Finding the Maximum Value for Each Row Among 3 Columns in R

Add a variable to a data frame containing max value of each row

You can use apply. For instance:

df[, "max"] <- apply(df[, 2:26], 1, max)

Here's a basic example:

> df <- data.frame(a=1:50, b=rnorm(50), c=rpois(50, 10))
> df$max <- apply(df, 1, max)
> head(df, 2)
  a          b  c max
1 1  1.3527115  9   9
2 2 -0.6469987 20  20
> tail(df, 2)
    a          b  c max
49 49 -1.4796887 10  49
50 50  0.1600679 13  50

Finding the maximum value for each row among 3 columns in R

You can use the apply function for this like so:

df$max<-apply(X=df, MARGIN=1, FUN=max)

The MARGIN=1 argument indicated that for every row in X you wish to apply the function in FUN. If you use MARGIN=2 it will be by column or MARGIN=c(1,2) it will be both rows and columns.

Calculate the maximum value across all rows without manually typing the names of every column

You get some data:

m <- tibble(matrix(runif(1000 * 500), ncol = 500))

Make sure every column is a double, then this should ideally work:

m_with_max_col <- m %>% 
  rowwise() %>% 
  mutate(max = max(c_across(where(is.numeric))))

This also works, but might be less desirable:

m_with_max_col <- m %>% 
  rowwise() %>% 
  mutate(max = max(across()))

Solution is taken from : Row-wise operations

Select the row with the maximum value in each group based on multiple columns in R dplyr

We may get rowwise max of the 'count' columns with pmax, grouped by 'col1', filter the rows where the max value of 'Max' column is.

library(dplyr)
df1 %>% 
 mutate(Max = pmax(count_col1, count_col2) ) %>%
 group_by(col1) %>%
 filter(Max == max(Max)) %>%
 ungroup %>%
 select(-Max)

-output

# A tibble: 3 × 4
  col1   col2   count_col1 count_col2
  <chr>  <chr>       <dbl>      <dbl>
1 apple  aple            1          4
2 banana banan           4          1
3 banana bananb          4          1

We may also use slice_max

library(purrr)
df1 %>%
  group_by(col1) %>%
  slice_max(invoke(pmax, across(starts_with("count")))) %>%
  ungroup
# A tibble: 3 × 4
  col1   col2   count_col1 count_col2
  <chr>  <chr>       <dbl>      <dbl>
1 apple  aple            1          4
2 banana banan           4          1
3 banana bananb          4          1

Finding the maximum value for each row and extract column names

You can use apply like

maxColumnNames <- apply(x,1,function(row) colnames(x)[which.max(row)])

Since you have a numeric matrix, you can't add the names as an extra column (it would become converted to a character-matrix).
You can choose a data.frame and do

resDf <- cbind(data.frame(x),data.frame(maxColumnNames = maxColumnNames))

resulting in

resDf
  A B C maxColumnNames
X 1 4 7              C
Y 2 5 8              C
Z 3 6 9              C

How to select the max value of each row (not all columns) and mutate 2 columns which are the max value and name in R？

Method 1

Simply use pmax and max.col function to identify the maximum values and columns.

library(dplyr)

df %>% mutate(max = pmax(a,b), type = colnames(df)[max.col(df[,3:4]) + 2 ])

Method 2

Or first re-shape your data to a "long" format for easier manipulation. Then use mutate to extract max values and names. Finally change it back to a "wide" format and relocate columns according to your target.

df %>% 
  pivot_longer(a:b, names_to = "colname") %>% 
  group_by(lon, lat) %>% 
  mutate(max = max(value), 
         type = colname[which.max(value)]) %>% 
  pivot_wider(everything(), names_from = "colname", values_from = "value") %>% 
  relocate(max, type, .after = b)

Output

# A tibble: 4 × 6
# Groups:   lon, lat [4]
    lon   lat     a     b   max type 
  <dbl> <dbl> <dbl> <dbl> <dbl> <chr>
1   102    31     4     5     5 b    
2   103    32     3     2     3 a    
3   104    33     7     4     7 a    
4   105    34     6     9     9 b

R Create column which holds column name of maximum value for each row

You can use rowwise in dplyr and get the column names of a row that have maximum value.

library(dplyr)

df %>%
  rowwise() %>%
  mutate(Max = paste0(names(.)[c_across() == max(c_across())], collapse = '_'))

#     V1    V2    V3 Max  
#  <dbl> <dbl> <dbl> <chr>
#1     2     7     7 V2_V3
#2     8     3     6 V1   
#3     1     5     4 V2   
#4     5     7     5 V2   
#5     6     3     1 V1

In base R, you could use apply -

df$Max <- apply(df, 1, function(x) paste0(names(df)[x == max(x)],collapse = '_'))

print from specific rows with highest value from multiple columns using R Studio

First, provide a reproducible version of your data (not a picture):

dput(dta)
structure(list(A = c(45, 20, 9, 6, 6), B = c(23, 34, 7, 10, 5
), C = c(12, 15, 8, 0, 4), D = c(4, 4, 6, 0, 3), E = c(5, 6, 
3, 1, 2)), class = "data.frame", row.names = c("BOX_A", "BOX_B", 
"BOX_C", "BOX_D", "BOX_E"))

Now find which column is the maximum:

idx <- apply(dta, 1, which.max)

Now display the rows where the maximum is in the first column. This is not what you asked for but it is what your picture shows:

dta[idx==1, ]
#        A  B  C D E
# BOX_A 45 23 12 4 5
# BOX_C  9  7  8 6 3
# BOX_E  6  5  4 3 2