diff --git a/data/Scripts/a tidy calculator r-script.R b/data/Scripts/a tidy calculator r-script.R
new file mode 100644
index 0000000..db82637
--- /dev/null
+++ b/data/Scripts/a tidy calculator r-script.R	
@@ -0,0 +1,270 @@
+# Script produced on 4 December 2024 using R-Instat Version 0.8.0.
+## A tidy calculation system practice
+
+# Creating a New Data Frame in R-Instat
+
+data <- data.frame(x1=as.numeric(rep(seq(1,1000), each=1, length.out=100)), x2=as.character(rep(NA, 100)))
+data_book$import_data(data_tables=list(data=data))
+
+rm(data)
+
+
+## The R-Instat calculator
+## A basic calculator
+
+# Doing basic calculations with the R-Instat calculator
+
+data <- data_book$get_data_frame(data_name="data", use_current_filter=FALSE)
+attach(what=data)
+scalars <- data_book$get_scalars(data_name="data")
+attach(what=scalars)
+calc <- 3 + 5
+calc
+data_book$add_scalar(data_name="data", scalar_name="calc", scalar_value=calc)
+detach(name=data, unload=TRUE)
+detach(name=scalars, unload=TRUE)
+rm(list=c("calc", "data", "scalars"))
+
+
+# Doing basic calculations with the R-Instat calculator
+
+data <- data_book$get_data_frame(data_name="data", use_current_filter=FALSE)
+attach(what=data)
+scalars <- data_book$get_scalars(data_name="data")
+attach(what=scalars)
+calc <- 3 ^ 5
+calc
+data_book$add_scalar(data_name="data", scalar_name="calc", scalar_value=calc)
+detach(name=data, unload=TRUE)
+detach(name=scalars, unload=TRUE)
+rm(list=c("calc", "data", "scalars"))
+
+
+## A column calculator
+
+# Using the R-Instat calculator to carry out column calculations: Producing a 5 times table
+
+data <- data_book$get_data_frame(data_name="data", use_current_filter=FALSE)
+attach(what=data)
+scalars <- data_book$get_scalars(data_name="data")
+attach(what=scalars)
+x2 <- x1 * 5
+data_book$add_columns_to_data(data_name="data", col_name="x2", col_data=x2, before=FALSE)
+
+detach(name=data, unload=TRUE)
+detach(name=scalars, unload=TRUE)
+data_book$append_to_variables_metadata(data_name="data", col_names="x2", property="labels", new_val="")
+rm(list=c("x2", "data", "scalars"))
+
+
+# Using the R-Instat calculator to carry out column calculations: Producing powers of 5 values
+
+data <- data_book$get_data_frame(data_name="data", use_current_filter=FALSE)
+attach(what=data)
+scalars <- data_book$get_scalars(data_name="data")
+attach(what=scalars)
+power5 <- x1 ^5
+data_book$add_columns_to_data(data_name="data", col_name="power5", col_data=power5, before=FALSE)
+
+detach(name=data, unload=TRUE)
+detach(name=scalars, unload=TRUE)
+data_book$append_to_variables_metadata(data_name="data", col_names="power5", property="labels", new_val="")
+rm(list=c("power5", "data", "scalars"))
+
+
+## The Maths Keyboard
+
+# Using the R-Instat calculator maths keyboard to carry out column calculations finding squareroots
+
+data <- data_book$get_data_frame(data_name="data", use_current_filter=FALSE)
+attach(what=data)
+scalars <- data_book$get_scalars(data_name="data")
+attach(what=scalars)
+sqrt <- sqrt(x1 )
+data_book$add_columns_to_data(data_name="data", col_name="sqrt", col_data=sqrt, before=FALSE)
+
+detach(name=data, unload=TRUE)
+detach(name=scalars, unload=TRUE)
+data_book$append_to_variables_metadata(data_name="data", col_names="sqrt", property="labels", new_val="")
+rm(list=c("sqrt", "data", "scalars"))
+
+
+## The Integer keyboard
+
+# Using the R-Instat calculator integer keyboard to carry out column calculations finding divisors
+
+data <- data_book$get_data_frame(data_name="data", use_current_filter=FALSE)
+attach(what=data)
+scalars <- data_book$get_scalars(data_name="data")
+attach(what=scalars)
+divisors <- DescTools::Divisors(x1 )
+data_book$add_columns_to_data(data_name="data", col_name="divisors", col_data=divisors, before=FALSE)
