Combines possible values for Thiamine heirachically so the most suitable is the one used. Considers Thiamine and Thiamine Hydrochloride.
Usage
THIAmg_combiner(
df,
THIAmg_column = "THIAmg",
THIAHCLmg_column = "THIAHCLmg",
comment = TRUE,
comment_col = "comments"
)Arguments
- df
Required - the data.frame the data is currently stored in.
- THIAmg_column
Required - default:
'THIAmg'- The name of the column containing Thiamine, vitamin B1 analysed and expressed as Thiamine in mg per 100g of EP.- THIAHCLmg_column
Required - default:
'THIAHCLmg'- The name of the column containing THIAHCLmg hydrochloride, vitamin B1 analysed and expressed as Thiamine hydrochloride in mg per 100g of EP.- comment
Required - default:
TRUE-TRUEorFALSE. If comment is set toTRUE(as it is by default), when the function is run a comment describing the source of theTHIAmg_combinedcolumn is added to the comment_col. If no comment_col is selected, andcomment = TRUE, one is created.- comment_col
Optional - default:
'comments'- A potential input variable; the column which contains the metadata comments for the food item in question. Not required if the comment parameter is set toFALSE. If set to true, and the comment_col entry is not found in the df, it will create a column with the name of the entry.
Value
Original data.frame with a new THIAmg_combined column, and
(depending on the options selected) an additional comment/comments column
and comment.
Examples
#' # Two example data.frames have been created to give an example of
# using the THIAmg_combiner; one with the expected inputs, another with custom
# inputs.
breakfast_df <- breakfast_df[, c("food_code", "food_name", "THIAmg", "THIAHCLmg",
"comments")]
breakfast_df
#> food_code food_name THIAmg THIAHCLmg comments
#> 1 F0001 Bacon 32 21
#> 2 F0002 Beans 90 45 These are imaginary food items
#> 3 F0003 Toast 130 20 <NA>
#> 4 F0004 Mushroom 21 69 With imaginary nutrient values
#> 5 F0005 Eggs <NA> 42
#> 6 F0006 Tomato 61 150 And blanks
#> 7 F0007 Sausage 21 23 <NA>
#> 8 F0008 Butter 30 To test different outputs
#> 9 F0009 Brown Sauce 59 52
#> 10 F0010 Tomato Ketchup <NA> NA And scenarios
# We start with a data.frame containing patchy values between THIAmg and THIAHCLmg. Ideally
# we would like to combine these into a single 'combined' column with as few gaps
# as possible. This is the purpose of the THIAmg_combiner.
THIA_results <- THIAmg_combiner(breakfast_df)
#> ---------------------------
#>
#> Breakdown of values used:
