Count the number of consecutive occurrences in a vector - r

I have the following vector:
vec <- c(28, 44, 45, 46, 47, 48, 61, 62, 70, 71, 82, 83, 104, 105, 111, 115, 125, 136, 137, 138, 146, 147, 158, 159, 160, 185, 186, 187, 188, 189, 190, 191, 192, 193, 209, 263, 264, 265, 266, 267, 268, 280, 283, 284, 308, 309, 318, 319, 324, 333, 334, 335, 347, 354)
Now I would like to get the number of consecutive occurrences in the vector of the minimum length two.
So here this would be valid for the following cases:
44, 45, 46, 47, 48
61, 62
70, 71
82, 83
104, 105
136, 137, 138
146, 147
158, 159, 160
185, 186, 187, 188, 189, 190, 191, 192, 193
263, 264, 265, 266, 267, 268
283, 284
308, 309
318, 319
333, 334, 335
So there are 14 times cases of consecutive numbers, and I just need the integer 14 as output.
Anybody with an idea how to do that?


We can use rle and diff functions :
a=rle(diff(vec))
sum(a$values==1)


diff and split will help
vec2 <- split(vec, cumsum(c(1, diff(vec) != 1)))
vec2[(sapply(vec2, function(x) length(x))>1)]
$`2`
[1] 44 45 46 47 48
$`3`
[1] 61 62
$`4`
[1] 70 71
$`5`
[1] 82 83
$`6`
[1] 104 105
$`10`
[1] 136 137 138
$`11`
[1] 146 147
$`12`
[1] 158 159 160
$`13`
[1] 185 186 187 188 189 190 191 192 193
$`15`
[1] 263 264 265 266 267 268
$`17`
[1] 283 284
$`18`
[1] 308 309
$`19`
[1] 318 319
$`21`
[1] 333 334 335


Brut force :
var <- sort(var)
nconsecutive <- 0
p <- length(var)-1
for (i in 1:p){
if((var[i + 1] - var[i]) == 1){
consecutive <- consecutive + 1
}else{
# If at least one consecutive number
if(consecutive > 0){
# when no more consecutive numbers add one to your increment
nconsecutive = nconsecutive + 1
}
# Re set to 0 your increment
consecutive <- 0
}
}


Here's another base R one-liner using tapply -
sum(tapply(vec, cumsum(c(TRUE, diff(vec) != 1)), length) > 1)
#[1] 14

Related

Piping in R :: Passing specific vector elements when feeding next function's arguments [duplicate]

This question already has an answer here:
Pipe a data frame to a function whose argument pipes a dot
(1 answer)
Closed 3 years ago.
Using piping in R (with %>%), how can one pass specific vector elements from a function's output to feed the next function's arguments?
I've tried using the dot operator with position in braces (i.e., .[1], .[2]) to no avail.
The only way that was working for me was with sapply(), but I'm wondering whether there's a simpler solution I'm missing.
Example
#I have a vector containing a sequence of numbers, with some duplicates and gaps,
#and I want to use its start and end points to create an analogous consecutive sequence.
original_sequence <- c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12,
13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27,
28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42,
43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57,
58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72,
73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87,
88, 89, 90, 91, 92, 93, 94, 95, 96, 98, 98, 99, 100, 101,
102, 103, 104, 105, 106, 107, 108, 109, 110)
## unsuccessful attempt #1
original_sequence %>%
range() %>%
seq()
[1] 1 2 ## this result is equivalent to the output of `seq(2)`,
## but what I want is to compute `seq(1 ,110)`.
## unsuccessful attempt #2
original_sequence %>%
range() %>%
seq(.[1]), .[2])
Error: unexpected ',' in:
" range() %>%
seq(.[1]),"
## attempt #3: somewhat successful but I wonder whether there's a better way
original_sequence %>%
range() %>%
sapply(., seq)
[[1]]
[1] 1
[[2]]
[1] 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38
[39] 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76
[77] 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110
Bottom line -- I was able to do it with sapply but I hope to figure out a solution in the spirit of my second attempt, because it's more handy to know a universal way to cherry-pick the specific vector elements you want to pass to the next function's arguments.