+
+detach(name=data, unload=TRUE)
+detach(name=scalars, unload=TRUE)
+data_book$append_to_variables_metadata(data_name="data", col_names="divisors", property="labels", new_val="")
+rm(list=c("divisors", "data", "scalars"))
+
+
+# Using the R-Instat calculator integer keyboard to carry out column calculations generating prime numbers
+
+data <- data_book$get_data_frame(data_name="data", use_current_filter=FALSE)
+attach(what=data)
+scalars <- data_book$get_scalars(data_name="data")
+attach(what=scalars)
+primes <- primes::generate_n_primes(n=nrow(x=data))
+data_book$add_columns_to_data(data_name="data", col_name="primes", col_data=primes, before=FALSE)
+
+detach(name=data, unload=TRUE)
+detach(name=scalars, unload=TRUE)
+data_book$append_to_variables_metadata(data_name="data", col_names="primes", property="labels", new_val="")
+rm(list=c("primes", "data", "scalars"))
+
+
+# Using the R-Instat calculator integer keyboard to carry out column calculations generating abundant numbers
+
+data <- data_book$get_data_frame(data_name="data", use_current_filter=FALSE)
+attach(what=data)
+scalars <- data_book$get_scalars(data_name="data")
+attach(what=scalars)
+abundant <- Zseq::Abundant(n=nrow(x=data), gmp=FALSE)
+data_book$add_columns_to_data(data_name="data", col_name="abundant", col_data=abundant, before=FALSE)
+
+detach(name=data, unload=TRUE)
+detach(name=scalars, unload=TRUE)
+data_book$append_to_variables_metadata(data_name="data", col_names="abundant", property="labels", new_val="")
+rm(list=c("abundant", "data", "scalars"))
+
+
+# Using the R-Instat calculator integer keyboard to carry out column calculations generating deficient numbers
+
+data <- data_book$get_data_frame(data_name="data", use_current_filter=FALSE)
+attach(what=data)
+scalars <- data_book$get_scalars(data_name="data")
+attach(what=scalars)
+deficient <- Zseq::Deficient(n=nrow(x=data), gmp=FALSE)
+data_book$add_columns_to_data(data_name="data", col_name="deficient", col_data=deficient, before=FALSE)
+
+detach(name=data, unload=TRUE)
+detach(name=scalars, unload=TRUE)
+data_book$append_to_variables_metadata(data_name="data", col_names="deficient", property="labels", new_val="")
+rm(list=c("deficient", "data", "scalars"))
+
+
+# Using the R-Instat calculator integer keyboard to carry out column calculations generating fibonacci numbers
+
+data <- data_book$get_data_frame(data_name="data", use_current_filter=FALSE)
+attach(what=data)
+scalars <- data_book$get_scalars(data_name="data")
+attach(what=scalars)
+fibonacci <- Zseq::Fibonacci(n=nrow(x=data))
+data_book$add_columns_to_data(data_name="data", col_name="fibonacci", col_data=fibonacci, before=FALSE, adjacent_column="x1")
+
+detach(name=data, unload=TRUE)
+detach(name=scalars, unload=TRUE)
+data_book$append_to_variables_metadata(data_name="data", col_names="fibonacci", property="labels", new_val="")
+rm(list=c("fibonacci", "data", "scalars"))
+
+
+## The basic keyboard
+
+# Doing basic calculations to check the ratios of the fibonacci numbers
+
+data <- data_book$get_data_frame(data_name="data", use_current_filter=FALSE)
+attach(what=data)
+scalars <- data_book$get_scalars(data_name="data")
+attach(what=scalars)
+calc <- 13 / 8
+calc
+data_book$add_scalar(data_name="data", scalar_name="calc", scalar_value=calc)
+detach(name=data, unload=TRUE)
+detach(name=scalars, unload=TRUE)
+rm(list=c("calc", "data", "scalars"))
+
+
+# Doin basic calculations to check the ratios of the fibonacci numbers
+
+data <- data_book$get_data_frame(data_name="data", use_current_filter=FALSE)
+attach(what=data)
+scalars <- data_book$get_scalars(data_name="data")
+attach(what=scalars)
+21 / 13
+detach(name=data, unload=TRUE)
+detach(name=scalars, unload=TRUE)
