % Row Count 12 (+ 3)
`               nthread = 2, objective = "binary:logistic")`\{\{noshy\}\} \newline % Row Count 14 (+ 2)
`\# predict`\{\{noshy\}\} \newline % Row Count 15 (+ 1)
`pred \textless{}- predict(bst, test\$data)`\{\{noshy\}\}% Row Count 16 (+ 1)
} \tn 
\hhline{>{\arrayrulecolor{DarkBackground}}-}
\SetRowColor{LightBackground}
\mymulticolumn{1}{x{5.377cm}}{(*Additional) Resources: \{\{popup="https://www.r-bloggers.com/2021/04/15-essential-packages-in-r-for-data-science/"\}\}1\{\{/popup\}\}, \{\{popup="https://xgboost.ai/about"\}\}2\{\{/popup\}\}}  \tn 
\hhline{>{\arrayrulecolor{DarkBackground}}-}
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\begin{tabularx}{5.377cm}{X}
\SetRowColor{DarkBackground}
\mymulticolumn{1}{x{5.377cm}}{\bf\textcolor{white}{4. mlr3}}  \tn
\SetRowColor{white}
\mymulticolumn{1}{x{5.377cm}}{Lots of functionality, you can deal with clustering, regression, classification, and survival analysis. \newline % Row Count 3 (+ 3)
`library(mlr3)`\{\{noshy\}\} \newline % Row Count 4 (+ 1)
`\# create learning task`\{\{noshy\}\} \newline % Row Count 5 (+ 1)
`task\_penguins = \seqsplit{as\_task\_classif(species} \textasciitilde{} ., data = palmerpenguins::penguins)`\{\{noshy\}\} \newline % Row Count 7 (+ 2)
`\# load learner and set hyperparameter`\{\{noshy\}\} \newline % Row Count 8 (+ 1)
`learner = lrn("classif.rpart", cp = .01)`\{\{noshy\}\} \newline % Row Count 10 (+ 2)
`\# train/test split`\{\{noshy\}\} \newline % Row Count 11 (+ 1)
`split = partition(task\_penguins, ratio = 0.67)`\{\{noshy\}\} \newline % Row Count 13 (+ 2)
`\# train the model`\{\{noshy\}\} \newline % Row Count 14 (+ 1)
\seqsplit{`learner\$train(task\_penguins}, split\$train\_set)`\{\{noshy\}\} \newline % Row Count 16 (+ 2)
`\# predict data`\{\{noshy\}\} \newline % Row Count 17 (+ 1)
`prediction = \seqsplit{learner\$predict(task\_penguins}, split\$test\_set)`\{\{noshy\}\} \newline % Row Count 19 (+ 2)
`\# calculate performance`\{\{noshy\}\} \newline % Row Count 20 (+ 1)
`prediction\$confusion`\{\{noshy\}\} \newline % Row Count 21 (+ 1)
`measure = msr("classif.acc")`\{\{noshy\}\} \newline % Row Count 22 (+ 1)
`prediction\$score(measure)`\{\{noshy\}\} \newline % Row Count 23 (+ 1)
`\# 3-fold cross validation`\{\{noshy\}\} \newline % Row Count 24 (+ 1)
`resampling = rsmp("cv", folds = 3L)`\{\{noshy\}\} \newline % Row Count 25 (+ 1)
`\# run experiments`\{\{noshy\}\} \newline % Row Count 26 (+ 1)
`rr = resample(task\_penguins, learner, resampling)`\{\{noshy\}\} \newline % Row Count 28 (+ 2)
`\# access results`\{\{noshy\}\} \newline % Row Count 29 (+ 1)
`rr\$score(measure){[}, .(task\_id, learner\_id, iteration, classif.acc){]}`\{\{noshy\}\} \newline % Row Count 31 (+ 2)
} \tn 
\end{tabularx}
\par\addvspace{1.3em}

