update

docs/learn/01.Reproducibility.Rmd

@@ -421,6 +421,61 @@ Gradual automation
 .img[![Eat the cake](img/Group.png)] 
 ]
 
+---
+
+## The Reproducible Research Manisfesto
+
+ 1. For every result, **keep track** of how it was produced
+
+ 2. **Avoid manual data manipulation** steps
+
+ 3. **Archive** the exact versions of all external programs used
+
+ 4. **Version control** all custom scripts
+
+ 5. **Record all intermediate results**, when possible in standardized formats
+
+ 6. For analyses that include randomness, **note underlying random seeds**
+
+ 7. Always **store raw data** behind plots
+
+ 8. Generate hierarchical analysis output, allowing layers of increasing detail to be inspected
+
+ 9.  Connect **textual statements** to underlying results
+
+ 10. Provide **public access** to scripts, runs, and results
+
+---
+
+##   From "click" to "script"
+
+.pull-left[
+
+Using the right combination of packages, you can integrate all necessary data analysis steps into **scripts**:
+
+
+ * Data management (clean, recode, merge, reshape)
+
+ * Data analysis (test, regression, multivariate analysis, etc...)
+
+ * Data visualisation (plot, map, graph...)
+
+ * Writing up results (report and presentation generation)
+]
+
+.pull-right[ 
+
+![](img/analysis.png)
+
+More on reproducible analysis [here](https://ropensci.github.io/reproducibility-guide/sections/introduction/)
+
+]
+
+---
+
+## Save time and minimize space for errors...
+
+![](img/exhausted.png)
 
 ---
 class: inverse, center, middle
@@ -434,5 +489,9 @@ class: inverse, center, middle
 
 [post Feedback here](https://github.com/unhcRverse/unhcrverse/issues/new?assignees=&labels=enhancement&projects=&template=comment_prex_1_reproducibility.md&title=%5Blearn%5D)
 
-
+---
+
+## Let install R & Rstudio...
+
+
 

docs/learn/02.Tidyverse.Rmd

@@ -69,6 +69,101 @@ https://towardsdatascience.com/the-stages-of-learning-data-science-3cc8be181f54
 
 See Video - https://www.youtube.com/watch?v=hpMc6TgT34I 
 
+---  
+
+## Essential Concept: Objects & Data elements
+
+-  `Vectors` are a core data structure in R, and are created with `c()`. Elements in a vector must be of the same type.
+
+-  `Data.frame` where each column is a vector, but adjacent vectors can hold different things
+
+- `Matrix` just like a data frame except it's all numeric
+
+- `List` are made of any dimension, mix and match
+
+- `Factors` are a special class that R uses for categorical variables, which also allows for value labeling and ordering.
+
+Reference link on [Manipulating data](http://www.cookbook-r.com/Manipulating_data/)
+
+
+---
+
+## Vector Example
+
+```{r eval=FALSE}
+  numbers = c(23, 13, 5, 7, 31)
+  names = c("mohammed", "hussein", "ali")
+
+#Elements are indexed starting at 1, and are accessed with `[]` notation.
+	numbers[1] # 23
+	names[1] # mohammed
+```
+
+---  
+
+## PART 2: Data frames
+
+[Data frames](http://www.r-tutor.com/r-introduction/data-frame)
+
+```{r eval=FALSE}
+    books = data.frame(
+        title = c("harry potter", "war and peace", "lord of the rings"),
+        author = c("rowling", "tolstoy", "tolkien"),
+        num_pages = c("350", "875", "500")
+    )
+
+# you can access columns of a data frame with `$`.
+	books$title # c("harry potter", "war and peace", "lord of the rings")
+	books$author[1] # "rowling"
+
+#You can also create new columns with `$`.
+	books$num_bought_today = c(10, 5, 8)
+	books$num_bought_yesterday = c(18, 13, 20)
+	books$total_num_bought = books$num_bought_today + books$num_bought_yesterday
+```
+
+---
+
+## Load a Data Frame
+
+``` {r eval=FALSE}
+
+data(CASchools)
+mydata <- CASchools
+
+# load a data set from csv and assign it to an object called 'mydata'
+#mydata <- read.csv("unhcr_mass_comm_db_merged_20140612.csv") 
+
+# first few rows of the dataset
+head(mydata)
+
+# last few rows
+tail(mydata)
+
+# variable names
+colnames(mydata)
+
+# pop-up view of entire data set (uncomment to run)
+# View(mydata)
+
+```
+
+---
+
+## Initial Exploration
+
+```{r eval=FALSE}
+# dimension of the data frame
+dim(mydata)
+
+# Structure of the data frame of all variables
+# this includes the class(type) i.e factor or not
+str(mydata)
+
+# summary statistics with means for every variable
+summary(mydata)
+```
+
 
 ---
 class: inverse, center, middle
@@ -377,6 +472,18 @@ class: inverse, center, middle
 You provide the data, tell ggplot2 how to map variables to aesthetics, what graphical primitives to use, and it takes care of the details.
 What does it take to create a graphic? Data, axis, geometric objects, etc.
 