+rm(list=c("data", "scalars"))
+
+# Doin basic calculations to check the ratios of the fibonacci numbers
+
+data <- data_book$get_data_frame(data_name="data", use_current_filter=FALSE)
+attach(what=data)
+scalars <- data_book$get_scalars(data_name="data")
+attach(what=scalars)
+calc <- 610 / 377
+calc
+data_book$add_scalar(data_name="data", scalar_name="calc", scalar_value=calc)
+detach(name=data, unload=TRUE)
+detach(name=scalars, unload=TRUE)
+rm(list=c("calc", "data", "scalars"))
+
+
+
+#  Duplicating the fibonacci numbers Column and changing it's type to numeric 
+
+fibonacci1 <- data_book$get_columns_from_data(data_name="data", col_names="fibonacci", use_current_filter=FALSE)
+data_book$add_columns_to_data(data_name="data", col_name="fibonacci1", col_data=fibonacci1, before=FALSE, adjacent_column="fibonacci")
+
+data_book$convert_column_to_type(data_name="data", col_names="fibonacci1", to_type="integer")
+rm(fibonacci1)
+
+
+## The transform keyboard
+# Using the transform keyboard and the lag button
+
+data <- data_book$get_data_frame(data_name="data", use_current_filter=FALSE)
+attach(what=data)
+scalars <- data_book$get_scalars(data_name="data")
+attach(what=scalars)
+fibonacci2 <- dplyr::lag(fibonacci1 )
+data_book$add_columns_to_data(data_name="data", col_name="fibonacci2", col_data=fibonacci2, before=FALSE, adjacent_column="fibonacci1")
+
+detach(name=data, unload=TRUE)
+detach(name=scalars, unload=TRUE)
+data_book$append_to_variables_metadata(data_name="data", col_names="fibonacci2", property="labels", new_val="")
+rm(list=c("fibonacci2", "data", "scalars"))
+
+
+## The basic keyboard
+# Using the basic keyboard in the R-Instat calculator to generate the golden ratios
+
+data <- data_book$get_data_frame(data_name="data", use_current_filter=FALSE)
+attach(what=data)
+scalars <- data_book$get_scalars(data_name="data")
+attach(what=scalars)
+golden <- fibonacci1 / fibonacci2
+data_book$add_columns_to_data(data_name="data", col_name="golden", col_data=golden, before=FALSE, adjacent_column="fibonacci2")
+
+detach(name=data, unload=TRUE)
+detach(name=scalars, unload=TRUE)
+data_book$append_to_variables_metadata(data_name="data", col_names="golden", property="labels", new_val="")
+rm(list=c("golden", "data", "scalars"))
+
+
+# Generating a line plot for the golden ratio
+
+data <- data_book$get_data_frame(data_name="data")
+last_graph <- ggplot2::ggplot(data=data, mapping=ggplot2::aes(y=golden, x=x1)) + ggplot2::geom_line(colour="blue", size=0.8) + ggplot2::geom_point() + theme_grey()
+data_book$add_object(data_name="data", object_name="last_graph", object_type_label="graph", object_format="image", object=check_graph(graph_object=last_graph))
+data_book$get_object_data(data_name="data", object_name="last_graph", as_file=TRUE)
+rm(list=c("last_graph", "data"))
+
+
+## You can often avoid this halfway calculator dialogue until you are comfortable with the simple use of R-Instat
+
+# Using the Transform dialog instead to calculate squareroots
+
+x1 <- data_book$get_columns_from_data(data_name="data", col_names="x1", use_current_filter=FALSE)
+sqrt <- sqrt(x=x1)
+data_book$add_columns_to_data(data_name="data", col_name="sqrt", col_data=sqrt, before=FALSE, adjacent_column="x1")
+
+data_book$append_to_variables_metadata(data_name="data", col_names="sqrt", property="labels", new_val="")
+rm(list=c("sqrt", "x1"))
\ No newline at end of file
diff --git a/data/Scripts/a whole world of data.R b/data/Scripts/a whole world of data.R
new file mode 100644
index 0000000..200acc6
--- /dev/null
+++ b/data/Scripts/a whole world of data.R	
@@ -0,0 +1,147 @@
+## A whole world of data r-script practical
+# Script produced on 4 December 2024 using R-Instat Version 0.8.0.
