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MAT381E-Fall21 · Jan 2, 2022 · 589364a · 589364a
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diff --git a/.DS_Store b/.DS_Store
diff --git a/README.md b/README.md
@@ -1 +1,6 @@
-# Week_13_14_Lecture_Notes
+
+# Week_13_14_Lecture_Notes: Building Interactive Web Applications
+
+There is one `.Rmd/html` file to follow:  
+
+ - `intro_rshiny.Rmd/intro_rshiny.html`.
diff --git a/countries-01/app.R b/countries-01/app.R
@@ -3,7 +3,8 @@ library(shiny)
 library(tidyverse)
 
 ## read data -------------------------------------------------------------------
-countries_data <- read_csv("/Users/gulinan/Desktop/Introduction to Data Science with R/Week_13-14/Week13_Lecture_Notes/source_files/data/countries_1998_2011.csv")
+countries_data <- 
+  read_csv("/Users/gulinan/Desktop/MAT381E_Introduction to Data Science/Week_13-14/Week_13_14_Lecture_Notes/data/countries_1998_2011.csv")
 
 ## subset data
 countries_data_2011 <- countries_data %>% 
@@ -49,7 +50,7 @@ server <- function(input, output) {
     ## output is a reserved word.
     ## countries_scatter is given by me.
     ## input has two parts: x_axis and y_axis
-    ## renderPlot({expr}): Renders a reactive plot that is suitable for assigning to an output slot.
+    ## renderPlot({expr}): Renders a reactive plot that is suitable for assigning to an output plot.
     ## expr: An expression that generates a plot.	
 
     output$countries_scatter <- renderPlot({

diff --git a/countries-02/app.R b/countries-02/app.R
@@ -3,7 +3,8 @@ library(shiny)
 library(tidyverse)
 
 ## read data -------------------------------------------------------------------
-countries_data <- read_csv("/Users/gulinan/Desktop/Introduction to Data Science with R/Week_13-14/Week13_Lecture_Notes/source_files/data/countries_1998_2011.csv")
+countries_data <-read_csv("/Users/gulinan/Desktop/MAT381E_Introduction to Data Science/Week_13-14/Week_13_14_Lecture_Notes/data/countries_1998_2011.csv")
+
 
 ## subset data
 countries_data_2011 <- countries_data %>% 

diff --git a/countries-03/app.R b/countries-03/app.R
@@ -3,7 +3,7 @@ library(shiny)
 library(tidyverse)
 
 ## read data -------------------------------------------------------------------
-countries_data <- read_csv("/Users/gulinan/Desktop/Introduction to Data Science with R/Week_13-14/Week13_Lecture_Notes/source_files/data/countries_1998_2011.csv")
+countries_data <-read_csv("/Users/gulinan/Desktop/MAT381E_Introduction to Data Science/Week_13-14/Week_13_14_Lecture_Notes/data/countries_1998_2011.csv")
 
 ## subset data
 countries_data_2011 <- countries_data %>% 

diff --git a/countries-04/app.R b/countries-04/app.R
@@ -4,7 +4,7 @@ library(tidyverse)
 library(DT)
 
 ## read data -------------------------------------------------------------------
-countries_data <- read_csv("/Users/gulinan/Desktop/Introduction to Data Science with R/Week_13-14/Week13_Lecture_Notes/source_files/data/countries_1998_2011.csv")
+countries_data <-read_csv("/Users/gulinan/Desktop/MAT381E_Introduction to Data Science/Week_13-14/Week_13_14_Lecture_Notes/data/countries_1998_2011.csv")
 
 ## subset data
 countries_data_2011 <- countries_data %>% 

diff --git a/countries-05/app.R b/countries-05/app.R
@@ -4,7 +4,7 @@ library(tidyverse)
 library(DT)
 
 ## read data -------------------------------------------------------------------
-countries_data <- read_csv("/Users/gulinan/Desktop/Introduction to Data Science with R/Week_13-14/Week13_Lecture_Notes/source_files/data/countries_1998_2011.csv")
+countries_data <-read_csv("/Users/gulinan/Desktop/MAT381E_Introduction to Data Science/Week_13-14/Week_13_14_Lecture_Notes/data/countries_1998_2011.csv")
 