\vfill
\columnbreak
\begin{tabularx}{5.377cm}{X}
\SetRowColor{DarkBackground}
\mymulticolumn{1}{x{5.377cm}}{\bf\textcolor{white}{4. mlr3 (cont)}}  \tn
\SetRowColor{white}
\mymulticolumn{1}{x{5.377cm}}{`rr\$aggregate(measure)`\{\{noshy\}\}% Row Count 1 (+ 1)
} \tn 
\hhline{>{\arrayrulecolor{DarkBackground}}-}
\SetRowColor{LightBackground}
\mymulticolumn{1}{x{5.377cm}}{(*Additional) Resources: \{\{popup="https://www.r-bloggers.com/2021/04/15-essential-packages-in-r-for-data-science/"\}\}1\{\{/popup\}\}, \{\{popup="https://mlr3.mlr-org.com/"\}\}2\{\{/popup\}\}, \{\{popup="https://cran.r-project.org/web/packages/mlr3/mlr3.pdf"\}\}3\{\{/popup\}\}}  \tn 
\hhline{>{\arrayrulecolor{DarkBackground}}-}
\end{tabularx}
\par\addvspace{1.3em}

\begin{tabularx}{5.377cm}{X}
\SetRowColor{DarkBackground}
\mymulticolumn{1}{x{5.377cm}}{\bf\textcolor{white}{4. mlr3 additional}}  \tn
\SetRowColor{LightBackground}
\mymulticolumn{1}{p{5.377cm}}{\vspace{1px}\centerline{\includegraphics[width=5.1cm]{/web/www.cheatography.com/public/uploads/worlddoit_1670702500_ экрана 2022-12-10 в 21.01.23.png}}} \tn 
\hhline{>{\arrayrulecolor{DarkBackground}}-}
\SetRowColor{LightBackground}
\mymulticolumn{1}{x{5.377cm}}{(*Additional)}  \tn 
\hhline{>{\arrayrulecolor{DarkBackground}}-}
\end{tabularx}
\par\addvspace{1.3em}

\begin{tabularx}{5.377cm}{X}
\SetRowColor{DarkBackground}
\mymulticolumn{1}{x{5.377cm}}{\bf\textcolor{white}{5. knitr}}  \tn
\SetRowColor{white}
\mymulticolumn{1}{x{5.377cm}}{It is reproducible, used for report creation, and integrates with various types of code structures like LaTeX, HTML, Markdown, LyX, etc. \newline % Row Count 3 (+ 3)
This package is an amazing one, you can make a beautiful pdf report and editable pdf forms with the help of latex coding. \newline % Row Count 6 (+ 3)
`kable`\{\{noshy\}\} \newline % Row Count 7 (+ 1)
`xtable`\{\{noshy\}\} \newline % Row Count 8 (+ 1)
`tikzDevice`\{\{noshy\}\}% Row Count 9 (+ 1)
} \tn 
\hhline{>{\arrayrulecolor{DarkBackground}}-}
\SetRowColor{LightBackground}
\mymulticolumn{1}{x{5.377cm}}{(*Additional) Resources: \{\{popup="https://www.r-bloggers.com/2021/04/15-essential-packages-in-r-for-data-science/"\}\}1\{\{/popup\}\}, \{\{popup="https://sachsmc.github.io/knit-git-markr-guide/knitr/knit.html"\}\}2\{\{/popup\}\}}  \tn 
\hhline{>{\arrayrulecolor{DarkBackground}}-}
\end{tabularx}
\par\addvspace{1.3em}