+# Importing the diamonds data into R-Instat from the library
+
+utils::data(package="ggplot2", X=diamonds)
+data_book$import_data(data_tables=list(diamonds=diamonds))
+
+
+# Producing a Scatter Plot in R-Instat
+
+diamonds <- data_book$get_data_frame(data_name="diamonds")
+last_graph <- ggplot2::ggplot(data=diamonds, mapping=ggplot2::aes(colour=cut, y=color, x=clarity)) + ggplot2::geom_jitter(width=0.40, height=0.40) + theme_grey()
+data_book$add_object(data_name="diamonds", object_name="last_graph", object_type_label="graph", object_format="image", object=check_graph(graph_object=last_graph))
+data_book$get_object_data(data_name="diamonds", object_name="last_graph", as_file=TRUE)
+rm(list=c("last_graph", "diamonds"))
+
+
+# Create Filter subdialog: Created new filter
+data_book$add_filter(filter=list(C0=list(column="carat", operation=">", value=1)), data_name="diamonds", filter_name="filter")
+
+
+# Data Options subdialog: Set the current filter
+data_book$set_current_filter(data_name="diamonds", filter_name="filter")
+
+
+# Producing a Scatter Plot in R-Instat with filtered values of carat>1
+
+diamonds <- data_book$get_data_frame(data_name="diamonds")
+last_graph <- ggplot2::ggplot(data=diamonds, mapping=ggplot2::aes(colour=cut, x=clarity, y=color)) + ggplot2::geom_jitter(width=0.40, height=0.40) + theme_grey()
+data_book$add_object(data_name="diamonds", object_name="last_graph", object_type_label="graph", object_format="image", object=check_graph(graph_object=last_graph))
+data_book$get_object_data(data_name="diamonds", object_name="last_graph", as_file=TRUE)
+rm(list=c("last_graph", "diamonds"))
+
+
+# Importing the mydata data into R-Instat from the library
+
+utils::data(package="openair", X=mydata)
+data_book$import_data(data_tables=list(mydata=mydata))
+
+
+# Importing the efc data into R-Instat from the library
+
+utils::data(package="sjlabelled", X=efc)
+data_book$import_data(data_tables=list(efc=efc))
+
+## Datasets for specific points
+
+# Importing the datasaurus data into R-Instat from the library
+
+utils::data(package="datasauRus", X=datasaurus_dozen)
+data_book$import_data(data_tables=list(datasaurus_dozen=datasaurus_dozen))
+
+# Right click menu: Convert the dataset Column To Factor
+data_book$convert_column_to_type(data_name="datasaurus_dozen", col_names="dataset", to_type="factor")
+
+
+
+# Producing a Scatter Plot in R-Instat
+
+datasaurus_dozen <- data_book$get_data_frame(data_name="datasaurus_dozen")
+last_graph <- ggplot2::ggplot(data=datasaurus_dozen, mapping=ggplot2::aes(colour=dataset, y=y, x=x)) + ggplot2::geom_jitter(width=0.40, height=0.40) + theme_grey() + ggplot2::theme(legend.position="none") + ggplot2::facet_wrap(facets= ~ dataset, dir="h")
+data_book$add_object(data_name="datasaurus_dozen", object_name="last_graph", object_type_label="graph", object_format="image", object=check_graph(graph_object=last_graph))
+data_book$get_object_data(data_name="datasaurus_dozen", object_name="last_graph", as_file=TRUE)
+rm(list=c("last_graph", "datasaurus_dozen"))
+
+
+# Importing the simpsons_paradox data into R-Instat from the library
+
+utils::data(package="datasauRus", X=simpsons_paradox)
+data_book$import_data(data_tables=list(simpsons_paradox=simpsons_paradox))
+
+# Right click menu: Convert Column(s) To Factor
+data_book$convert_column_to_type(data_name="simpsons_paradox", col_names="dataset", to_type="factor")
+
+
+# Producing a Scatter Plot in R-Instat
+