One way would be to use {} and pass input arguments to seq
library(dplyr)
original_sequence %>%
range() %>%
{seq(.[[1]], .[2])}
#[1] 1 2 3 4 5 6 7 8 9 10 11 12......
Or we can mix it with base R do.call
original_sequence %>% range() %>% {do.call(seq, as.list(.))}
Or as #Ozan147 mentioned if your sequence always starts with 1 we can use max
original_sequence %>% max %>% seq

We can use reduce
library(tidyverse)
original_sequence %>%
range %>%
reduce(seq)
#[1] 1 2 3 4 ...

How to create list-columns from list in R?

# Sample data
df <- tibble(id=1:2, xml_str=c("<?xml version='1.0'?><!DOCTYPE svg PUBLIC '-//W3C//DTD SVG 1.1//EN' 'http://www.w3.org/Graphics/SVG/1.1/DTD/svg11.dtd'><svg version='1.1' xmlns='http://www.w3.org/2000/svg'>'/>\n<path fill='none' stroke='#ff0000' stroke-width='5' d='M171, 160 L171, 160, 168, 159, 164, 159, 163, 159, 162, 159, 161, 159, 161, 158, 162, 158, 162, 157, 163, 156, 165, 156'/>'/>\n<path fill='none' stroke='#ff0000' stroke-width='5' d='M172, 226 L172, 226, 171, 213, 170, 212, 171, 212, 172, 212, 173, 212, 173, 211, 172, 211, 171, 211, 171, 212, 171, 215'/>\n<path fill='none' stroke='#ff0000' stroke-width='5' d='M153, 94 L153, 94, 150, 90, 150, 89, 150, 88, 150, 87, 150, 86, 150, 85, 150, 84, 150, 82, 150, 81, 150, 80, 150, 79'/>'/>'/>'/>\n<path fill='none' stroke='#ff0000' stroke-width='5' d='M346, 84 L346, 84, 346, 79, 347, 78, 347, 77, 348, 77, 348, 76, 348, 75, 348, 76, 348, 77, 349, 77, 348, 78'/>\n<path fill='none' stroke='#ff0000' stroke-width='5' d='M314, 67 L314, 67, 311, 76, 309, 76, 308, 77, 307, 77, 307, 76, 306, 76, 305, 76, 305, 77, 306, 77, 307, 77, 306, 77, 305, 79, 304, 80'/>\n<path fill='none' stroke='#ff0000' stroke-width='5' d='M313, 57 L313, 57, 321, 56, 321, 57, 321, 58'/>\n<path fill='none' stroke='#ff0000' stroke-width='5' d='M332, 58 L332, 58, 332, 57, 331, 57, 333, 57, 334, 57, 335, 57, 336, 58, 337, 58, 338, 58, 339, 58, 340, 58, 341, 58, 341, 59, 340, 60, 339, 60, 338, 60, 337, 60, 336, 60, 335, 60, 334, 60, 333, 60, 332, 60, 331, 60, 331, 59, 333, 58, 334, 58'/></svg>", "<?xml version='1.0'?><!DOCTYPE svg PUBLIC '-//W3C//DTD SVG 1.1//EN' 'http://www.w3.org/Graphics/SVG/1.1/DTD/svg11.dtd'><svg version='1.1' xmlns='http://www.w3.org/2000/svg'>\n<path fill='none' stroke='#ff0000' stroke-width='5' d='M315, 80 L315, 80, 321, 79, 320, 79, 318, 79, 317, 79'/>\n<path fill='none' stroke='#ff0000' stroke-width='5' d='M334, 83 L334, 83, 334, 82'/>\n<path fill='none' stroke='#ff0000' stroke-width='5' d='M315, 80 L315, 80, 315, 82, 315, 83, 315, 84, 315, 85'/>\n<path fill='none' stroke='#ff0000' stroke-width='5' d='M315, 72 L315, 72'/>\n<path fill='none' stroke='#ff0000' stroke-width='5' d='M315, 69 L315, 69, 315, 70'/>\n<path fill='none' stroke='#ff0000' stroke-width='5' d='M332, 66 L332, 66, 332, 67'/>\n<path fill='none' stroke='#ff0000' stroke-width='5' d='M315, 56 L315, 56'/>\n<path fill='none' stroke='#ff0000' stroke-width='5' d='M315, 66 L315, 66, 315, 67'/>\n<path fill='none' stroke='#ff0000' stroke-width='5' d='M315, 72 L315, 72'/>\n<path fill='none' stroke='#ff0000' stroke-width='5' d='M332, 72 L332, 72, 333, 75'/>\n<path fill='none' stroke='#ff0000' stroke-width='5' d='M315, 72 L315, 72'/>\n<path fill='none' stroke='#ff0000' stroke-width='5' d='M334, 73 L334, 73, 333, 73'/></svg>"))
df <- df %>%
rowwise() %>%
mutate(nodes = (xml_str %>% read_xml() %>% xml_find_all(., "//#d") %>% as_list()))
With the data frame above, I want to extract all path-element d-nodes from the xml string and store them as a list in the same data frame, but I get Column nodes must be length 1 (the group size), not 7
The piping used in the mutate statement does return a single list.
I can leave out the 'rowwise()', but that simply expects length 2 instead of 1.
What am I missing here?

