Created slides

Class4/Comp_Econ_Code/Code_Examples.r

@@ -1,8 +1,40 @@
-library(tidyverse)
+####Load libraries
-getwd()
+  library(tidyverse) #tidyverse is used to organize the data with read_csv()
+  library(fixest) #Fixest is load so a fixed effect model can be used.
+#Creating directories to store the raw data set, 
+#  so the results can reproduced more easily if the data changes.
+  dir.create("Data",showWarnings = FALSE)
+  dir.create("Data/Orig_Data",showWarnings = FALSE)
+  #Check if direjctory exits
+  dir.exists("Data/Orig_Data")
+
+# Help --------------------------------------------------------------------
+
+
+#List all files in the working directory
+list.files()
+#List all files in the working directory that end in png
+  list.files("./",pattern="*.png")
+#list all files in the Data folder staring from the working directory
+  list.files("Data/")
+#write a csv file to the directory
+  write_csv(diamonds, "Data/diamonds.csv")
+#write a tab separated file to the directory (tsv)
+  write_tsv(diamonds, "Data/diamonds.tsv")
+#list all files in the Data directory. Save in a variable.
+  FILE_LIST <- list.files("Data/")
+  print(FILE_LIST)
+#Check if a file exists in the Data directory
+file.exists("Data/DIAMOND.csv")
+#Check if the file in the list exists
+  file.exists(FILE_LIST[1])
+#Check if the file in the list exists
+  FILE_LOC <- paste0("./Data/",FILE_LIST[1])
+  print(FILE_LOC)
+  file.exists(FILE_LOC)
+
 
 ggplot(diamonds, aes(x = carat, y = price)) + 
   geom_hex()
 ggsave("diamonds.png")
 dir.create("./data")
-write_csv(diamonds, "data/diamonds.csv")

Class4/Slides/Best_Practice.tex

@@ -18,6 +18,14 @@
 \end{frame}
 
 %%%%%%%%%%%%%%%%%%
+\begin{frame}{Shortcuts}
+	\begin{itemize}
+		\item \texttt{Alt + - (the minus sign)} creates a arrow \texttt{->}
+		\item{\texttt{Cmd/Ctrl + Shift + N} open a new Rscript}
+		\item{\texttt{Cmd/Ctrl + Enter.} execute the current line}
+		\item{\texttt{Cmd/Ctrl + Shift + S.} execute the entire script}
+	\end{itemize}
+\end{frame}
 
 \begin{frame}{What problems have you run into?}
 	\begin{centering}
@@ -105,11 +113,12 @@
 \end{frame}
 %%%%%%%%%%%%%%%%%%
 \begin{frame}{Class Exercise}
-	\huge
+	\centering
-	Download relevant data
+	\begin{enumerate}
-
+		\item{Create a new project folder, make sure R does not auto-save.}
-	\normalsize
+		\item{Open R from your programs and run getwd()}
-	It is good practice to store the data is a separate folder in the location of the Rscript. Such as a "Data" folder.
+		\item{Close R and open the R project, run getwd() again}
+	\end{enumerate}
 \end{frame}
 
