R - Rank Largest to Smallest

rank and order in R

set.seed(1)
x <- sample(1:50, 30)    
x
# [1] 14 19 28 43 10 41 42 29 27  3  9  7 44 15 48 18 25 33 13 34 47 39 49  4 30 46  1 40 20  8
rank(x)
# [1]  9 12 16 25  7 23 24 17 15  2  6  4 26 10 29 11 14 19  8 20 28 21 30  3 18 27  1 22 13  5
order(x)
# [1] 27 10 24 12 30 11  5 19  1 14 16  2 29 17  9  3  8 25 18 20 22 28  6  7  4 13 26 21 15 23

rank returns a vector with the "rank" of each value. the number in the first position is the 9th lowest. order returns the indices that would put the initial vector x in order.

The 27th value of x is the lowest, so 27 is the first element of order(x) - and if you look at rank(x), the 27th element is 1.

x[order(x)]
# [1]  1  3  4  7  8  9 10 13 14 15 18 19 20 25 27 28 29 30 33 34 39 40 41 42 43 44 46 47 48 49

Sort a data frame in R largest to smallest from value in a column

Could you please try following and let me know if this helps you.

library(dplyr)
df[with(df, order(-Letter)), ] %>% select (Number)

Output will be as follows.

6      F
5      E
4      D
3      C
2      B
1      A
> 

Data created by as follows:

df <- data.frame(
  v1 = c('A','B','C','D','E','F'),
  v2 = c(1,2,3,4,5,6),
  v3 = c(11,12,12.5,11.5,11.75,13)
)
colnames(df)<-c("Number","Letter","Age")

Trouble using dplyr::order to rank values from smallest to largest including positive integers smaller than 1

We need rank instead of order. According to ?rank

Returns the sample ranks of the values in a vector.

library(dplyr)
data %>%
       group_by(pitch_2) %>% 
       mutate(rank = order(euclid_dist))
# A tibble: 6 x 4
# Groups:   pitch_2 [1]
#  pitch_1   pitch_2   euclid_dist  rank
#  <chr>     <chr>           <dbl> <dbl>
#1 429721-CU 493247-SI        2.53     2
#2 114849-FC 493247-SI        3.52     6
#3 430599-FF 493247-SI        3.49     5
#4 458567-FF 493247-SI        2.59     3
#5 435261-CU 493247-SI        3.1      4
#6 425629-CU 493247-SI        2.14     1

data

data <- structure(list(pitch_1 = c("429721-CU", "114849-FC", "430599-FF", 
"458567-FF", "435261-CU", "425629-CU"), pitch_2 = c("493247-SI", 
"493247-SI", "493247-SI", "493247-SI", "493247-SI", "493247-SI"
), euclid_dist = c(2.53, 3.52, 3.49, 2.59, 3.1, 2.14), rank = c(15L, 
6L, 14L, 27L, 8L, 17L)), class = "data.frame", row.names = c("1", 
"2", "3", "4", "5", "6"))

How to rank within groups in R?

You can do this pretty cleanly with dplyr

library(dplyr)
df %>%
    group_by(customer_name) %>%
    mutate(my_ranks = order(order(order_values, order_dates, decreasing=TRUE)))

Source: local data frame [5 x 4]
Groups: customer_name

  customer_name order_dates order_values my_ranks
1          John  2010-11-01           15        3
2           Bob  2008-03-25           12        1
3          Alex  2009-11-15            5        1
4          John  2012-08-06           15        2
5          John  2015-05-07           20        1

Create a ranking variable with dplyr?

It sounds like you're looking for dense_rank from "dplyr" -- but applied in a reverse order than what rank normally does.