+simpsons_paradox <- data_book$get_data_frame(data_name="simpsons_paradox")
+last_graph <- ggplot2::ggplot(data=simpsons_paradox, mapping=ggplot2::aes(colour=dataset, x=x, y=y)) + ggplot2::geom_jitter(width=0.40, height=0.40) + theme_grey() + ggplot2::theme(legend.position="none") + ggplot2::facet_wrap(facets= ~ dataset, dir="h")
+data_book$add_object(data_name="simpsons_paradox", object_name="last_graph", object_type_label="graph", object_format="image", object=check_graph(graph_object=last_graph))
+data_book$get_object_data(data_name="simpsons_paradox", object_name="last_graph", as_file=TRUE)
+rm(list=c("last_graph", "simpsons_paradox"))
+
+
+# Producing a Scatter Plot in R-Instat with a line of best fit
+
+simpsons_paradox <- data_book$get_data_frame(data_name="simpsons_paradox")
+last_graph <- ggplot2::ggplot(data=simpsons_paradox, mapping=ggplot2::aes(colour=dataset, y=y, x=x)) + ggplot2::geom_jitter(width=0.40, height=0.40) + ggplot2::geom_smooth(method="lm", se=TRUE) + theme_grey() + ggplot2::theme(legend.position="none")
+data_book$add_object(data_name="simpsons_paradox", object_name="last_graph", object_type_label="graph", object_format="image", object=check_graph(graph_object=last_graph))
+data_book$get_object_data(data_name="simpsons_paradox", object_name="last_graph", as_file=TRUE)
+rm(list=c("last_graph", "simpsons_paradox"))
+
+
+# Importing the UCBAdmissions data into R-Instat from the library
+
+utils::data(package="datasets", X=UCBAdmissions)
+data_book$import_data(data_tables=list(UCBAdmissions=UCBAdmissions))
+
+
+## Datasets from books
+
+
+
+# Importing the movielens data From the R-Instat Library
+
+utils::data(package="dslabs", X=movielens)
+data_book$import_data(data_tables=list(movielens=movielens))
+
+
+## Agriculture data
+
+# Importing the gomezsplitsplit data From the R-Instat Library
+
+utils::data(package="agridat", X=gomez.splitsplit)
+data_book$import_data(data_tables=list(gomez.splitsplit=gomez.splitsplit))
+
+
+## Data from lists
+
+
+# Importing lists of Canadian municipalities into R-Instat
+
+canadian_municipalities <- read_corpora(data=rcorpora::corpora("geography/canadian_municipalities"))
+data_book$import_data(data_tables=list(canadian_municipalities=canadian_municipalities))
+
+rm(canadian_municipalities)
+
+
+## Datasets from outside R Packages
+
+## MICS data
+
+
+# Importing the MICS Dataset into R-Instat
+#  Dataset
+# Get the current working directory
+current_dir <- getwd()
+
+# Construct the desired file path by navigating up two directories and into "Library"
+file_path <- file.path(dirname(dirname(current_dir)), "Library", "mics.RDS")
+
+# Read the RDS file
+new_RDS <- readRDS(file = file_path)
+
+# Dialog: Import Dataset
+data_book$import_RDS(data_RDS=new_RDS)
+rm(new_RDS)
diff --git a/data/Scripts/fun with lists.R b/data/Scripts/fun with lists.R
new file mode 100644
index 0000000..992bf9e
--- /dev/null
+++ b/data/Scripts/fun with lists.R	
@@ -0,0 +1,112 @@
+## Fun with lists
+# Script produced on 4 December 2024 using R-Instat Version 0.8.0.
+## Animals lists
+
+# Producing a list of dinosaurs
+
+dinosaurs <- read_corpora(data=rcorpora::corpora("animals/dinosaurs"))
+data_book$import_data(data_tables=list(dinosaurs=dinosaurs))
+
+rm(dinosaurs)
+
+
+# Using the Transform Text Column dialog to examine the length of dinosaurs names
+
+list <- data_book$get_columns_from_data(data_name="dinosaurs", col_names="list", use_current_filter=FALSE)
+length <- stringr::str_length(string=list)