 \begin{frame}{File Management}
@@ -134,7 +143,7 @@
 \only<1-14>{
 \begin{columns}[T,onlytextwidth]
     \column{0.5\textwidth}
-	\textbf{Usefull Functions}
+	\textbf{Useful Functions}
 	\begin{itemize}
 	\onslide<2->{\item \texttt{create.dir()}}
 	\onslide<3->{\item\texttt{dir.exists()}}
@@ -155,17 +164,112 @@
 }
 \end{columns}
 \vspace{1.5em}
-\onslide<14>{Many other options in R review \texttt{help()} and the internet.}
+\onslide<14->{For downloading raw files \texttt{download.file()} is great!}
+\onslide<15>{Many other options in R review \texttt{help()} and the internet.}
 }
 \only<15>{\includegraphics[width=\textwidth]{DIR.png}}
 \only<16>{\includegraphics[width=\textwidth]{DIR2.png}}
 \end{frame}
-
+%%%%%%%%%%%
+\begin{frame}{Using Directories for Organization}
+	Keep your main working space clean, and separate what you can.
+\vspace{1.5em}
+    \begin{enumerate}
+	    \onslide<2->{\item Make diffrent files for each main data step. Downloading, cleaning, various analyses.}
+	    \onslide<3->{\item You can save the data downloading portion as a file called \texttt{1\_EIA\_Data\_Proc.R}}
+	    \onslide<4->{\item In the main file you could load the code with \texttt{source(``1\_EIA\_Data\_Proc.R'')}}
+	    \onslide<5->{R will run the code in the current directory even if the script is saved elsewhere.}
+\end{enumerate}
+\end{frame}
+%%%%%%%%%%%%%%%%%%%
+\begin{frame}{Class Exercise}
+	\centering
+	\begin{enumerate}
+		\item{Using the R project create a directory for data, with a sub-directory for raw data and cleaned data.}
+		\item{Using R create directory for scripts}
+		\item{In R verify the directories were created using code.}
+		\item{All code should use relative paths. Make sure it can be run multiple times without errors.}
+	\end{enumerate}
+\end{frame}
+%%%%%%%%%%%%
 \begin{frame}{Naming Files}
 %	\href{https://r4ds.hadley.nz/workflow-scripts.html#fn2'}{For an example DONT LEAVE AS A LINK FOR MY REFRENCE}
-	It might be tempting to name your files code.R or myscript.R, but you should think a bit harder before choosing a name for your file. Three important principles for file naming are as follows\:
+	File names should be \textbf{human readable}:
-    File names should be machine readable\: avoid spaces, symbols, and special characters. Don’t rely on case sensitivity to distinguish files.
+    \begin{enumerate}
-    File names should be human readable\: use file names to describe what’s in the file.
+	    \onslide<2->{\item Use file names to describe what’s in the file.}
-    File names should play well with default ordering\: start file names with numbers so that alphabetical sorting puts them in the order they get used.
+	    \onslide<3->{\item Don’t rely on case sensitivity to distinguish files.}
+	    \onslide<4->{\item File names should play well with default ordering}
+	    \onslide<5->{\item Start file names with numbers so that alphabetical sorting puts them in the order they get used.}
+	\onslide<6->{\item Include dates in the name of output files.}
+	\end{enumerate}
+	\onslide<7->{File names should be \textbf{computer readable} avoid:}
+    \begin{enumerate}
+	\onslide<8->{\item spaces}
+	\onslide<9->{\item symbols }
+	\onslide<10->{\item special characters}
+   \end{enumerate}
+				   
 \end{frame}
+\begin{frame}{Class Exercise}
+	\only<1-7>{
+		\only<1>{List as many issues you can find in these file names? Explain why they might cause you problems in a long term project.}
+		\only<2->{\includegraphics[width=\textwidth]{Bad_File_Names.png}}
+	\begin{itemize}
+	\onslide<3->{\item File names contain spaces}
+	\onslide<4->{\item Same name but different capitalization}
+	\onslide<5->{\item Names don’t describe their contents ``temp''}
+	\onslide<6->{\item Outputs should be in seperate directory from inputs}
+	\onslide<7->{\item Outputs files should have dates in the name}
+\end{itemize}
+}
+	\only<8>{\includegraphics[width=\textwidth]{Good_File_Names.png}}
+\end{frame}
+%%%%%%%%%%%%%%%
+\begin{frame}{Commenting Code}
+	\only<1-3>{
+	\onslide<1-3>{Comments are lines of code which do not run. These are \textbf{\emph{very}} important. }
+	\newline
+	\onslide<2-3>{	In R these are created by starting a line with ``\#''}
+\onslide<3>{
+	\begin{enumerate}
+		\item{You should add a comment to any line of code which is not highly simple.}
+		\item{Keep a clean comment style}
+		\item{Comment above a section of code. Indent the following code}
+		\item{Always include the why of your code. The what and how of your code is less critical} 
+		\item{Think about what you would need to know if you forgot everything about the project}
+	\end{enumerate}
+}
+}
+\only<4>{
+	  \includegraphics[width=0.7\textwidth]{What_Comments}
+	  \includegraphics[width=\textwidth]{Why_Comments}
+
+  }
+\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}{Class Exercise}
+	\begin{enumerate}
+\item Identify a data set you are interested in on FRED
+	\item Load the data 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 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 Save the Rscript in a directory for scripts. Pay attention to the name
+	\item In the main directory create a Rscript and in that script start by loading the data loading script
+	\item After this add a section of code to find the mean, and summary of the data
+\end{enumerate}
+\end{frame}
+
+
 \end{document}