\begin{tabularx}{5.377cm}{X}
\SetRowColor{DarkBackground}
\mymulticolumn{1}{x{5.377cm}}{\bf\textcolor{white}{6. plotly}}  \tn
\SetRowColor{white}
\mymulticolumn{1}{x{5.377cm}}{Plotly's R graphing library makes interactive, publication-quality graphs. Example of how to make line plots, scatter plots, area charts, bar charts, error bars, box plots, histograms, heatmaps, subplots, multiple-axes, and 3D (WebGL based) charts. \newline % Row Count 5 (+ 5)
`library(plotly)`\{\{noshy\}\} \newline % Row Count 6 (+ 1)
`\# volcano is a numeric matrix that ships with R`\{\{noshy\}\} \newline % Row Count 8 (+ 2)
`fig \textless{}- plot\_ly(z = \textasciitilde{}volcano) \%\textgreater{}\% add\_surface(`\{\{noshy\}\} \newline % Row Count 10 (+ 2)
`  contours = list(`\{\{noshy\}\} \newline % Row Count 11 (+ 1)
`    z = list( show=TRUE, usecolormap=TRUE,`\{\{noshy\}\} \newline % Row Count 13 (+ 2)
`      \seqsplit{highlightcolor="\#ff0000"}, project=list(z=TRUE) ) ) )`\{\{noshy\}\} \newline % Row Count 15 (+ 2)
`fig \textless{}- fig \%\textgreater{}\% layout(`\{\{noshy\}\} \newline % Row Count 16 (+ 1)
`    scene = list( camera= list(`\{\{noshy\}\} \newline % Row Count 17 (+ 1)
`        eye = list(x=1.87, y=0.88, z=-0.64) )))`\{\{noshy\}\} \newline % Row Count 19 (+ 2)
`fig`\{\{noshy\}\}% Row Count 20 (+ 1)
} \tn 
\hhline{>{\arrayrulecolor{DarkBackground}}-}
\SetRowColor{LightBackground}
\mymulticolumn{1}{x{5.377cm}}{(*Additional) Resources: \{\{popup="https://plotly.com/r/"\}\}1\{\{/popup\}\}, \{\{popup="https://plotly-r.com/"\}\}2\{\{/popup\}\}, \{\{popup="https://www.r-bloggers.com/2021/04/15-essential-packages-in-r-for-data-science/"\}\}3\{\{/popup\}\}}  \tn 
\hhline{>{\arrayrulecolor{DarkBackground}}-}
\end{tabularx}
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\begin{tabularx}{5.377cm}{X}
\SetRowColor{DarkBackground}
\mymulticolumn{1}{x{5.377cm}}{\bf\textcolor{white}{6. plotly: Output}}  \tn
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\mymulticolumn{1}{p{5.377cm}}{\vspace{1px}\centerline{\includegraphics[width=5.1cm]{/web/www.cheatography.com/public/uploads/worlddoit_1670748653_ экрана 2022-12-11 в 9.09.34.png}}} \tn 
\hhline{>{\arrayrulecolor{DarkBackground}}-}
\SetRowColor{LightBackground}
\mymulticolumn{1}{x{5.377cm}}{(*Additional)}  \tn 
\hhline{>{\arrayrulecolor{DarkBackground}}-}
\end{tabularx}
\par\addvspace{1.3em}

