rdata-scienceanalysiseda

Calculate the most consumed food items by Ill Patients

I have a dataset as below, which has many columns. There are some columns whose headings are :

baked_hamburgur,spinach,mashed_potato,cabbages,jello,rolls,brown,milk,coffee,water,cakes,vanilla,chocolate,fruitsalad

There are other columns as well, but I am only interested as of now in the above columns.

the value in each row of these columns is either: yes, or no.

A screenshot of this data is as under, as I am not able to attach/share this file in the question itself.

My Dataset with many columns for Data Analysis of Ill Patients

The dput(head()) output is as under: 

> dput(head(illness_data))

structure(list(Age = structure(c(18L, 26L, 22L, 25L, 29L, 13L
), .Label = c("10", "106", "11", "12", "14", "15", "16", "17", 
"18", "19", "2", "20", "22", "23", "24", "25", "26", "27", "28", 
"30", "31", "32", "33", "34", "36", "38", "39", "4", "42", "43", 
"44", "45", "46", "48", "5", "7", "8", "9", "seven"), class = "factor"), 
    sex = structure(c(3L, 2L, 3L, 3L, 2L, 3L), .Label = c("-1", 
    "Female", "Male"), class = "factor"), timesupper = c(2000L, 
    1830L, 1830L, 1930L, 1930L, 1930L), ill = structure(c(1L, 
    1L, 1L, 1L, 1L, 1L), .Label = "yes", class = "factor"), onsetdate = structure(c(4L, 
    4L, 4L, 1L, 1L, 4L), .Label = c("18-Apr", "18-Jun", "18/4", 
    "19-Apr"), class = "factor"), onsettime = c(30L, 30L, 30L, 
    2230L, 2230L, 200L), baked_hamburgur = structure(c(2L, 2L, 
    2L, 2L, 2L, 1L), .Label = c("no", "yes"), class = "factor"), 
    spinach = structure(c(2L, 2L, 2L, 2L, 2L, 1L), .Label = c("no", 
    "yes"), class = "factor"), mashed_potato = structure(c(2L, 
    2L, 1L, 1L, 2L, 1L), .Label = c("no", "yes"), class = "factor"), 
    cabbages = structure(c(1L, 2L, 1L, 2L, 1L, 1L), .Label = c("no", 
    "yes"), class = "factor"), jello = structure(c(1L, 1L, 1L, 
    2L, 2L, 1L), .Label = c("no", "yes"), class = "factor"), 
    rolls = structure(c(2L, 1L, 1L, 1L, 2L, 1L), .Label = c("no", 
    "yes"), class = "factor"), brown = structure(c(1L, 1L, 1L, 
    1L, 2L, 1L), .Label = c("no", "yes"), class = "factor"), 
    milk = structure(c(1L, 1L, 1L, 1L, 1L, 1L), .Label = c("no", 
    "yes"), class = "factor"), coffee = structure(c(2L, 2L, 2L, 
    1L, 2L, 1L), .Label = c("no", "yes"), class = "factor"), 
    water = structure(c(1L, 1L, 1L, 2L, 2L, 1L), .Label = c("no", 
    "yes"), class = "factor"), cakes = structure(c(1L, 1L, 2L, 
    1L, 1L, 1L), .Label = c("no", "yes"), class = "factor"), 
    vanilla = structure(c(2L, 2L, 2L, 2L, 2L, 2L), .Label = c("no", 
    "yes"), class = "factor"), chocolate = structure(c(1L, 2L, 
    2L, 1L, 1L, 2L), .Label = c("no", "yes"), class = "factor"), 
    fruitsalad = structure(c(1L, 1L, 1L, 1L, 1L, 1L), .Label = c("no", 
    "yes", "yes</pre></body></html>Ztext/plain\b\v\035(F]l~Ó_Ý\026R\002\001"
    ), class = "factor")), .Names = c("Age", "sex", "timesupper", 
"ill", "onsetdate", "onsettime", "baked_hamburgur", "spinach", 
"mashed_potato", "cabbages", "jello", "rolls", "brown", "milk", 
"coffee", "water", "cakes", "vanilla", "chocolate", "fruitsalad"
), row.names = c(NA, 6L), class = "data.frame")

A complete dput command output is as under: 