Try this:

df %>% mutate(rank = dense_rank(desc(score)))
#   name score rank
# 1    A    10    1
# 2    B    10    1
# 3    C     9    2
# 4    D     8    3

Ranking continuous data in decreasing order

Simply give a minus before df0:

t(apply(-df0, 1, rank))
#     x1 x2 x3 x4
#[1,]  4  2  3  1
#[2,]  4  3  2  1
#[3,]  1  3  2  4
#[4,]  3  4  2  1
#[5,]  1  4  2  3

Difference between sort(), rank(), and order()

sort() sorts the vector in an ascending order.

rank() gives the respective rank of the numbers present in the vector, the smallest number receiving the rank 1.

order() returns the indices of the vector in a sorted order.

for example: if we apply these functions are applied to the vector - c (3, 1, 2, 5, 4)

sort(c (3, 1, 2, 5, 4)) will give c(1,2,3,4,5)

rank(c (3, 1, 2, 5, 4)) will give c(3,1,2,5,4)

order(c (3, 1, 2, 5, 4)) will give c(2,3,1,5,4).
if you put these indices in this order, you will get the sorted vector. Notice how v[2] = 1, v[3] = 2, v[1] = 3, v[5] = 4 and v[4] = 5

also there is a tie handling method in R. If you run rank(c (3, 1, 2, 5, 4, 2)) it will give Rank 1 to 1, since there are two 2 present R will rank them on 2 and 3 but assign Rank 2.5 to each of them, next 3 will get Rank 4.0, so

rank(c (3, 1, 2, 5, 4, 2)) will give you output [4.0 1.0 2.5 6.0 5.0 2.5]

Hope this is helpful.

in r, how to rank dataframe some columns descending and other columns ascending based on lists elements?

Another option is to use map to do this simultaneously by creating a column of 1, -1s

library(dplyr)
library(tidyr)
library(purrr)
library(stringr)
tibble(col1 = list(Asclist1, Deslist2), col2 = c(1, -1)) %>% 
    unnest_longer(col1) %>% 
    group_split(col2) %>%
    map_dfc(~ DF1 %>% 
              mutate(tmp = first(.x$col2)) %>% 
              select(one_of(.x$col1), tmp)  %>% 
              transmute_at(vars(-tmp), list(rank = ~rank(tmp * .)))) %>% 
   bind_cols(DF1, .)
# name sex age grade income score age_rank grade_rank income_rank score_rank
#1 john   m  99    96     59    99      1.0          1           4        5.0
#2 adam   m  46    46     36    46      3.0          4           3        3.0
#3  leo   m  23    63     93    23      4.5          2           5        1.5
#4 lena   f  54    54     34    54      2.0          3           2        4.0
#5   Di   f  23    23     23    23      4.5          5           1        1.5
#Warning message:
#Unknown columns: `spending` 

It would also notify the unknown columns as a warning

Update

If there is a single column with transmute_at, it would not add the name in list as suffix. To bypass that, we can create a function with rename_if

f1 <- function(dat) {
     nm1 <- setdiff(names(dat), "tmp")   
     n1 <- length(nm1)
    

      dat %>%
          transmute_at(vars(-tmp), list(rank = ~rank(tmp * .))) %>%
          rename_if(rep(n1 == 1, n1), ~ str_c(nm1, "_", .))       
                               
    }
            

tibble(col1 = list(Asclist1, Deslist2), col2 = c(1, -1)) %>% 
     unnest_longer(col1) %>% 
     group_split(col2) %>%
     map_dfc(~ DF1 %>% 
               mutate(tmp = first(.x$col2)) %>% 
               select(one_of(.x$col1), tmp)  %>% 
               f1(.)) %>% 
    bind_cols(DF1, .)
#  CAT           PN         SP Quantity Price amount amount_rank Quantity_rank Price_rank
#    1  sweets          gum    trident       23    10     23         9.5           3.5          1
#    2  sweets          gum    clortes       34    20     34         6.0           7.0          3
#    3  sweets     biscuits    loacker       23    26     23         9.5           3.5          6
#    4  sweets     biscuits        tuc       23    22     23         9.5           3.5          4
#    5  sweets         choc aftereight       54    51     54         3.0          10.0          9
#    6  sweets         choc      lindt       32    52     32         7.0           6.0         10
#    7  drinks    hotdrinks        tea       45    45     45         4.0           9.0          8
#    8  drinks    hotdrinks  green tea       23    23     23         9.5           3.5          5
#    9  drinks       juices     orange       12    12     12        12.0           1.0          2
#    10 drinks       juices      mango       56    56     56         2.0          11.0         11
#    11 drinks energydrinks powerhorse       76    76     76         1.0          12.0         12
#    12 drinks energydrinks    redbull       43    43     43         5.0           8.0          7

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