 ## subset data
 countries_data_2011 <- countries_data %>% 

diff --git a/countries-06/app.R b/countries-06/app.R
@@ -5,7 +5,7 @@ library(DT)
 library(plotly)
 
 ## read data -------------------------------------------------------------------
-countries_data <- read_csv("/Users/gulinan/Desktop/Introduction to Data Science with R/Week_13-14/Week13_Lecture_Notes/source_files/data/countries_1998_2011.csv")
+countries_data <-read_csv("/Users/gulinan/Desktop/MAT381E_Introduction to Data Science/Week_13-14/Week_13_14_Lecture_Notes/data/countries_1998_2011.csv")
 
 ## subset data
 countries_data_2011 <- countries_data %>% 

diff --git a/countries-07/app.R b/countries-07/app.R
@@ -7,7 +7,7 @@ library(plotly)
 
 # we are not doing any sub-setting on data here.
 
-countries_data <- read_csv("/Users/gulinan/Desktop/Introduction to Data Science with R/Week_13-14/Week13_Lecture_Notes/source_files/data/countries_1998_2011.csv")
+countries_data <-read_csv("/Users/gulinan/Desktop/MAT381E_Introduction to Data Science/Week_13-14/Week_13_14_Lecture_Notes/data/countries_1998_2011.csv")
 
 
 ## UI ##########################################################################

diff --git a/countries-08/app.R b/countries-08/app.R
@@ -4,7 +4,7 @@ library(tidyverse)
 library(plotly)
 
 ## read data -------------------------------------------------------------------
-countries_data <- read_csv("/Users/gulinan/Desktop/Introduction to Data Science with R/Week_13-14/Week13_Lecture_Notes/source_files/data/countries_1998_2011.csv")
+countries_data <-read_csv("/Users/gulinan/Desktop/MAT381E_Introduction to Data Science/Week_13-14/Week_13_14_Lecture_Notes/data/countries_1998_2011.csv")
 
 
 ## UI ##########################################################################

diff --git a/countries-09/app.R b/countries-09/app.R
@@ -5,7 +5,7 @@ library(plotly)
 library(shinythemes)
 
 ## read data -------------------------------------------------------------------
-countries_data <- read_csv("/Users/gulinan/Desktop/Introduction to Data Science with R/Week_13-14/Week13_Lecture_Notes/source_files/data/countries_1998_2011.csv")
+countries_data <-read_csv("/Users/gulinan/Desktop/MAT381E_Introduction to Data Science/Week_13-14/Week_13_14_Lecture_Notes/data/countries_1998_2011.csv")
 
 ## numeric columns to plot
 numeric_columns <- c("human_development_index", "corruption_perception_index",

diff --git a/denemefall21/app.R b/denemefall21/app.R
@@ -0,0 +1,49 @@
+#
+# This is a Shiny web application. You can run the application by clicking
+# the 'Run App' button above.
+#
+# Find out more about building applications with Shiny here:
+#
+#    http://shiny.rstudio.com/
+#
+
+library(shiny)
+
+# Define UI for application that draws a histogram
+ui <- fluidPage(
+
+    # Application title
+    titlePanel("Old Faithful Geyser Data"),
+
+    # Sidebar with a slider input for number of bins 
+    sidebarLayout(
+        sidebarPanel(
+            sliderInput("bins",
+                        "Number of bins:",
+                        min = 1,
+                        max = 50,
+                        value = 30)
+        ),
+
+        # Show a plot of the generated distribution
+        mainPanel(
+           plotOutput("distPlot")
+        )
+    )
+)
+
+# Define server logic required to draw a histogram
+server <- function(input, output) {
+
+    output$distPlot <- renderPlot({
+        # generate bins based on input$bins from ui.R
+        x    <- faithful[, 2]
+        bins <- seq(min(x), max(x), length.out = input$bins + 1)
+
+        # draw the histogram with the specified number of bins
+        hist(x, breaks = bins, col = 'darkgray', border = 'white')
+    })
+}
+
+# Run the application 
+shinyApp(ui = ui, server = server)
diff --git a/images/hdi_index.png b/images/hdi_index.png
diff --git a/intro_rshiny.Rmd b/intro_rshiny.Rmd
@@ -52,46 +52,6 @@ class: left
 * Introduction to `Shiny` package.  
 * Examples.
 