> dput(illness_data)

structure(list(Age = structure(c(18L, 26L, 22L, 25L, 29L, 13L, 
36L, 8L, 11L, 7L, 24L, 10L, 8L, 35L, 34L, 6L, 22L, 39L, 12L, 
9L, 36L, 17L, 9L, 20L, 37L, 27L, 32L, 30L, 21L, 24L, 3L, 18L, 
33L, 16L, 5L, 31L, 28L, 14L, 19L, 38L, 2L, 4L, 23L, 1L, 18L, 
15L), .Label = c("10", "106", "11", "12", "14", "15", "16", "17", 
"18", "19", "2", "20", "22", "23", "24", "25", "26", "27", "28", 
"30", "31", "32", "33", "34", "36", "38", "39", "4", "42", "43", 
"44", "45", "46", "48", "5", "7", "8", "9", "seven"), class = "factor"), 
    sex = structure(c(3L, 2L, 3L, 3L, 2L, 3L, 3L, 3L, 2L, 3L, 
    3L, 2L, 3L, 3L, 2L, 2L, 3L, 3L, 3L, 2L, 2L, 1L, 3L, 3L, 3L, 
    2L, 2L, 3L, 2L, 3L, 3L, 3L, 2L, 3L, 2L, 2L, 3L, 3L, 3L, 3L, 
    3L, 3L, 2L, 3L, 2L, 3L), .Label = c("-1", "Female", "Male"
    ), class = "factor"), timesupper = c(2000L, 1830L, 1830L, 
    1930L, 1930L, 1930L, 2200L, 1900L, 1930L, NA, NA, NA, NA, 
    2200L, NA, NA, NA, 2200L, NA, NA, 2200L, 2200L, NA, NA, 2200L, 
    NA, NA, NA, NA, NA, 1900L, NA, 1100L, NA, NA, NA, 2200L, 
    1930L, 1930L, 2200L, NA, NA, 1930L, 1930L, NA, NA), ill = structure(c(1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L
    ), .Label = "yes", class = "factor"), onsetdate = structure(c(4L, 
    4L, 4L, 1L, 1L, 4L, 4L, 2L, 4L, 4L, 4L, 1L, 1L, 4L, 1L, 3L, 
    1L, 4L, 1L, 1L, 4L, 4L, 1L, 1L, 4L, 1L, 4L, 4L, 1L, 4L, 4L, 
    1L, 1L, 1L, 1L, 1L, 4L, 4L, 1L, 4L, 4L, 4L, 4L, 1L, 4L, 1L
    ), .Label = c("18-Apr", "18-Jun", "18/4", "19-Apr"), class = "factor"), 
    onsettime = c(30L, 30L, 30L, 2230L, 2230L, 200L, 100L, 2300L, 
    200L, 1030L, 30L, 2215L, 2200L, 100L, 2300L, 2145L, 2145L, 
    100L, 2300L, 2100L, 100L, 100L, 2115L, 2330L, 100L, 2130L, 
    230L, 200L, 2130L, 30L, 100L, 2230L, 1500L, 2400L, 2300L, 
    2230L, 100L, 230L, 2330L, 100L, 30L, 30L, 100L, 2400L, 215L, 
    2300L), baked_hamburgur = structure(c(2L, 2L, 2L, 2L, 2L, 
    1L, 1L, 2L, 1L, 2L, 1L, 2L, 2L, 1L, 2L, 1L, 1L, 1L, 2L, 2L, 
    1L, 1L, 2L, 2L, 1L, 2L, 1L, 2L, 2L, 2L, 1L, 2L, 1L, 2L, 2L, 
    2L, 1L, 2L, 2L, 1L, 2L, 2L, 1L, 2L, 2L, 2L), .Label = c("no", 
    "yes"), class = "factor"), spinach = structure(c(2L, 2L, 
    2L, 2L, 2L, 1L, 1L, 2L, 1L, 2L, 1L, 2L, 2L, 1L, 2L, 2L, 2L, 
    1L, 2L, 2L, 1L, 1L, 2L, 2L, 1L, 1L, 1L, 2L, 2L, 2L, 1L, 2L, 
    1L, 2L, 1L, 2L, 1L, 2L, 2L, 1L, 1L, 1L, 1L, 2L, 1L, 2L), .Label = c("no", 
    "yes"), class = "factor"), mashed_potato = structure(c(2L, 
    2L, 1L, 1L, 2L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 2L, 1L, 2L, 2L, 
    2L, 1L, 2L, 2L, 1L, 1L, 2L, 1L, 1L, 2L, 1L, 1L, 2L, 1L, 1L, 
    2L, 1L, 2L, 2L, 2L, 1L, 2L, 2L, 1L, 2L, 1L, 1L, 2L, 2L, 2L
    ), .Label = c("no", "yes"), class = "factor"), cabbages = structure(c(1L, 
    2L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 1L, 2L, 1L, 
    2L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 1L, 2L, 1L, 2L, 1L, 1L, 1L, 
    2L, 1L, 2L, 1L, 2L, 1L, 1L, 2L, 1L, 2L, 2L, 1L, 2L, 1L, 2L
    ), .Label = c("no", "yes"), class = "factor"), jello = structure(c(1L, 
    1L, 1L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 2L, 1L, 
    1L, 1L, 2L, 2L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 
    1L, 1L, 2L, 1L, 2L, 1L, 1L, 2L, 1L, 2L, 2L, 1L, 2L, 2L, 2L
    ), .Label = c("no", "yes"), class = "factor"), rolls = structure(c(2L, 
    1L, 1L, 1L, 2L, 1L, 1L, 2L, 1L, 2L, 1L, 2L, 2L, 1L, 2L, 2L, 
    2L, 1L, 2L, 2L, 1L, 1L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 
    2L, 1L, 2L, 2L, 2L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L