\begin{tabularx}{5.377cm}{X}
\SetRowColor{DarkBackground}
\mymulticolumn{1}{x{5.377cm}}{\bf\textcolor{white}{7.  e1071}}  \tn
\SetRowColor{white}
\mymulticolumn{1}{x{5.377cm}}{Dealing with clustering, Fourier Transform, Naive Bayes, SVM, and other types of modeling data analysis then you can't avoid e1071. \newline % Row Count 3 (+ 3)
Example: \newline % Row Count 4 (+ 1)
`\#Author DataFlair`\{\{noshy\}\} \newline % Row Count 5 (+ 1)
`library("e1071")`\{\{noshy\}\} \newline % Row Count 6 (+ 1)
`data("iris")`\{\{noshy\}\} \newline % Row Count 7 (+ 1)
`head(iris)`\{\{noshy\}\} \newline % Row Count 8 (+ 1)
`x \textless{}- iris{[},-5{]}`\{\{noshy\}\} \newline % Row Count 9 (+ 1)
`y \textless{}- iris{[}5{]}`\{\{noshy\}\} \newline % Row Count 10 (+ 1)
`model\_svm \textless{}- svm(Species \textasciitilde{} ., data=iris)`\{\{noshy\}\} \newline % Row Count 12 (+ 2)
`summary(svm\_model)`\{\{noshy\}\} \newline % Row Count 13 (+ 1)
`pred \textless{}- predict(model\_svm,x)`\{\{noshy\}\} \newline % Row Count 14 (+ 1)
`confusionMatrix(pred,y\$Species)`\{\{noshy\}\}% Row Count 15 (+ 1)
} \tn 
\hhline{>{\arrayrulecolor{DarkBackground}}-}
\SetRowColor{LightBackground}
\mymulticolumn{1}{x{5.377cm}}{(*Additional) Ressources: \{\{popup="https://www.r-bloggers.com/2021/04/15-essential-packages-in-r-for-data-science/"\}\}1\{\{/popup\}\}, \{\{popup="https://data-flair.training/blogs/e1071-in-r/"\}\}2\{\{/popup\}\}}  \tn 
\hhline{>{\arrayrulecolor{DarkBackground}}-}
\end{tabularx}
\par\addvspace{1.3em}

\begin{tabularx}{5.377cm}{X}
\SetRowColor{DarkBackground}
\mymulticolumn{1}{x{5.377cm}}{\bf\textcolor{white}{8. tidyverse}}  \tn
\SetRowColor{white}
\mymulticolumn{1}{x{5.377cm}}{For data manipulation. Covered in lectures (see previous sections). \newline % Row Count 2 (+ 2)
Example: \newline % Row Count 3 (+ 1)
`library(tidyverse)`\{\{noshy\}\} \newline % Row Count 4 (+ 1)
`library(lubridate)`\{\{noshy\}\} \newline % Row Count 5 (+ 1)
`library(nycflights13)`\{\{noshy\}\} \newline % Row Count 6 (+ 1)
Create a new column basis count option \newline % Row Count 7 (+ 1)
`flights \%\textgreater{}\%`\{\{noshy\}\} \newline % Row Count 8 (+ 1)
`  mutate(long\_flight = (air\_time \textgreater{}= 6 * 60)) \%\textgreater{}\%`\{\{noshy\}\} \newline % Row Count 10 (+ 2)
`  View()`\{\{noshy\}\} \newline % Row Count 11 (+ 1)
Randomly Shuffle the data \newline % Row Count 12 (+ 1)
`flights \%\textgreater{}\%`\{\{noshy\}\} \newline % Row Count 13 (+ 1)
`  slice\_sample(n = 15)`\{\{noshy\}\}% Row Count 14 (+ 1)
} \tn 
\hhline{>{\arrayrulecolor{DarkBackground}}-}
\SetRowColor{LightBackground}
\mymulticolumn{1}{x{5.377cm}}{(*Additional) Ressources: \{\{popup="https://www.r-bloggers.com/2021/04/15-essential-packages-in-r-for-data-science/"\}\}1\{\{/popup\}\}, \{\{popup="https://finnstats.com/index.php/2021/04/02/tidyverse-in-r/"\}\}2\{\{/popup\}\}}  \tn 
\hhline{>{\arrayrulecolor{DarkBackground}}-}
\end{tabularx}
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\begin{tabularx}{5.377cm}{X}
\SetRowColor{DarkBackground}
\mymulticolumn{1}{x{5.377cm}}{\bf\textcolor{white}{9. caret}}  \tn
\SetRowColor{white}
\mymulticolumn{1}{x{5.377cm}}{If you are dealing with classification and regression problems then caret is one of the essential packages. \newline % Row Count 3 (+ 3)
`caret` package is the extension of the caret is CaretEnsemble which is used for combining different models. \newline % Row Count 6 (+ 3)
Example: \newline % Row Count 7 (+ 1)
Visualization of feature distribution by class \newline % Row Count 8 (+ 1)
`featurePlot(x = GermanCredit{[},c("EmploymentDuration", "Age"){]},`\{\{noshy\}\} \newline % Row Count 10 (+ 2)
`           y = GermanCredit\$Class,`\{\{noshy\}\} \newline % Row Count 11 (+ 1)
`            plot = "box")`\{\{noshy\}\} \newline % Row Count 12 (+ 1)
Pre-processing: imputation of missing data, one-hot encoding, and normalization \newline % Row Count 14 (+ 2)
`set.seed(355)`\{\{noshy\}\} \newline % Row Count 15 (+ 1)
`bagMissing \textless{}- preProcess(trainingSet, method = "bagImpute")`\{\{noshy\}\} \newline % Row Count 17 (+ 2)
`trainingSet \textless{}- predict(bagMissing, newdata = trainingSet)`\{\{noshy\}\} \newline % Row Count 19 (+ 2)
`dummyModel \textless{}- dummyVars(Class \textasciitilde{} ., data = trainingSet)`\{\{noshy\}\} \newline % Row Count 21 (+ 2)
`trainingSetX \textless{}- \seqsplit{as.data.frame(predict(dummyModel}, newdata = trainingSet))`\{\{noshy\}\}% Row Count 23 (+ 2)
} \tn 
\hhline{>{\arrayrulecolor{DarkBackground}}-}
\SetRowColor{LightBackground}
\mymulticolumn{1}{x{5.377cm}}{(*Additional) Ressources: \{\{popup="https://www.r-bloggers.com/2021/04/15-essential-packages-in-r-for-data-science/"\}\}1\{\{/popup\}\}, \{\{popup="https://rstudio-pubs-static.s3.amazonaws.com/867468\_4fc8916a0b2f4732b2a04fd20c7b5b70.html"\}\}2\{\{/popup\}\}}  \tn 
\hhline{>{\arrayrulecolor{DarkBackground}}-}
\end{tabularx}
\par\addvspace{1.3em}