-
----
-#### <span style="color:red"> Some important notes on Interim report</span> 
-<p> 
-<ul>
-<li> State your aim and provide some information on your topic.</li>
-<li> Provide information on your data set (do not expect us to understand your data) and tells us about the variables in your data set.</li>
-<li> Tells us where you obtained your data (access link etc) and save your data set in your R project, so that we can see the content.</li>
-<li> If you use abbreviations, be sure that you have given the long form of the abbreviation at your first mention.</li>
-<li> Do not use abbreviations such as "we'll do". Use the full form, such as "we will do".</li>
-<li> In addition to outputs, include your codes in the report as well.</li>
-<li> Turn off warnings and messages (warning=F, message=F).</li>
-<li> Align your code vertically, not horizontally. If it does not fit into a line, break down it into smaller pieces at appropriate places. </li>
-<li> Do not try to give too much information with a single graphic. It is overwhelming. Instead, use faceting (side-by-side small graphs).</li>
-<li> Do not forget to put x-axis title, y-axis title, main title. Graphics should be
-informative.</li>
-<li> Explain the graphics with a few sentences in your report. </li>
-<li> Have a visualization style and be consistent throughout the report.</li>
-<li> Do not use default ggplot2 colors. Try out different palettes for object colors and background colors.</li>
-<li> If you mention something at the introduction such as "we will do this", then show it in the report. Otherwise, omit it.</li>
-<li> In conclusion, shortly summarize your aim and findings.</li>
-<li> In the end this is a report!..It should be appealing for people to read it!..</li>
-</ul> </p>
----
-#### **Office Hours**
-
-- May 31, 2021 between 20:30-22:30.   
-- June 7, 2021 between 20:30-22:30.   
-- June 14, 2021 between 20:30-22:30.   
-- June 21, 2021 between 20:30-22:30.     
-
-#### **Zoom meeting link details**:
-
-
-[Join Zoom Meeting](https://itu-edu-tr.zoom.us/j/99088059412?pwd=bTNZcElreWd3Z1MyS0hvVnpLOEdrQT09)
-
-Meeting ID: 990 8805 9412  
-Passcode: 396830
-
-
 ---
 
 - Please visit the [NASA Earth Data's Covid-19 Dashboard](
@@ -110,14 +70,14 @@ knitr::include_graphics("logo/rshiny.png")
 
 ---
 #### Shiny package
-- [`Shiny`](https://shiny.rstudio.com/) is an `R` package that provides elegant and powerful web framework for **building interactive web applications (apps)** directly from `R`.
+-  [R Shiny](https://shiny.rstudio.com/) is an `R` package that provides elegant and powerful web framework for **building interactive web applications (apps)** directly from `R`.
 - You can host standalone apps on a **webpage** or build **dashboards**. 
 - Shiny applications are automatically live and outputs change instantly as users modify inputs, without requiring a reload of the browser.
 - You can also extend your Shiny apps with [CSS themes](http://rstudio.github.io/shinythemes/?_ga=2.128822476.1106871023.1621587722-51308884.1621587722), [htmlwidgets](http://www.htmlwidgets.org/), and [JavaScript](https://github.com/daattali/shinyjs/blob/master/README.md) actions.
 - To install and load the package:
 