    ), .Label = c("no", "yes"), class = "factor"), brown = structure(c(1L, 
    1L, 1L, 1L, 2L, 1L, 1L, 2L, 1L, 1L, 1L, 2L, 1L, 1L, 2L, 1L, 
    2L, 1L, 2L, 2L, 1L, 1L, 2L, 2L, 1L, 2L, 1L, 2L, 2L, 1L, 1L, 
    1L, 1L, 2L, 2L, 2L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 2L, 2L
    ), .Label = c("no", "yes"), class = "factor"), milk = structure(c(1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 
    1L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L
    ), .Label = c("no", "yes"), class = "factor"), coffee = structure(c(2L, 
    2L, 2L, 1L, 2L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 2L, 1L, 1L, 1L, 
    1L, 1L, 2L, 2L, 1L, 1L, 2L, 2L, 1L, 2L, 1L, 2L, 2L, 1L, 1L, 
    2L, 1L, 2L, 1L, 2L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 2L, 2L
    ), .Label = c("no", "yes"), class = "factor"), water = structure(c(1L, 
    1L, 1L, 2L, 2L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 2L, 1L, 2L, 2L, 
    2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 
    1L, 1L, 1L, 2L, 1L, 1L, 2L, 2L, 1L, 1L, 1L, 1L, 2L, 2L, 1L
    ), .Label = c("no", "yes"), class = "factor"), cakes = structure(c(1L, 
    1L, 2L, 1L, 1L, 1L, 2L, 1L, 1L, 2L, 1L, 1L, 2L, 2L, 2L, 2L, 
    2L, 2L, 2L, 2L, 2L, 1L, 1L, 2L, 2L, 1L, 1L, 2L, 1L, 1L, 1L, 
    1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 2L, 2L, 2L
    ), .Label = c("no", "yes"), class = "factor"), vanilla = structure(c(2L, 
    2L, 2L, 2L, 2L, 2L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
    2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 
    2L, 2L, 2L, 2L, 2L, 2L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L
    ), .Label = c("no", "yes"), class = "factor"), chocolate = structure(c(1L, 
    2L, 2L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 2L, 1L, 2L, 1L, 
    1L, 2L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 1L, 1L, 2L, NA, 1L, 1L, 
    2L, 2L, 2L, 2L, 1L, 2L, 2L, 2L, 2L, 2L, 1L, 2L, 2L, 2L, 1L
    ), .Label = c("no", "yes"), class = "factor"), fruitsalad = structure(c(1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 2L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 3L
    ), .Label = c("no", "yes", "yes</pre></body></html>Ztext/plain\b\v\035(F]l~Ó_Ý\026R\002\001"
    ), class = "factor")), .Names = c("Age", "sex", "timesupper", 
"ill", "onsetdate", "onsettime", "baked_hamburgur", "spinach", 
"mashed_potato", "cabbages", "jello", "rolls", "brown", "milk", 
"coffee", "water", "cakes", "vanilla", "chocolate", "fruitsalad"
), class = "data.frame", row.names = c(NA, -46L))

R has correctly read these columns as Factor type variable(s).

Now, each of these columns correspond to what every ill patient in a hospital has consumed.

I'd like to know the most consumed food item by ill patients, using R.

Kindly advise a good way to do so. Thanks!

Note, I have not tried any other options, than the ones mentioned in this URL below. However, I could not make it work.

Count Factor Columns Using R

Solution

  • Since all the rows have ill = 'yes' we can count in each column the number of values with yes in it. A base R approach could be : 

    head(sort(colSums(illness_data[7:20] == "yes"), decreasing = TRUE), 5)

#        vanilla baked_hamburgur           cakes         spinach   mashed_potato 
#             43              29              27              26              23

    I have selected columns 7 to 20 because those are the only columns where food item is present. Also I have selected only top 5 values, you can select any value by changing the number 5 in head command.