Reorder Rows Using Custom Order

Arranging rows in custom order using dplyr

We can use factor to change the order in a custom way

df %>%
    arrange(factor(Reg, levels = LETTERS[c(3, 1, 2)]), desc(Res), desc(Pop))
#  Reg   Res    Pop
#1   C Urban 501638
#2   C Rural 499274
#3   A Urban 500414
#4   A Rural 500501
#5   B Urban 499922
#6   B Rural 500016

Or with match to get the index and arrange on it

df %>%
    arrange(match(Reg, c("C", "A", "B")), desc(Res), desc(Pop))

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If we have multiple columns to arrange in descending order

df %>%
     arrange_at(2:3, desc) %>%
     arrange(match(Reg, c("C", "A", "B")))

Reorder rows using custom order

First, create a vector with the letters in the desired order. Then match* the vector with the variable to be sorted. match returns indices of (first) matches, which can be plugged into slice:

library(dplyr)

# create a vector with letters in the desired order
x <- c("C", "A", "B")

DT %>%
  slice(match(x, category))
#   category b
# 1        C 3
# 2        A 1
# 3        B 2

Another way would be to convert "category" to a factor, set levels to the desired order, and use arrange:

DT %>%
  mutate(category =  factor(category, levels = x)) %>%
  arrange(category)    
#   category b
# 1        C 3
# 2        A 1
# 3        B 2

*The match method is inspired by this answer.

Reorder rows of Pandas dataframe using custom order over multiple columns

You can represent Name and Subject as categorical variables:

names = ['Dan','Tim','Ari']
subjects = ['Science','History','Math']

df = df.astype({'Name': pd.CategoricalDtype(names, ordered=True),
                'Subject': pd.CategoricalDtype(subjects, ordered=True)})

>>> df.sort_values(['Name', 'Subject'])
  Name  Subject  Test1  Test2
7  Dan  Science     58     28
8  Dan  History     10     50
6  Dan     Math     10      1
1  Tim  Science     46     78
2  Tim  History     54     61
0  Tim     Math     10      5
4  Ari  Science     83     32
5  Ari  History     39     43
3  Ari     Math     10      7

>>> df.sort_values(['Subject', 'Name'])
  Name  Subject  Test1  Test2
7  Dan  Science     58     28
1  Tim  Science     46     78
4  Ari  Science     83     32
8  Dan  History     10     50
2  Tim  History     54     61
5  Ari  History     39     43
6  Dan     Math     10      1
0  Tim     Math     10      5
3  Ari     Math     10      7

Arrange rows in custom order using R

You can make country an ordered factor.

library(dplyr)

country <- rep(c("AT","BE","CY","DE","EE"),10)
value <- seq(1, 50)

# chenged this to a vector rather than a data frame
target_cc <- c("DE","CY","BE","AT","EE")

df %>% 
  mutate(country = factor(country, levels = target_cc)) %>% 
  arrange(country)

Reordering rows in data frame (R)

You need to change the Group.1 column to factor. After that, you can use order to re-order the rows based on Group.1 as follows.

df2$Group.1 <- factor(df2$Group.1, levels = c('B', 'D', 'A', 'C', 'E', 'F'))

df3 <- df2[order(df2$Group.1), ]

df3
#   Group.1         x
# 2       B 15.333333
# 4       D  4.916667
# 1       A 14.500000
# 3       C  2.083333
# 5       E  3.500000
# 6       F 16.666667

DATA

df2 <- read.table(text = "Group.1 x
A       14.500000
B       15.333333
C       2.083333
D       4.916667
E       3.500000
F       16.666667",
                      header = TRUE, stringsAsFactors = FALSE)

Reordering rows in a tables following a custom order

Instead of replacing the values with the labels, convert the vector into ordered:

q1 <- sample(c(1:5, 77, 99), 100, T)

q1 <- ordered(q1, labels= c("Very good", "Good", "Average",
                            "Poor", "Very poor", "Unsure", "No answer"))

table(q1)

q1
Very good      Good   Average      Poor Very poor    Unsure No answer 
       15        14        13        21         9        16        12 

Reorder matrix rows by custom sort

This is sorting a matrix you can easily find this on google searching for

r sorting matrix

Have a look here

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