+data_book$add_columns_to_data(data_name="dinosaurs", col_name="length", col_data=length, before=FALSE, adjacent_column="list")
+
+rm(list=c("length", "list"))
+
+
+# Copying the Row Numbers into a column
+
+row <- data_book$get_row_names(data_name="dinosaurs")
+data_book$add_columns_to_data(data_name="dinosaurs", col_name="row", col_data=row, before=TRUE)
+
+rm(row)
+
+
+# Sorting the lengths of the names to find out the longest name
+
+data_book$sort_dataframe(data_name="dinosaurs", col_names="length", decreasing=TRUE)
+
+
+## Food lists
+
+# Producing a list of bread and pastries
+
+breads_and_pastries <- read_corpora(data=rcorpora::corpora("foods/breads_and_pastries"))
+data_book$import_data(data_tables=list(breads_and_pastries=breads_and_pastries))
+
+rm(breads_and_pastries)
+
+
+# Producing a list of fruits
+
+fruits <- read_corpora(data=rcorpora::corpora("foods/fruits"))
+data_book$import_data(data_tables=list(fruits=fruits))
+
+rm(fruits)
+
+
+# Producing a list of vegetables
+
+vegetables <- read_corpora(data=rcorpora::corpora("foods/vegetables"))
+data_book$import_data(data_tables=list(vegetables=vegetables))
+
+rm(vegetables)
+
+
+#  Appending the food lists to create one data frame
+
+food <- dplyr::bind_rows(data_book$get_data_frame(data_name=c("breads_and_pastries","fruits","vegetables")), .id="type")
+data_book$import_data(data_tables=list(food=food))
+
+rm(food)
+
+# Right click menu: Convert Column(s) To Factor
+data_book$convert_column_to_type(data_name="food", col_names="type", to_type="factor")
+
+
+# Checking the Labels/Levels
+
+data_book$set_factor_levels(data_name="food", col_name="type", new_labels=c("breads_and_pastries","fruits","vegetables"))
+
+
+## Crossword Clues
+
+# Producing a list of word clues
+
+clues_four <- read_corpora(data=rcorpora::corpora("words/word_clues/clues_four"))
+data_book$import_data(data_tables=list(clues_four=clues_four))
+
+rm(clues_four)
+
+
+
+# Using the Count in Factor the clue number for each word
+
+variable2 <- data_book$get_columns_from_data(data_name="clues_four", col_names="variable2", use_current_filter=FALSE)
+clue <- dae::fac.nested(nesting.fac=variable2)
+data_book$add_columns_to_data(data_name="clues_four", col_name="clue", col_data=clue, before=FALSE, adjacent_column="variable2")
+
+rm(list=c("clue", "variable2"))
+
+
+# Using the Unstack dialog to make the data wider
+
+clues_four <- data_book$get_data_frame(data_name="clues_four")
+clues_four_unstacked <- tidyr::pivot_wider(data=clues_four  %>%  dplyr::select(clue, list, variable2), names_from=clue, values_from=list, names_prefix="clue")
+data_book$import_data(data_tables=list(clues_four_unstacked=clues_four_unstacked))
+
+rm(list=c("clues_four_unstacked", "clues_four"))
+
+
+# Right click menu: Delete Row(s)
+data_book$remove_rows_in_data(data_name="clues_four_unstacked", row_names="1")
+
+
+# Replacing the missing Values with blanks
+
+data_book$replace_value_in_data(data_name="clues_four_unstacked", col_names=c("clue1","clue2","clue3","clue4","clue5","clue6","clue7"), new_value="", old_is_missing=TRUE)
\ No newline at end of file
diff --git a/data/Scripts/fun with sequences.R b/data/Scripts/fun with sequences.R
new file mode 100644
index 0000000..a2f7943
--- /dev/null
+++ b/data/Scripts/fun with sequences.R	
@@ -0,0 +1,240 @@
+# Script produced on 4 December 2024 using R-Instat Version 0.8.0.
+## Fun with Sequences
+## This script will explore sequences. 