\begin{tabularx}{5.377cm}{X}
\SetRowColor{DarkBackground}
\mymulticolumn{1}{x{5.377cm}}{\bf\textcolor{white}{10. shiny}}  \tn
\SetRowColor{white}
\mymulticolumn{1}{x{5.377cm}}{If you are thinking about an interactive and beautiful web interface then Shiny is the solution. \newline % Row Count 2 (+ 2)
Shiny interfaces are directly written in R and provide a customizable slider widget that has built-in support for animation. \newline % Row Count 5 (+ 3)
Example: \newline % Row Count 6 (+ 1)
`library(shiny)`\{\{noshy\}\} \newline % Row Count 7 (+ 1)
`\# See above for the definitions of ui and server`\{\{noshy\}\} \newline % Row Count 9 (+ 2)
`ui \textless{}- ...`\{\{noshy\}\} \newline % Row Count 10 (+ 1)
`server \textless{}- ...`\{\{noshy\}\} \newline % Row Count 11 (+ 1)
`shinyApp(ui = ui, server = server)`\{\{noshy\}\}% Row Count 12 (+ 1)
} \tn 
\hhline{>{\arrayrulecolor{DarkBackground}}-}
\SetRowColor{LightBackground}
\mymulticolumn{1}{x{5.377cm}}{(*Additional) Ressources: \{\{popup="https://www.r-bloggers.com/2021/04/15-essential-packages-in-r-for-data-science/"\}\}1\{\{/popup\}\}, \{\{popup="https://shiny.rstudio.com/tutorial/written-tutorial/lesson1/"\}\}2\{\{/popup\}\}}  \tn 
\hhline{>{\arrayrulecolor{DarkBackground}}-}
\end{tabularx}
\par\addvspace{1.3em}