#>
#> No suitable value for THIAmg_combined found
#> 1
#> THIAmg_combined equal to THIAHCLmg
#> 2
#> THIAmg_combined equal to THIAmg
#> 7
#>
#> ---------------------------
THIA_results
#> food_code food_name THIAmg THIAHCLmg
#> 1 F0001 Bacon 32 21
#> 2 F0002 Beans 90 45
#> 3 F0003 Toast 130 20
#> 4 F0004 Mushroom 21 69
#> 5 F0005 Eggs <NA> 42
#> 6 F0006 Tomato 61 150
#> 7 F0007 Sausage 21 23
#> 8 F0008 Butter 30
#> 9 F0009 Brown Sauce 59 52
#> 10 F0010 Tomato Ketchup <NA> NA
#> comments
#> 1 THIAmg_combined equal to THIAmg
#> 2 These are imaginary food items; THIAmg_combined equal to THIAmg
#> 3 THIAmg_combined equal to THIAmg
#> 4 With imaginary nutrient values; THIAmg_combined equal to THIAmg
#> 5 THIAmg_combined equal to THIAHCLmg
#> 6 And blanks; THIAmg_combined equal to THIAmg
#> 7 THIAmg_combined equal to THIAmg
#> 8 To test different outputs; THIAmg_combined equal to THIAHCLmg
#> 9 THIAmg_combined equal to THIAmg
#> 10 And scenarios; No suitable value for THIAmg_combined found
#> THIAmg_combined
#> 1 32
#> 2 90
#> 3 130
#> 4 21
#> 5 42
#> 6 61
#> 7 21
#> 8 30
#> 9 59
#> 10 <NA>
# Note how there is now a new THIAmg_combined column, with values filled in
# from the THIAmg and THIAHCLmg columns, depending on which is most appropriate.
# A comment has also been added to the comments column detailing this change.
# This works without any input beyond the data.frame containing the nutrition
# information because the function is expecting standard column names, comprised
# of the nutrient INFOODS Tagname and the unit. However, if the columns are not
# named this way, then the user must specify which column relates to which input.
# An example of this is shown below.
breakfast_df_nonstandard <- breakfast_df_nonstandard[, c("food_code", "food_name",
"Thiamine_milligrams", "Thiamine_from_HCL_milligrams", "comments_column")]
breakfast_df_nonstandard
#> food_code food_name Thiamine_milligrams Thiamine_from_HCL_milligrams
#> 1 F0001 Bacon 32 21
#> 2 F0002 Beans 90 45
#> 3 F0003 Toast 130 20
#> 4 F0004 Mushroom 21 69
#> 5 F0005 Eggs <NA> 42
#> 6 F0006 Tomato 61 150
#> 7 F0007 Sausage 21 23
#> 8 F0008 Butter 30
#> 9 F0009 Brown Sauce 59 52
#> 10 F0010 Tomato Ketchup <NA> NA
#> comments_column
#> 1
#> 2 These are imaginary food items
#> 3 <NA>
#> 4 With imaginary nutrient values
#> 5
#> 6 And blanks
#> 7 <NA>
#> 8 To test different outputs
#> 9
#> 10 And scenarios
# You can see how the column names are different. The values remain the same
# however.
# To use these non-standard names, you must specify each input - as shown below.
THIA_results_nonstandard <- THIAmg_combiner(breakfast_df_nonstandard,
THIAmg_column = "Thiamine_milligrams",
THIAHCLmg_column = "Thiamine_from_HCL_milligrams",
comment_col = "comments_column")
#> ---------------------------
#>
#> Breakdown of values used:
#>
#> No suitable value for THIAmg_combined found
#> 1
#> THIAmg_combined equal to THIAHCLmg
#> 2
#> THIAmg_combined equal to THIAmg
#> 7
#>
#> ---------------------------
THIA_results_nonstandard
#> food_code food_name Thiamine_milligrams Thiamine_from_HCL_milligrams
#> 1 F0001 Bacon 32 21
#> 2 F0002 Beans 90 45
#> 3 F0003 Toast 130 20
#> 4 F0004 Mushroom 21 69
#> 5 F0005 Eggs <NA> 42
#> 6 F0006 Tomato 61 150
#> 7 F0007 Sausage 21 23
#> 8 F0008 Butter 30
#> 9 F0009 Brown Sauce 59 52
#> 10 F0010 Tomato Ketchup <NA> NA
#> comments_column
#> 1 THIAmg_combined equal to THIAmg
#> 2 These are imaginary food items; THIAmg_combined equal to THIAmg
#> 3 THIAmg_combined equal to THIAmg
#> 4 With imaginary nutrient values; THIAmg_combined equal to THIAmg
#> 5 THIAmg_combined equal to THIAHCLmg
#> 6 And blanks; THIAmg_combined equal to THIAmg
#> 7 THIAmg_combined equal to THIAmg
#> 8 To test different outputs; THIAmg_combined equal to THIAHCLmg
#> 9 THIAmg_combined equal to THIAmg
#> 10 And scenarios; No suitable value for THIAmg_combined found
#> THIAmg_combined
#> 1 32
#> 2 90
#> 3 130
#> 4 21
#> 5 42
#> 6 61
#> 7 21
#> 8 30
#> 9 59
#> 10 <NA>
# You can see from the results that the calculation is run in exactly the same
# way, with the changed column names.