It's not exactly the way you're doing it, but you can use str_extract_all and regex to pull out the relevant string as a list of comma-separated strings
ans <-
df %>%
dplyr::mutate(dnodes = stringr::str_extract_all(xml_str, "(?<=[d]=')[^']+(?='\\/)"))
ans$dnodes
# [[1]]
# [1] "M171, 160 L171, 160, 168, 159, 164, 159, 163, 159, 162, 159, 161, 159, 161, 158, 162, 158, 162, 157, 163, 156, 165, 156"
# [2] "M172, 226 L172, 226, 171, 213, 170, 212, 171, 212, 172, 212, 173, 212, 173, 211, 172, 211, 171, 211, 171, 212, 171, 215"
# [3] "M153, 94 L153, 94, 150, 90, 150, 89, 150, 88, 150, 87, 150, 86, 150, 85, 150, 84, 150, 82, 150, 81, 150, 80, 150, 79"
# [4] "M346, 84 L346, 84, 346, 79, 347, 78, 347, 77, 348, 77, 348, 76, 348, 75, 348, 76, 348, 77, 349, 77, 348, 78"
# [5] "M314, 67 L314, 67, 311, 76, 309, 76, 308, 77, 307, 77, 307, 76, 306, 76, 305, 76, 305, 77, 306, 77, 307, 77, 306, 77, 305, 79, 304, 80"
# [6] "M313, 57 L313, 57, 321, 56, 321, 57, 321, 58"
# [7] "M332, 58 L332, 58, 332, 57, 331, 57, 333, 57, 334, 57, 335, 57, 336, 58, 337, 58, 338, 58, 339, 58, 340, 58, 341, 58, 341, 59, 340, 60, 339, 60, 338, 60, 337, 60, 336, 60, 335, 60, 334, 60, 333, 60, 332, 60, 331, 60, 331, 59, 333, 58, 334, 58"
# [[2]]
# [1] "M315, 80 L315, 80, 321, 79, 320, 79, 318, 79, 317, 79" "M334, 83 L334, 83, 334, 82"
# [3] "M315, 80 L315, 80, 315, 82, 315, 83, 315, 84, 315, 85" "M315, 72 L315, 72"
# [5] "M315, 69 L315, 69, 315, 70" "M332, 66 L332, 66, 332, 67"
# [7] "M315, 56 L315, 56" "M315, 66 L315, 66, 315, 67"
# [9] "M315, 72 L315, 72" "M332, 72 L332, 72, 333, 75"
# [11] "M315, 72 L315, 72" "M334, 73 L334, 73, 333, 73"
You can convert to list of a vector of strings with
ans <-
df %>%
dplyr::mutate(dnodes = stringr::str_extract_all(xml_str, "(?<=[d]=')[^']+(?='\\/)")) %>%
dplyr::mutate(dnodes = purrr::map(dnodes, ~unlist(strsplit(paste(.x, collapse=", "), ", "))))
ans$dnodes
# [[1]]
# [1] "M171" "160 L171" "160" "168" "159" "164" "159" "163" "159" "162"
# [11] "159" "161" "159" "161" "158" "162" "158" "162" "157" "163"
# [21] "156" "165" "156" "M172" "226 L172" "226" "171" "213" "170" "212"
# [31] "171" "212" "172" "212" "173" "212" "173" "211" "172" "211"
# [41] "171" "211" "171" "212" "171" "215" "M153" "94 L153" "94" "150"
# [51] "90" "150" "89" "150" "88" "150" "87" "150" "86" "150"
# [61] "85" "150" "84" "150" "82" "150" "81" "150" "80" "150"
# etc