\begin{tabularx}{5.377cm}{X}
\SetRowColor{DarkBackground}
\mymulticolumn{1}{x{5.377cm}}{\bf\textcolor{white}{10. shiny: Output}}  \tn
\SetRowColor{LightBackground}
\mymulticolumn{1}{p{5.377cm}}{\vspace{1px}\centerline{\includegraphics[width=5.1cm]{/web/www.cheatography.com/public/uploads/worlddoit_1670751729_ экрана 2022-12-11 в 10.41.52.png}}} \tn 
\hhline{>{\arrayrulecolor{DarkBackground}}-}
\SetRowColor{LightBackground}
\mymulticolumn{1}{x{5.377cm}}{(*Additional) Ressources: \{\{popup="https://www.r-bloggers.com/2021/04/15-essential-packages-in-r-for-data-science/"\}\}1\{\{/popup\}\}, \{\{popup="https://data-flair.training/blogs/e1071-in-r/"\}\}2\{\{/popup\}\}}  \tn 
\hhline{>{\arrayrulecolor{DarkBackground}}-}
\end{tabularx}
\par\addvspace{1.3em}

\begin{tabularx}{5.377cm}{X}
\SetRowColor{DarkBackground}
\mymulticolumn{1}{x{5.377cm}}{\bf\textcolor{white}{11. tidyquant}}  \tn
\SetRowColor{white}
\mymulticolumn{1}{x{5.377cm}}{`tidyquant` is considered as a financial package that is used to carry out quantitative financial analysis. \newline % Row Count 3 (+ 3)
Package tidyquant is also widely used for importing, analyzing, and visualizing data. \newline % Row Count 5 (+ 2)
Example: \newline % Row Count 6 (+ 1)
`library(tidyquant)`\{\{noshy\}\} \newline % Row Count 7 (+ 1)
`google \textless{}- tq\_get(x = "GOOG")`\{\{noshy\}\} \newline % Row Count 8 (+ 1)
`tq\_get\_options()`\{\{noshy\}\} \newline % Row Count 9 (+ 1)
`?tq\_get`\{\{noshy\}\} \newline % Row Count 10 (+ 1)
`tq\_exchange\_options()`\{\{noshy\}\} \newline % Row Count 11 (+ 1)
`nyse \textless{}- tq\_exchange("NYSE")`\{\{noshy\}\}% Row Count 12 (+ 1)
} \tn 
\hhline{>{\arrayrulecolor{DarkBackground}}-}
\SetRowColor{LightBackground}
\mymulticolumn{1}{x{5.377cm}}{(*Additional) Ressources: \{\{popup="https://www.r-bloggers.com/2021/04/15-essential-packages-in-r-for-data-science/"\}\}1\{\{/popup\}\}, \{\{popup="https://quantdev.ssri.psu.edu/sites/qdev/files/tidyquant\_tutorial\_Gray.html"\}\}2\{\{/popup\}\}}  \tn 
\hhline{>{\arrayrulecolor{DarkBackground}}-}
\end{tabularx}
\par\addvspace{1.3em}