-```{r, eval=F}
-install.packages("shiny")
+```{r}
+#install.packages("shiny")
 library(shiny)
 ```
 
@@ -449,7 +409,7 @@ server <- function(input, output) {
 
 
 
-- Each `render*()` function takes a single argument: an `R expression` surrounded by braces {} and and do some light pre-processing on the expression.
+- Each `render*()` function takes a single argument: an `R expression` surrounded by braces {} and do some light pre-processing on the expression.
 
 ---
 - The `R expression` can be one simple line of text, or it can involve many lines of code, as if it were a complicated function call.	
@@ -529,6 +489,10 @@ shinyApp(ui = ui, server = server)
 
 - <span style="color:purple">**The Human Development Index (HDI)** is a summary measure of average achievement in key dimensions of human development: a long and healthy life, being knowledgeable and have a decent standard of living. The HDI is the geometric mean of normalized indices for each of the three dimensions.</span>
 
+```{r, echo=FALSE, out.width="100%"}
+knitr::include_graphics("images/hdi_index.png")
+```
+
 ---
 
 class: middle, center
@@ -555,7 +519,7 @@ View(data)
 
 ---
 #### Example: Countries-01
-- Filter the data for the year 2011 and develop a `Shiny` app which enables to select one of variables **human_development_index**, **corruption_perception_index**, **population**, **life_exp**, and **gdp_per_capita** through a  `input widget` to plot the selected variable on the horizontal axis and also enables to select another variable  through another `input widget` to plot that selected variable on the vertical axis.
+- Filter the data for the year 2011 and develop a `Shiny` app which enables to select one of variables **human_development_index**, **corruption_perception_index**, **population**, **life_exp**, and **gdp_per_capita** through an  `input widget` to plot the selected variable on the horizontal axis and also enables to select another variable  through another `input widget` to plot that selected variable on the vertical axis.
 - Afterwards, get a scatter plot of the selected two variables and identify the points by their **continent type** by assigning different **colors**.
 
 ---
@@ -1038,7 +1002,11 @@ on this selection, create `SliderInput` widgets for "pct_noba", "pct_rent", "med
 ---
 class: middle, center
 
-<span style="color:purple">WISH YOU A GOOD WINTER BREAK!..☃️</span>
+<span style="color:purple">WISH YOU A GOOD FINAL EXAM WEEK & WINTER BREAK!..</span>
+
+<br>
+
+✏️ 📚  ☃️
 
                                
 

diff --git a/intro_rshiny.html b/intro_rshiny.html
@@ -4,7 +4,7 @@
     <title>MAT381E-Week 13-14: Building Interactive Web Applications</title>
     <meta charset="utf-8" />
     <meta name="author" content="Gül İnan" />
-    <meta name="date" content="2022-01-01" />
+    <meta name="date" content="2022-01-02" />
     <script src="intro_rshiny_files/header-attrs-2.11/header-attrs.js"></script>
     <link href="intro_rshiny_files/remark-css-0.0.1/default.css" rel="stylesheet" />
     <script src="intro_rshiny_files/fabric-4.3.1/fabric.min.js"></script>
@@ -26,7 +26,7 @@
 # MAT381E-Week 13-14: Building Interactive Web Applications
 ### Gül İnan
 ### Department of Mathematics<br/>Istanbul Technical University
-### January 1, 2022
+### January 2, 2022
 
 ---
 
@@ -47,46 +47,6 @@
 * Introduction to `Shiny` package.  
 * Examples.
 
-
----
-#### &lt;span style="color:red"&gt; Some important notes on Interim report&lt;/span&gt; 
-&lt;p&gt; 
-&lt;ul&gt;
-&lt;li&gt; State your aim and provide some information on your topic.&lt;/li&gt;
-&lt;li&gt; Provide information on your data set (do not expect us to understand your data) and tells us about the variables in your data set.&lt;/li&gt;
-&lt;li&gt; Tells us where you obtained your data (access link etc) and save your data set in your R project, so that we can see the content.&lt;/li&gt;
-&lt;li&gt; If you use abbreviations, be sure that you have given the long form of the abbreviation at your first mention.&lt;/li&gt;
-&lt;li&gt; Do not use abbreviations such as "we'll do". Use the full form, such as "we will do".&lt;/li&gt;
-&lt;li&gt; In addition to outputs, include your codes in the report as well.&lt;/li&gt;
-&lt;li&gt; Turn off warnings and messages (warning=F, message=F).&lt;/li&gt;
-&lt;li&gt; Align your code vertically, not horizontally. If it does not fit into a line, break down it into smaller pieces at appropriate places. &lt;/li&gt;
-&lt;li&gt; Do not try to give too much information with a single graphic. It is overwhelming. Instead, use faceting (side-by-side small graphs).&lt;/li&gt;