Does this do what you want? I usually wrap the right side of my mutate(name = right_side) in list() to accomplish this.
df <- df %>%
mutate(nodes = list(xml_str %>% read_xml() %>% xml_find_all(., "//#d")))
class(df$nodes)
"list"
class(df$nodes[[1]])
"xml_nodeset"
Not sure if you want the xml_nodeset objects or perhaps CPak's solution with actual strings is better for you.

How to merge multiple columns into one column?

I currently have data spread out across multiple columns in R. I am looking for a way to put this information into the one column as a vector for each of the individual rows.
Is there a function to do this?
For example, the data looks like this:
DF <- data.frame(id=rep(LETTERS, each=1)[1:26], replicate(26, sample(1001, 26)), Class=sample(c("Yes", "No"), 26, TRUE))
select(DF, cols=c("id", "X1","X2", "X23", "Class"))
How can I merge the columns "X1","X2", "X23" into a vector containing numeric type variables for each of the IDs?

Like this?
library(reshape2)
melt(df) %>% dcast(id ~ ., fun.aggregate = list)
Using id, Class as id variables
id .
1 A 422, 74, 439
2 B 879, 443, 923
3 C 575, 901, 749
4 D 813, 747, 21
5 E 438, 526, 675
6 F 863, 562, 474
7 G 103, 713, 918
8 H 585, 294, 525
9 I 115, 76, 175
10 J 953, 379, 926
11 K 679, 439, 377
12 L 816, 624, 538
13 M 678, 226, 142
14 N 667, 369, 586
15 O 795, 422, 248
16 P 165, 22, 612
17 Q 294, 476, 746
18 R 968, 368, 290
19 S 238, 481, 980
20 T 921, 482, 741
21 U 550, 15, 296
22 V 121, 358, 625
23 W 213, 313, 242
24 X 92, 77, 58
25 Y 607, 936, 350
26 Z 660, 42, 275
A note though: I do not know your final use case, but this strikes me as something you probably do not want to have. It is often more advisable to stick to tidy data, see e.g. https://cran.r-project.org/web/packages/tidyr/vignettes/tidy-data.html

remove every 4 rows between two numbers

for example, I have a data frame with one column containing numbers. these is how it looks.
head(c1)
c
1 300
2 302
3 304
4 306
5 308
6 310
Here is the sample data frame.
c1 <- structure(list(c = c(300, 302, 304, 306, 308, 310, 312, 314,
316, 318, 320, 322, 324, 326, 328, 330, 332, 334, 336, 338, 340,
342, 344, 346, 348, 350, 352, 354, 356, 358, 360, 362, 364, 366,
368, 370, 372, 374, 376, 378, 380, 382, 384, 386, 388, 390, 392,
394, 396, 398, 400)), .Names = "c", row.names = c(NA, -51L), class = "data.frame")
I want to delete the rows between 300 to 310 and 310 to 320 and so on..
I want to have a dataframe like these
300
310
320
330
340
350
.
.
.
400
Any ideas how to do these, I found how to remove every nth row, but not every four rows between two numbers

You can make use of the modulo operator %%. If you want the result as an atomic vector, you can run
c1$c[c1$c %% 10 == 0]
or if you want it as a data.frame with 1 column, you can use
c1[c1$c %% 10 == 0, , drop=FALSE]