+
+## Decomposition of a Graphic
+
+The **"grammar of graphics"** is a [conceptual description](https://ramnathv.github.io/pycon2014-r/visualize/ggplot2.html) of all potential graphs. It can be summarized as follows:
+
+```
+-  plot ::= coord scale+ facet? layer+
+
+-  layer ::= data mapping stat geom position?
+```
+![](img/ggplot2-anatomy-all-annotated.png) 
+
 ---
 
 ## Structure of `ggplot2`
@@ -1387,4 +1494,14 @@ class: inverse, center, middle
 - [A ggplot2 tutorial for beautiful plotting in R](https://www.cedricscherer.com/2019/08/05/a-ggplot2-tutorial-for-beautiful-plotting-in-r/) and [ggplot Wizardry Hands-On](https://z3tt.github.io/OutlierConf2021/) by Cedric Scherer
 - Ggplot workshop [Part1](https://www.youtube.com/watch?v=h29g21z0a68)/[Part2](https://www.youtube.com/watch?v=0m4yywqNPVY) by Thomas Lin Pedersen (one of the main maintainer of ggplot)
 
+
+---
+
+# Excercise
+
+Check the last #tidytuesday submission on Refugee 
+
+https://twitter.com/search?q=%20%23TidyTuesday%20refugees&src=typed_query
+
+Select a chart and try to reproduce it!!
 

docs/learn/03.Functions.Rmd

@@ -50,6 +50,9 @@ Collaboration
 
 ## Transition from Scripts to Functions
 
+
+.pull-left[
+
 Script Example
 
 ```{r}
@@ -59,6 +62,11 @@ mean_value <- mean(data)
 print(mean_value)
 ```
 
+
+]
+
+.pull-right[
+
 
 
 Function Example
@@ -76,15 +84,23 @@ mean_value <- calculate_mean(data)
 print(mean_value)
 ```
 
+]
 
 ---
 
 ## Key Differences
 
+
+.pull-left[
+
   * Functions encapsulate code into reusable units.
   * Parameters allow customization of function behavior.
 
-Creating Functions in R
+
+]
+
+.pull-right[
+
 Function Structure
 
 ```{r}
@@ -95,11 +111,27 @@ function_name <- function(parameter1, parameter2, ...) {
   return(result)
 }
 ```
+]
 
 ---
 
 ## Example: Custom Function
 
+
+.pull-left[
+
+ 1. Takes an input
+
+ 2. Apply a transformation
+
+ 3. Generates an output
+
+
+]
+
+.pull-right[
+
+
 ```{r}
 
 # Custom function to calculate the median of a numeric vector
@@ -108,7 +140,7 @@ calculate_median <- function(data) {
   return(median_value)
 }
 ```
-
+]
 
 ---
 
@@ -124,20 +156,23 @@ print(median_value)
 
 ---
 
-## Import Data
+## Import Data 
 
 
-- Data import: [`readr`](https://readr.tidyverse.org/), [`readxl`](https://readxl.tidyverse.org/), etc.
+from Excel - [`readxl`](https://readxl.tidyverse.org/),
 
 
----
+from Text: [`readr`](https://readr.tidyverse.org/),  etc.
+
 
-## Start with Documentation 
+---
 
-Why Document Functions?
+## Why Document Functions?
 
   * Documentation provides information on how to use a function.
+
   * Helps other users (including your future self) understand the purpose and usage of the function.
+
   * Standard practice for sharing code.
 
 R Documentation
@@ -259,9 +294,9 @@ Example with Custom Parameters
 
 ---
 
-## Conclusion: Key Takeaways
+## Key Takeaways
 
-  * Functions are essential for code reusability and modularity.  
+  * Functions are essential for code re-usability and modularity.  
 
   * Transition from scripts to functions for better code organization. 
 
@@ -288,7 +323,7 @@ class: inverse, center, middle
 
 ---
 
-## Reference:  
+# Reference
 
  - [Build Advanced Charts in R](https://wd3.myworkday.com/unhcr/learning/course/efee8410b2b410017044140f1aeb0001?type=9882927d138b100019b928e75843018d)
 
@@ -300,4 +335,10 @@ class: inverse, center, middle
 
  - [R for Data Science](https://r4ds.had.co.nz/), 
 
- - [Advanced R Programming](https://adv-r.hadley.nz/)
+ - [Advanced R Programming](https://adv-r.hadley.nz/)
+
+---
+
+# Excercise
+
+Use the char your previously created and turn it into a function with parameters

docs/learn/04.SurveyToolbox.Rmd

@@ -285,10 +285,10 @@ App Maturity: __beta-version__
 
 ---
 
-##  How to finalise and maintain such Toolbox
+##  How to finalise and maintain such Toolbox...
 .pull-left[
 
-The regular Standard Multi-Tier IT Standard Support model...
+Applying Standard Multi-Tier IT Standard Support model...
 
   * __Tier 4__: Code Review & Quality Insurance (_Contracted Company with frame agreement_)