diff --git a/Class6/Class_Examples/apply.r b/Class6/Class_Examples/apply.r
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+++ b/Class6/Class_Examples/apply.r
@@ -0,0 +1,8 @@
+DAT <- 1:8
+?apply
+apply(DAT,mean)
+?mapply
+x <- as.data.frame(cbind(x1 = c(3,NA,12,7), x2 = c(4:1, 2:5)) )
+dimnames(x)[[1]] <- letters[1:8]
+apply(x, 2, mean, trim = .2,na.rm=TRUE)
+?mean
\ No newline at end of file
diff --git a/Class6/Slides/Function.png b/Class6/Slides/Function.png
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diff --git a/Class6/Slides/If.png b/Class6/Slides/If.png
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diff --git a/Class6/Slides/Loops_Tidy.tex b/Class6/Slides/Loops_Tidy.tex
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+++ b/Class6/Slides/Loops_Tidy.tex
@@ -0,0 +1,111 @@
+\documentclass{beamer}
+\usepackage{graphicx}
+\usepackage{multicol}
+\usepackage{hyperref}
+\usepackage{lipsum} % for placeholder text
+\graphicspath{{pdf_images/}}
+
+
+\title{ECON 4530/5530 \\ Computational Economics}
+\subtitle{Data transformation and Loops}
+\author{Alex Gebben}
+
+\begin{document}
+
+% Title Slide
+\begin{frame}
+  \titlepage
+\end{frame}
+%%%%%%%%%%%%%%%%%%
+\begin{frame}{Loops}
+	\only<1->{There are three types of loops in R }
+	\begin{enumerate}
+		\onslide<2->{	\item{A \emph{for} loop runs for each value in a list}}
+	\begin{itemize}
+		\onslide<3->{\item \texttt{for(i in 1:10){Code to run}}}
+	\end{itemize}
+	\begin{enumerate}
+		\onslide<4->{	\item{A \emph{While} loop runs if a condtion is metif a condtion is met.\emph{Can lead to infinite loops}}}
+	\begin{itemize}
+		\onslide<5->{\item \texttt{while(a==b){Code to run}}}
+	\end{itemize}
+		\onslide<4->{apply functions }
+	\begin{itemize}
+		\onslide<5->{\item \texttt{while(a==b){Code to run}}}
+	\end{itemize}
+	\end{enumerate}
+\end{frame}
+\begin{frame}{Section Comments}
+	Section comments visually separate chunks of code. It is an excellent practice to distinguish types of analysis, or groups of code.
+	\newline
+\vspace{1em}
+\onslide<2->{\includegraphics[width=\textwidth]{Section_comments.png}}
+	\newline
+\vspace{1em}
+\onslide<3->{RStudio provides a keyboard shortcut to create these headers \texttt{(Cmd/Ctrl + Shift + R)}}
+\end{frame}
+%%%%%%%%%%%%
+\begin{frame}{\emph{if} statements}
+	\only<1-8>{
+	\emph{If} only run code when certain condtions are met
+	\newline
+	\onslide<2->{	\textbf{Possible uses}}
+	\begin{enumerate}
+		\onslide<3->{\item Load a file only if it does not exist }
+		\onslide<4->{\item Switch the value of an entry}
+		\onslide<5->{\item Create a new dummy variable}
+		\onslide<6->{\item Account for changes in column names on servers}
+	\end{enumerate}
+	\onslide<7->{Can be combined with \emph{else}}
+	\newline
+	\onslide<8->{The R function \texttt{ifelse()} can be a good shortcut}
+}
+\only<9>{\includegraphics[width=0.75\textwidth]{If.png}}
+\end{frame}
+%%%%%%%%%%%%%%%%
+\begin{frame}{Class Exercise}
+Use an if statement to write a csv file in a ``Data'' directory if the folder exists, otherwise it creates the directory first.
+\end{frame}
+%%%%%%%%%%%%
+\begin{frame}{functions}
+	\only<1-6>{
+	\emph{functions} save a set of code to use later.
+	\newline
+	\onslide<2->{They are exactly the same as the functions you already use in R}
+	\onslide<3->{Must define function inputs, code and output}
+	\begin{enumerate}
+		\onslide<4->{\item Use if you repeat code more than twice }
+		\onslide<4->{\item Stores complex code avoids typos}
+		\onslide<5->{\item Can be loaded in script files}
+		\onslide<6->{\item Could be used in your own library}
+	\end{enumerate}
+}
+\only<7>{\includegraphics[width=\textwidth]{Function.png}}
+\only<8>{The \texttt{try()} function can be useful when creating your own functions. It prevents the code from stopping after a failure. Use with care.}
+\end{frame}
+%%%%%%%%%%%%%%%%
+\begin{frame}{Class Exercise}
+	Turn the previous if statement into a function. Allow the user to pass in the name of the folder that is created. 
+\end{frame}
+%%%%%%%%%%%%%%%%%%%
+\begin{frame}{Class Exercise}
+	\only<1>{\LARGE Remember proper naming of files, data and scripts. Provide clear comments.}
+\only<2>{
+	\begin{enumerate}
+\item Identify three data set you are interested in on FRED
+	\item Load one data set using a URL saved as a character variable
+	\item Create a raw data subdirectory and save the raw data into it
+	\item Clean the data, at least update the column names
+	\item Save the cleaned data as a CSV and an RDS file in a cleaned data subdirectory with proper names
+	\item Include a comment on the first line of the file explain what the code is used for and why.
+	\item Comment any other code as needed
+	\item Turn this code into a function where the user passes in the URL, and column names
+	\item Save function in a separate Rscript in a directory for scripts. Pay attention to the name
+	\item In the main directory create a Rscript and in that script load script 
+	\item Use the function to clean all three data sets 
+	\item After this add a section of code to find the mean, and summary of the data
+\end{enumerate}
+}
+\end{frame}
+
+\end{document}
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