+
+## Abundant numbers
+# Understanding abundant numbers
+
+# Creating a New Data Frame
+
+data <- data.frame(x1=as.numeric(rep(seq(1,1000), each=1, length.out=500)))
+data_book$import_data(data_tables=list(data=data))
+
+rm(data)
+
+
+# Generating abundant numbers using the R-Instat calculator and the integer keyboard
+
+data <- data_book$get_data_frame(data_name="data", use_current_filter=FALSE)
+attach(what=data)
+scalars <- data_book$get_scalars(data_name="data")
+attach(what=scalars)
+abundant <- Zseq::Abundant(n=nrow(x=data), gmp=FALSE)
+data_book$add_columns_to_data(data_name="data", col_name="abundant", col_data=abundant, before=FALSE)
+
+detach(name=data, unload=TRUE)
+detach(name=scalars, unload=TRUE)
+data_book$append_to_variables_metadata(data_name="data", col_names="abundant", property="labels", new_val="")
+rm(list=c("abundant", "data", "scalars"))
+
+
+
+# Generating divisors for the abundant numbers using the R-Instat calculator and the integer keyboard
+
+data <- data_book$get_data_frame(data_name="data", use_current_filter=FALSE)
+attach(what=data)
+scalars <- data_book$get_scalars(data_name="data")
+attach(what=scalars)
+divisors <- DescTools::Divisors(abundant )
+data_book$add_columns_to_data(data_name="data", col_name="divisors", col_data=divisors, before=FALSE)
+
+detach(name=data, unload=TRUE)
+detach(name=scalars, unload=TRUE)
+data_book$append_to_variables_metadata(data_name="data", col_names="divisors", property="labels", new_val="")
+rm(list=c("divisors", "data", "scalars"))
+
+
+## Calculating abundance
+
+
+# Calculating the sum of the divisors using the R-Instat calculator and the list keyboard
+
+data <- data_book$get_data_frame(data_name="data", use_current_filter=FALSE)
+attach(what=data)
+scalars <- data_book$get_scalars(data_name="data")
+attach(what=scalars)
+sum <- sapply(  divisors ,sum)
+data_book$add_columns_to_data(data_name="data", col_name="sum", col_data=sum, before=FALSE)
+
+detach(name=data, unload=TRUE)
+detach(name=scalars, unload=TRUE)
+data_book$append_to_variables_metadata(data_name="data", col_names="sum", property="labels", new_val="")
+rm(list=c("sum", "data", "scalars"))
+
+
+
+# Calculating abundance using the R-Instat calculator 
+
+data <- data_book$get_data_frame(data_name="data", use_current_filter=FALSE)
+attach(what=data)
+scalars <- data_book$get_scalars(data_name="data")
+attach(what=scalars)
+abundance <- sum / abundant
+data_book$add_columns_to_data(data_name="data", col_name="abundance", col_data=abundance, before=FALSE)
+
+detach(name=data, unload=TRUE)
+detach(name=scalars, unload=TRUE)
+data_book$append_to_variables_metadata(data_name="data", col_names="abundance", property="labels", new_val="")
+rm(list=c("abundance", "data", "scalars"))
+
+
+## Super-abundant numbers
+
+
+# Calculating max column of the abundances using the R-Instat calculator 
+
+data <- data_book$get_data_frame(data_name="data", use_current_filter=FALSE)
+attach(what=data)
+scalars <- data_book$get_scalars(data_name="data")
+attach(what=scalars)
+max <- cummax(abundance )
+data_book$add_columns_to_data(data_name="data", col_name="max", col_data=max, before=FALSE)
+
+detach(name=data, unload=TRUE)
+detach(name=scalars, unload=TRUE)
+data_book$append_to_variables_metadata(data_name="data", col_names="max", property="labels", new_val="")
+rm(list=c("max", "data", "scalars"))
+
+
+# Calculating differences of the max column of the abundances using the R-Instat calculator 
+
+data <- data_book$get_data_frame(data_name="data", use_current_filter=FALSE)
+attach(what=data)
+scalars <- data_book$get_scalars(data_name="data")
+attach(what=scalars)
+diff <- c(NA,diff(x=max , lag = 1, differences = 1))
+data_book$add_columns_to_data(data_name="data", col_name="diff", col_data=diff, before=FALSE)
+
+detach(name=data, unload=TRUE)
+detach(name=scalars, unload=TRUE)
+data_book$append_to_variables_metadata(data_name="data", col_names="diff", property="labels", new_val="")
+rm(list=c("diff", "data", "scalars"))
+
+
+# Editing a Cell in R-Instat
+
+data_book$replace_value_in_data(data_name="data", col_name="diff", new_value=0.33, rows="1")
+
+
+# Create Filter subdialog: Created new filter
+data_book$add_filter(filter=list(C0=list(column="diff", operation=">", value=0)), data_name="data", filter_name="filter")
+
+
+# Filtering out the superabundant numbers
+
+data_book$set_current_filter(data_name="data", filter_name="filter")