\begin{tabularx}{5.377cm}{X}
\SetRowColor{DarkBackground}
\mymulticolumn{1}{x{5.377cm}}{\bf\textcolor{white}{12. tidyr}}  \tn
\SetRowColor{white}
\mymulticolumn{1}{x{5.377cm}}{`tidyr` is a new package that makes it easy to "tidy" your data. tidyr package is an evolution of Reshape2. \newline % Row Count 3 (+ 3)
The data is considered tidy when each variable represents columns and each row represents an observation. \newline % Row Count 6 (+ 3)
`gather()` makes "wide" data longer \newline % Row Count 7 (+ 1)
`spread()` makes "long" data wider \newline % Row Count 8 (+ 1)
`separate()` splits a single column into multiple columns \newline % Row Count 10 (+ 2)
`unite()` combines multiple columns into a single column \newline % Row Count 12 (+ 2)
and More... \newline % Row Count 13 (+ 1)
Example: \newline % Row Count 14 (+ 1)
`wide\_DF \textless{}- unite\_DF \%\textgreater{}\% spread(Quarter, Revenue)`\{\{noshy\}\} \newline % Row Count 16 (+ 2)
`head(wide\_DF, 24)`\{\{noshy\}\}% Row Count 17 (+ 1)
} \tn 
\hhline{>{\arrayrulecolor{DarkBackground}}-}
\SetRowColor{LightBackground}
\mymulticolumn{1}{x{5.377cm}}{(*Additional) Ressources: \{\{popup="https://www.r-bloggers.com/2021/04/15-essential-packages-in-r-for-data-science/"\}\}1\{\{/popup\}\}, \{\{popup="https://uc-r.github.io/tidyr"\}\}2\{\{/popup\}\}}  \tn 
\hhline{>{\arrayrulecolor{DarkBackground}}-}
\end{tabularx}
\par\addvspace{1.3em}

\begin{tabularx}{5.377cm}{X}
\SetRowColor{DarkBackground}
\mymulticolumn{1}{x{5.377cm}}{\bf\textcolor{white}{13. ggraph}}  \tn
\SetRowColor{white}
\mymulticolumn{1}{x{5.377cm}}{Takes away all the limitations of ggplot2. \newline % Row Count 1 (+ 1)
Example for Networks: \newline % Row Count 2 (+ 1)
`ggraph(ig\_loc, layout="fr") + `\{\{noshy\}\} \newline % Row Count 3 (+ 1)
`  \seqsplit{geom\_edge\_link(aes(color} = factor(to), width = log(weight)), alpha = 0.5, `\{\{noshy\}\} \newline % Row Count 5 (+ 2)
`                  start\_cap = circle(2, 'mm'), end\_cap = circle(2, 'mm')) + `\{\{noshy\}\} \newline % Row Count 7 (+ 2)
`  scale\_edge\_width(range = c(0.5, 2.5)) + `\{\{noshy\}\} \newline % Row Count 9 (+ 2)
`  geom\_node\_point(color = V(ig\_loc)\$color, size = 5, alpha = 0.5) +`\{\{noshy\}\} \newline % Row Count 11 (+ 2)
`  \seqsplit{geom\_node\_text(aes(label} = name), repel = TRUE) +`\{\{noshy\}\} \newline % Row Count 13 (+ 2)
`  theme\_void() + `\{\{noshy\}\} \newline % Row Count 14 (+ 1)
`  theme(legend.position = "none") `\{\{noshy\}\}% Row Count 15 (+ 1)
} \tn 
\hhline{>{\arrayrulecolor{DarkBackground}}-}
\SetRowColor{LightBackground}
\mymulticolumn{1}{x{5.377cm}}{(*Additional) Ressources: \{\{popup="https://www.r-bloggers.com/2021/04/15-essential-packages-in-r-for-data-science/"\}\}1\{\{/popup\}\}, \{\{popup="https://rpubs.com/neloe/ggraph\_intro"\}\}2\{\{/popup\}\}, \newline \{\{popup="https://www.data-imaginist.com/2017/ggraph-introduction-layouts/"\}\}3\{\{/popup\}\}}  \tn 
\hhline{>{\arrayrulecolor{DarkBackground}}-}
\end{tabularx}
\par\addvspace{1.3em}

