CODEWITHSUNDEEP
rdataframesapply
user869097
user869097

Reputation: 1362

Get the value with most occurrences in data frame for each row

Suppose I have a simple data frame

test_df <- data.frame(c(0,0,1,0,0,1,1,1,1,1),c(1,0,0,0,0,0,0,0,0,0))

I want to get which number (0 or 1) is the maximum for each row. In my example 1 for the first vector (6 occurrences), 0 for the second one (9 occurrences).

I started with:

> sapply(test_df,table)
  c.0..0..1..0..0..1..1..1..1..1. c.1..0..0..0..0..0..0..0..0..0.
0                               4                               9
1                               6                               1

so far looks fine. Then

> sapply((sapply(test_df,table)),max)
[1] 4 6 9 1

I got lost, did I loose the associations? 1 -> 6 , 0 -> 9 What I want is to have returned a vector with the "winner": 1,0,...

1 for the first vector (6 occurrences)
0 for the second vector (9 occurrences)
...

Upvotes: 3

Views: 1117

Answers (2)

SymbolixAU
SymbolixAU

Reputation: 26248

This can be done in one apply statement. Although, it's unclear whether you want the maximum occurrences for each row or column, so here's both (using @akrun 's cleaner data set), returning a vector showing the 'winner' (either 1 or 0) for each row/column.

## Data
test_df <- data.frame(v1= c(0,0,1,0,0,1,1,1,1,1),
                      v2= c(1,0,0,0,0,0,0,0,0,0),
                      v3= c(1,0,0,0,0,0,0,0,0,1)) 
#    v1 v2 v3
# 1   0  1  1
# 2   0  0  0
# 3   1  0  0
# 4   0  0  0
# 5   0  0  0
# 6   1  0  0
# 7   1  0  0
# 8   1  0  0
# 9   1  0  0
# 10  1  0  1

## Solution - For each row
apply(test_df, 1, function(x) { sum(sum(x == 1) > sum(x == 0)) })

## Result
# [1] 1 0 0 0 0 0 0 0 0 1

## Solution - For each column
apply(test_df, 2, function(x) { sum(sum(x == 1) > sum(x == 0)) })

## Result 
# v1 v2 v3 
# 1  0  0

Upvotes: 2

akrun
akrun

Reputation: 886938

We can use apply with MARGIN=1 to extract the max value from each row of the sapply output.

frqCol <- sapply(test_df, table)
apply(frqCol, 1, max)
# 0 1 
# 9 6

or use rowMaxs from matrixStats

library(matrixStats)
rowMaxs(frqCol)
#[1] 9 6

If we need the 'max' value per column

apply(frqCol, 2, max)

and 

colMaxs(frqCol)

With the new example

test_df <- data.frame(v1= c(0,0,1,0,0,1,1,1,1,1),
                  v2= c(1,0,0,0,0,0,0,0,0,0),
                  v3= c(1,0,0,0,0,0,0,0,0,1)) 
frqCol <- sapply(test_df, table)
apply(frqCol, 2, max)
#v1 v2 v3 
#6  9  8 
colMaxs(frqCol)
#[1] 6 9 8

Upvotes: 2

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