Menu Design Proposition for Agriculture Research Design and Data Analysis

[fran2or]

With reference to #6620, the special agriculture research menu in the current version in R-Instat is Options by Context but needs to change. The new proposed name change is Experimental . The menu has not been fully conceptualized but the main proposed frame work for its menu design is as follows:

Experimental

• Open From Library
• Field Book Design
• Check Data
  • One Variable summarise
  • One Variable Graph
  • One Variable Frequencies Tables
  • Duplicates
  • Compare Columns
  • Pivot Tables
• Prepare
  • Column Operations
    • Row Summaries (Mean , Sum, Diference, etc)
    • Combine Columns
    • Recoding Columns
  • Calculate Difference Between Options
  • Stack
  • Unstack
  • Merge Additional Data
• Define
  • On - Station
  • On - Farm
• Describe
  • Frequency Tables
  • Summary Tables
  • Compare Two Options
  • Boxplot
  • Density Plot & Histograms
  • Heat maps
• Model
  • Fit Model
  • Model Comparison

Attached is slightly more detailed document. Fully prepared and approved dialogs will follow when ready.
Experimental Data Design.docx

[derekagorhom]

@fran2or from the first R script which is the Dataframe for Treatment;
the code runs well in R studio but when used in R-instat, we need to change some parts of the code so as to produce a dataframe in R-instat.
Below is the original rcode:

Data Frame

Multiple treatement

library("tidyr")
vec1 <- c("A", "B", "AA", "CDE")    # Create example vectors
vec2 <- 1:3
crossing(vec1, vec2) 

Simple treatement

data <- data.frame(data=matrix(data=NA, nrow=10, ncol=1))

To make it run in R-instat this code should work

Create example vectors

vec1 <- c("A", "B", "AA", "CDE")    
vec2 <- 1:3

Create a crossing of vec1 and vec2

crossed_data <- crossing(treat = vec1, yield = vec2)

Import the data using data_book$import_data

data_book$import_data(data_tables = list(data3 = crossed_data))

Remove the crossed_data object from the environment

rm(crossed_data)

But even in this case that is not how the R-instat code produces new data frames:
the example below shows how we create a dataframe in R-instat.

data <- data.frame(....Code....)
data_book$import_data(data_tables=list(data=data))
rm(data)

I will try and have a meeting with lily by Monday and discuss how we can make the rcode better.

[Emmanuel-Afrifa]

I just run the codes produced above in R-INSTAT and it produces a result.

[lilyclements]

@derekagorhom thanks for explaining! So is it going to be as a new tab at the top of the "New Data Frame" dialog?

[derekagorhom]

@lilyclements yes please that is the plan since we currently do not have a way to create a dataframe for Agricultural research in R-instat

[lilyclements]

@derekagorhom Nice. Have you planned out the design of it?

[derekagorhom]

Data for treatments.odt
Yes @lilyclements above document contain the initail design.
you can have a look