+
+
+
+# Creating a New Data Frame
+
+data1 <- data.frame(x1=as.numeric(rep(seq(1,100000), each=1, length.out=100000)))
+data_book$import_data(data_tables=list(data1=data1))
+
+rm(data1)
+
+
+# Generating divisors using the R-Instat calculator and the integer keyboard
+
+data1 <- data_book$get_data_frame(data_name="data1", use_current_filter=FALSE)
+attach(what=data1)
+scalars <- data_book$get_scalars(data_name="data1")
+attach(what=scalars)
+divisor <- DescTools::Divisors(x1 )
+data_book$add_columns_to_data(data_name="data1", col_name="divisor", col_data=divisor, before=FALSE)
+
+detach(name=data1, unload=TRUE)
+detach(name=scalars, unload=TRUE)
+data_book$append_to_variables_metadata(data_name="data1", col_names="divisor", property="labels", new_val="")
+rm(list=c("divisor", "data1", "scalars"))
+
+
+
+# Calculating the sum of divisors using the R-Instat calculator and the list keyboard
+
+data1 <- data_book$get_data_frame(data_name="data1", use_current_filter=FALSE)
+attach(what=data1)
+scalars <- data_book$get_scalars(data_name="data1")
+attach(what=scalars)
+sum <- sapply(  divisor ,sum)  + x1
+data_book$add_columns_to_data(data_name="data1", col_name="sum", col_data=sum, before=FALSE)
+
+detach(name=data1, unload=TRUE)
+detach(name=scalars, unload=TRUE)
+data_book$append_to_variables_metadata(data_name="data1", col_names="sum", property="labels", new_val="")
+rm(list=c("sum", "data1", "scalars"))
+
+
+
+# Calculating the relative abundance 
+
+data1 <- data_book$get_data_frame(data_name="data1", use_current_filter=FALSE)
+attach(what=data1)
+scalars <- data_book$get_scalars(data_name="data1")
+attach(what=scalars)
+abundance <- sum / x1
+data_book$add_columns_to_data(data_name="data1", col_name="abundance", col_data=abundance, before=FALSE)
+
+detach(name=data1, unload=TRUE)
+detach(name=scalars, unload=TRUE)
+data_book$append_to_variables_metadata(data_name="data1", col_names="abundance", property="labels", new_val="")
+rm(list=c("abundance", "data1", "scalars"))
+
+
+# Calculating the cumulative maxima
+
+data1 <- data_book$get_data_frame(data_name="data1", use_current_filter=FALSE)
+attach(what=data1)
+scalars <- data_book$get_scalars(data_name="data1")
+attach(what=scalars)
+max <- cummax(abundance )
+data_book$add_columns_to_data(data_name="data1", col_name="max", col_data=max, before=FALSE)
+
+detach(name=data1, unload=TRUE)
+detach(name=scalars, unload=TRUE)
+data_book$append_to_variables_metadata(data_name="data1", col_names="max", property="labels", new_val="")
+rm(list=c("max", "data1", "scalars"))
+
+
+
+# Calculating the differences of the cumulative maxima
+
+data1 <- data_book$get_data_frame(data_name="data1", use_current_filter=FALSE)
+attach(what=data1)
+scalars <- data_book$get_scalars(data_name="data1")
+attach(what=scalars)
+super <- c(NA,diff(x=max , lag = 1, differences = 1)) > 0
+data_book$add_columns_to_data(data_name="data1", col_name="super", col_data=super, before=FALSE)
+
+detach(name=data1, unload=TRUE)
+detach(name=scalars, unload=TRUE)
+data_book$append_to_variables_metadata(data_name="data1", col_names="super", property="labels", new_val="")
+rm(list=c("super", "data1", "scalars"))
+
+
+# Replace Value In Data
+data_book$replace_value_in_data(data_name="data1", col_name="super", rows="1", new_value=TRUE)
+
+
+# Create Filter subdialog: Created new filter
+data_book$add_filter(filter=list(C0=list(column="super", operation="==", value=TRUE)), data_name="data1", filter_name="filter")
+
+
+# Filtering out the superabundant numbers
+
+data_book$set_current_filter(data_name="data1", filter_name="filter")
+
+
+# Finding the count of divisors for the super-abundant numbers
+
+data1 <- data_book$get_data_frame(data_name="data1", use_current_filter=FALSE)
+attach(what=data1)
+scalars <- data_book$get_scalars(data_name="data1")
+attach(what=scalars)
+count <- sapply(  divisor ,length)
+data_book$add_columns_to_data(data_name="data1", col_name="count", col_data=count, before=FALSE)
+
+detach(name=data1, unload=TRUE)
+detach(name=scalars, unload=TRUE)
+data_book$append_to_variables_metadata(data_name="data1", col_names="count", property="labels", new_val="")
+rm(list=c("count", "data1", "scalars"))
\ No newline at end of file
diff --git a/data/mics.RDS b/data/mics.RDS
new file mode 100644
index 0000000..f6e2e1c
Binary files /dev/null and b/data/mics.RDS differ