Trying to use separate to split one column into more than 2 columns

I'm new to R and practicing using the Titanic data set from Kaggle. I am attempting to separate last name, first name, salutation, and extra information into separate columns so that I can try to categorize the age of the passengers - adult or child.
The following is sample data from the Train data set:
head(traindf,5)
# Source: local data frame [5 x 12]
#
# PassengerId Survived Pclass
# 1 1 0 3
# 2 2 1 1
# 3 3 1 3
# 4 4 1 1
# 5 5 0 3
# Variables not shown: Name (chr), Sex (fctr), Age (dbl), SibSp (int), Parch
# (int), Ticket (fctr), Fare (dbl), Cabin (fctr), Embarked (fctr)
The following is a sample that includes the Name:
select(traindf,Survived,Pclass,Name,Sex)
# Source: local data frame [891 x 4]
#
# Survived Pclass Name Sex
# 1 0 3 Braund, Mr. Owen Harris male
# 2 1 1 Cumings, Mrs. John Bradley (Florence Briggs Thayer) female
# 3 1 3 Heikkinen, Miss. Laina female
# 4 1 1 Futrelle, Mrs. Jacques Heath (Lily May Peel) female
# 5 0 3 Allen, Mr. William Henry male
# 6 0 3 Moran, Mr. James male
# 7 0 1 McCarthy, Mr. Timothy J male
# 8 0 3 Palsson, Master. Gosta Leonard male
# 9 1 3 Johnson, Mrs. Oscar W (Elisabeth Vilhelmina Berg) female
# 10 1 2 Nasser, Mrs. Nicholas (Adele Achem) female
I can use the following code to separate last name from the rest of the column:
require(tidyr) # for the separate() function
traindfnames <- traindf %>%
separate(Name, c("Lastname","Salutation"), sep = ",")
traindfnames
# Source: local data frame [891 x 13]
#
# PassengerId Survived Pclass Lastname
# 1 1 0 3 Braund
# 2 2 1 1 Cumings
# 3 3 1 3 Heikkinen
# 4 4 1 1 Futrelle
# 5 5 0 3 Allen
# 6 6 0 3 Moran
# 7 7 0 1 McCarthy
# 8 8 0 3 Palsson
# 9 9 1 3 Johnson
# 10 10 1 2 Nasser
# .. ... ... ... ...
# Variables not shown: Salutation (chr), Sex (fctr), Age (dbl), SibSp (int),
# Parch (int), Ticket (fctr), Fare (dbl), Cabin (fctr), Embarked (fctr)
However, when I try to add a field for First Name:
traindfnames <- traindf %>%
separate(Name, c("Lastname","Salutation","firstname"), sep =",,")
I get this error:
# Error: Values not split into 3 pieces at 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 148, 149, 150, 151, 152, 153, 154, 155, 156, 157, 158, 159, 160, 161, 162, 163, 164, 165, 166, 167, 168, 169, 170, 171, 172, 173, 174, 175, 176, 177, 178, 179, 180, 181, 182, 183, 184, 185, 186, 187, 188, 189, 190, 191, 192, 193, 194, 195, 196, 197, 198, 199, 200, 201, 202, 203, 204, 205, 206, 207, 208, 209, 210, 211, 212, 213, 2
Am I using incorrect syntax or 3 fields from one column isn't possible?

Having looked at this data, I think the easiest way to do it is using something like str_match() from package stringr. If you assume data$Name is in the form
"[Lastname], [Salutation]. [Firstname]"
the regular expression to match this is
str_match(data$Name, "([A-Za-z]*),\\s([A-Za-z]*)\\.\\s(.*)")
# [,1] [,2] [,3] [,4]
# [1,] "Braund, Mr. Owen Harris" "Braund" "Mr" "Owen Harris"
# [2,] "Cumings, Mrs. John Bradley (Florence Briggs Thayer)" "Cumings" "Mrs" "John Bradley (Florence Briggs Thayer)"
# [3,] "Heikkinen, Miss. Laina" "Heikkinen" "Miss" "Laina"
# [4,] "Futrelle, Mrs. Jacques Heath (Lily May Peel)" "Futrelle" "Mrs" "Jacques Heath (Lily May Peel)"
# [5,] "Allen, Mr. William Henry" "Allen" "Mr" "William Henry"
# [6,] "Moran, Mr. James" "Moran" "Mr" "James"
So you need to add columns 2 to 4 above to your original data frame. I am not sure you can do this with separate actually. Writing
separate(data, Name, c("Lastname", "Salutation", "Firstname"), sep = "[,\\.]")
will try to split each entry by comma or dot, but it runs into a problem in the 514th entry that looks like "Rothschild, Mrs. Martin (Elizabeth L. Barrett)" (notice the second dot).
In short, the easiest way I can see of doing what you want is
data[c("Firstname", "Salutation", "Lastname")] <-
str_match(data$Name, "([A-Za-z]*),\\s([A-Za-z]*)\\.\\s(.*)")[, 2:4]

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