From Excel Table to Data Frame in R - r

Question

I need to generate a Data Frame in R from the below Excel Table.
Every time I modify one of the values from column Value the variable Score will have a different value (the cell is protected so I cannot see the formula).
The idea is to generate enough samples to check the main sources of variability, and perform some basic statistics.
I think the only way would be to manually modify the variables in the column Value and anotate the result from Score in the Dataframe.
The main issue I am having is that I am not used to work with data that has this format, and because of this I am finding difficult to visualize how should I structure the Data Frame.
I am getting stuck because the variable Score depends on 5 different Stages (where each one of them has 2 different variables) and a set of dimensions with 7 different variables.
I was trying the way I am used to create Data Frames, starting with the Vectors, but it feels wrong and I cannot see how can I represent this relationships between the different variables.
stage <- c('Inspection','Cut','Assembling','Test','Labelling','Dimensions')
variables <- c('Experience level', 'Equipement', 'User','Length','Wide','Length Body','Width Body','Tape Wing','Tape Body','Clip)
range <- c('b','m','a','UA','UB','UC') ?? not sure what to do about the range??
Could anybody help me with the logic on how this should be modelled?

Answer 1

As suggested by #Gregor, to resolve your main issue consider building a data frame of all needed values in respective columns. Then run each row to produce Score.
Specifically, to build needed data frame from inputs in Excel table, consider Map (wrapper to mapply) and data.frame constructor on equal-length list or vectors of 17 items:
Excel Table Inputs
# VECTOR OF 17 CHARACTER ITEMS
stage_list <- c(rep("Inspection", 2),
rep("Cut", 2),
rep("Assembling", 2),
rep("Test", 2),
rep("Labelling", 2),
rep("Dimensions", 7))
# VECTOR OF 17 CHARACTER ITEMS
exp_equip <- c("Experience level", "Equipement")
var_list <- c(rep(exp_equip, 3),
c("User", "Equipement"),
exp_equip,
c("Length", "Wide", "Length body", "Width body",
"Tape wing", "Tape body", "Clip"))
# LIST OF 17 VECTORS
bma_range <- c("b", "m", "a")
noyes_range <- c("no", "yes")
range_list <- c(replicate(6, bma_range, simplify=FALSE),
list(c("UA", "UB", "UC")),
replicate(3, bma_range, simplify=FALSE),
list(seq(6.5, 9.5, by=0.1)),
list(seq(11.9, 12.1, by=0.1)),
list(seq(6.5, 9.5, by=0.1)),
list(seq(4, 6, by=1)),
replicate(3, noyes_range, simplify=FALSE))
Map + data.frame
df_list <- Map(function(s, v, r)
data.frame(Stage = s, Variable = v, Range = r, stringsAsFactors=FALSE),
stage_list, var_list, range_list, USE.NAMES = FALSE)
# APPEND ALL DFS
final_df <- do.call(rbind, df_list)
head(final_df)
# Stage Variable Range
# 1 Inspection Experience level b
# 2 Inspection Experience level m
# 3 Inspection Experience level a
# 4 Inspection Equipement b
# 5 Inspection Equipement m
# 6 Inspection Equipement a
Rextester demo
Score Calculation (using unknown score_function, assumed to take three non-optional args)
# VECTORIZED METHOD
final_df$Score <- score_function(final_df$Stage, final_df$Variable, final_df$Range)
# NON-VECTORIZED/LOOP ROW METHOD
final_df$Score <- sapply(1:nrow(final_df), function(i)
score_function(final_df$Stage[i], final_df$Variable[i], final_df$Range[i])
# NON-VECTORIZED/LOOP ELEMENTWISE METHOD
final_df$Score <- mapply(score_function, final_df$Stage, final_df$Variable, final_df$Range)