-&lt;li&gt; Do not forget to put x-axis title, y-axis title, main title. Graphics should be
-informative.&lt;/li&gt;
-&lt;li&gt; Explain the graphics with a few sentences in your report. &lt;/li&gt;
-&lt;li&gt; Have a visualization style and be consistent throughout the report.&lt;/li&gt;
-&lt;li&gt; Do not use default ggplot2 colors. Try out different palettes for object colors and background colors.&lt;/li&gt;
-&lt;li&gt; If you mention something at the introduction such as "we will do this", then show it in the report. Otherwise, omit it.&lt;/li&gt;
-&lt;li&gt; In conclusion, shortly summarize your aim and findings.&lt;/li&gt;
-&lt;li&gt; In the end this is a report!..It should be appealing for people to read it!..&lt;/li&gt;
-&lt;/ul&gt; &lt;/p&gt;
----
-#### **Office Hours**
-
-- May 31, 2021 between 20:30-22:30.   
-- June 7, 2021 between 20:30-22:30.   
-- June 14, 2021 between 20:30-22:30.   
-- June 21, 2021 between 20:30-22:30.     
-
-#### **Zoom meeting link details**:
-
-
-[Join Zoom Meeting](https://itu-edu-tr.zoom.us/j/99088059412?pwd=bTNZcElreWd3Z1MyS0hvVnpLOEdrQT09)
-
-Meeting ID: 990 8805 9412  
-Passcode: 396830
-
-
 ---
 
 - Please visit the [NASA Earth Data's Covid-19 Dashboard](
@@ -101,15 +61,15 @@
 
 ---
 #### Shiny package
-- [`Shiny`](https://shiny.rstudio.com/) is an `R` package that provides elegant and powerful web framework for **building interactive web applications (apps)** directly from `R`.
+-  [R Shiny](https://shiny.rstudio.com/) is an `R` package that provides elegant and powerful web framework for **building interactive web applications (apps)** directly from `R`.
 - You can host standalone apps on a **webpage** or build **dashboards**. 
 - Shiny applications are automatically live and outputs change instantly as users modify inputs, without requiring a reload of the browser.
 - You can also extend your Shiny apps with [CSS themes](http://rstudio.github.io/shinythemes/?_ga=2.128822476.1106871023.1621587722-51308884.1621587722), [htmlwidgets](http://www.htmlwidgets.org/), and [JavaScript](https://github.com/daattali/shinyjs/blob/master/README.md) actions.
 - To install and load the package:
 
 
 ```r
-install.packages("shiny")
+#install.packages("shiny")
 library(shiny)
 ```
 
@@ -427,7 +387,7 @@
 
 
 
-- Each `render*()` function takes a single argument: an `R expression` surrounded by braces {} and and do some light pre-processing on the expression.
+- Each `render*()` function takes a single argument: an `R expression` surrounded by braces {} and do some light pre-processing on the expression.
 
 ---
 - The `R expression` can be one simple line of text, or it can involve many lines of code, as if it were a complicated function call.	
@@ -507,6 +467,8 @@
 
 - &lt;span style="color:purple"&gt;**The Human Development Index (HDI)** is a summary measure of average achievement in key dimensions of human development: a long and healthy life, being knowledgeable and have a decent standard of living. The HDI is the geometric mean of normalized indices for each of the three dimensions.&lt;/span&gt;
 
+&lt;img src="images/hdi_index.png" width="100%" /&gt;
+
 ---
 
 class: middle, center
@@ -547,7 +509,7 @@
 
 ---
 #### Example: Countries-01
-- Filter the data for the year 2011 and develop a `Shiny` app which enables to select one of variables **human_development_index**, **corruption_perception_index**, **population**, **life_exp**, and **gdp_per_capita** through a  `input widget` to plot the selected variable on the horizontal axis and also enables to select another variable  through another `input widget` to plot that selected variable on the vertical axis.
+- Filter the data for the year 2011 and develop a `Shiny` app which enables to select one of variables **human_development_index**, **corruption_perception_index**, **population**, **life_exp**, and **gdp_per_capita** through an  `input widget` to plot the selected variable on the horizontal axis and also enables to select another variable  through another `input widget` to plot that selected variable on the vertical axis.
 - Afterwards, get a scatter plot of the selected two variables and identify the points by their **continent type** by assigning different **colors**.
 
 ---
@@ -1004,7 +966,11 @@
 ---
 class: middle, center
 
-&lt;span style="color:purple"&gt;WISH YOU A GOOD WINTER BREAK!..☃️&lt;/span&gt;
+&lt;span style="color:purple"&gt;WISH YOU A GOOD FINAL EXAM WEEK &amp; WINTER BREAK!..&lt;/span&gt;
+
+&lt;br&gt;
+
+✏️ 📚  ☃️