\begin{tabularx}{5.377cm}{X}
\SetRowColor{DarkBackground}
\mymulticolumn{1}{x{5.377cm}}{\bf\textcolor{white}{13. ggraph: Output}}  \tn
\SetRowColor{LightBackground}
\mymulticolumn{1}{p{5.377cm}}{\vspace{1px}\centerline{\includegraphics[width=5.1cm]{/web/www.cheatography.com/public/uploads/worlddoit_1670753329_ экрана 2022-12-11 в 11.05.43.png}}} \tn 
\hhline{>{\arrayrulecolor{DarkBackground}}-}
\SetRowColor{LightBackground}
\mymulticolumn{1}{x{5.377cm}}{(*Additional)}  \tn 
\hhline{>{\arrayrulecolor{DarkBackground}}-}
\end{tabularx}
\par\addvspace{1.3em}

\begin{tabularx}{5.377cm}{X}
\SetRowColor{DarkBackground}
\mymulticolumn{1}{x{5.377cm}}{\bf\textcolor{white}{14. ggplot2}}  \tn
\SetRowColor{white}
\mymulticolumn{1}{x{5.377cm}}{`ggplot2` is one of the most popular visualization package in R. \newline % Row Count 2 (+ 2)
It is famous for its functionality and high-quality graphs that set it apart from other visualization packages. \newline % Row Count 5 (+ 3)
Example: \newline % Row Count 6 (+ 1)
`ggplot(chic, aes(x = o3, y = temp))+`\{\{noshy\}\} \newline % Row Count 7 (+ 1)
`  labs(x = "Ozone Level", y = "Temperature (°F)") +`\{\{noshy\}\} \newline % Row Count 9 (+ 2)
`  geom\_smooth(`\{\{noshy\}\} \newline % Row Count 10 (+ 1)
`    method = "lm",`\{\{noshy\}\} \newline % Row Count 11 (+ 1)
`    formula = y \textasciitilde{} x + I(x\textasciicircum{}2) + I(x\textasciicircum{}3) + I(x\textasciicircum{}4) + I(x\textasciicircum{}5),`\{\{noshy\}\} \newline % Row Count 13 (+ 2)
`    color = "black",`\{\{noshy\}\} \newline % Row Count 14 (+ 1)
`    fill = "firebrick") +`\{\{noshy\}\} \newline % Row Count 15 (+ 1)
`  geom\_point(color = "gray40", alpha = .3)`\{\{noshy\}\}% Row Count 17 (+ 2)
} \tn 
\hhline{>{\arrayrulecolor{DarkBackground}}-}
\SetRowColor{LightBackground}
\mymulticolumn{1}{x{5.377cm}}{(*Additional) Ressources: \{\{popup="https://www.r-bloggers.com/2021/04/15-essential-packages-in-r-for-data-science/"\}\}1\{\{/popup\}\}, \{\{popup="https://www.cedricscherer.com/2019/08/05/a-ggplot2-tutorial-for-beautiful-plotting-in-r/"\}\}2\{\{/popup\}\}, \{\{popup="http://r-statistics.co/Top50-Ggplot2-Visualizations-MasterList-R-Code.html"\}\}3\{\{/popup\}\}}  \tn 
\hhline{>{\arrayrulecolor{DarkBackground}}-}
\end{tabularx}
\par\addvspace{1.3em}

\begin{tabularx}{5.377cm}{X}
\SetRowColor{DarkBackground}
\mymulticolumn{1}{x{5.377cm}}{\bf\textcolor{white}{14. ggplot2: Output}}  \tn
\SetRowColor{LightBackground}
\mymulticolumn{1}{p{5.377cm}}{\vspace{1px}\centerline{\includegraphics[width=5.1cm]{/web/www.cheatography.com/public/uploads/worlddoit_1670754604_ экрана 2022-12-11 в 11.10.46.png}}} \tn 
\hhline{>{\arrayrulecolor{DarkBackground}}-}
\SetRowColor{LightBackground}
\mymulticolumn{1}{x{5.377cm}}{(*Additional)}  \tn 
\hhline{>{\arrayrulecolor{DarkBackground}}-}
\end{tabularx}
\par\addvspace{1.3em}


% That's all folks
\end{multicols*}

\end{document}