reshape (converting to character) - r

i have a the following matrix
data=structure(list(Metric = c("x", "y"), Result1 = c(9,
18), Result2 = c(7, 14
), Delta = c(-170, -401)), .Names = c("Metric",
"Result_1", "Result_2", "Delta"), row.names = c(NA,
-2L), class = "data.frame")
I would like to transform it in 1 row and to double the number of columns
I tried the following (as.vector(t(data))). However when I do that it transofrms everything to character and i loose data information
Any help?


We can split the data frame and then use bind_cols from the dplyr package. Although I am not sure this is your expected output as you did not provide any examples, just description.
dplyr::bind_cols(split(data, data$Metric))
Metric Result_1 Result_2 Delta Metric1 Result_11 Result_21 Delta1
1 x 9 7 -170 y 18 14 -401


In Base R
dd=stack(data)
A=dd$values
names(A)=dd$ind
data.frame(as.list(A))
Metric Metric.1 Result_1 Result_1.1 Result_2 Result_2.1 Delta Delta.1
1 x y 9 18 7 14 -170 -401

Related

Convert dates into numbers

I need your support while working with dates.
While importing an .xls file, the column of dates was correctly converted into numbers by R. Unfortunately some dates are still there in the format: dd/mm/yyyy or d/mm/yyyy or dd/mm/yy. Probably this results from different settings of different os. I don't know. Is there a way to manage this?
Thank you in advance
my_data <- read_excel("my_file.xls")
born_date
18520
30859
16/04/1972
26612
30291
24435
11/02/1964
26/09/1971
18427
23688
Original_dates
14/9/1950
26/6/1984
16/04/1972
9/11/1972
6/12/1982
24/11/1966
11/02/1964
26/09/1971
13/6/1950

Here is one way how we could solve it:
First we define the numeric values only by exlcuden those containing the string /.
Then we use excel_numeric_to_date function from janitor package.
Finally with coalesce we combine both:
library(dplyr)
library(janitor)
library(lubridate)
df %>%
mutate(x = ifelse(str_detect(born_date, '\\/'), NA_real_, born_date),
x = excel_numeric_to_date(as.numeric(as.character(x)), date_system = "modern"),
born_date = dmy(born_date)) %>%
mutate(born_date = coalesce(born_date, x), .keep="unused")
born_date
1 1950-09-14
2 1984-06-26
3 1972-04-16
4 1972-11-09
5 1982-12-06
6 1966-11-24
7 1964-02-11
8 1971-09-26
9 1950-06-13
10 1964-11-07
data:
df <- structure(list(born_date = c("18520", "30859", "16/04/1972",
"26612", "30291", "24435", "11/02/1964", "26/09/1971", "18427",
"23688")), class = "data.frame", row.names = c(NA, -10L))

1) This translates the two types of dates. Each returns an NA for those elements not of that type. Then we use coalesce to combine them. This only needs dplyr and no warnings are produced.
library(dplyr)
my_data %>%
mutate(born_date = coalesce(
as.Date(born_date, "%d/%m/%Y"),
as.Date(as.numeric(ifelse(grepl("/",born_date), NA, born_date)), "1899-12-30"))
)
## born_date
## 1 1950-09-14
## 2 1984-06-26
## 3 1972-04-16
## 4 1972-11-09
## 5 1982-12-06
## 6 1966-11-24
## 7 1964-02-11
## 8 1971-09-26
## 9 1950-06-13
## 10 1964-11-07
2) Here is a base R version.
my_data |>
transform(born_date = pmin(na.rm = TRUE,
as.Date(born_date, "%d/%m/%Y"),
as.Date(as.numeric(ifelse(grepl("/",born_date), NA, born_date)), "1899-12-30"))
)
Note
The input in reproducible form.
my_data <-
structure(list(born_date = c("18520", "30859", "16/04/1972",
"26612", "30291", "24435", "11/02/1964", "26/09/1971", "18427",
"23688")), class = "data.frame", row.names = c(NA, -10L))

Remove replicate number from end of string

I just need to remove all replicate numbers and letter "R" from the end of all rows in a column, strain and create a new column with those results in mutant, preferable using dplyr so I can pipe the results forward.
For example
print(df)
strain measurement
1 CK522R1 75
2 CN344attBR1 50
3 GL065R13 32
4 GL078R100 27
Desired Output
strain measurement mutant
1 CK522R1 75 CK522
2 CN344attBR1 50 CN344attB
3 GL065R13 32 GL065
4 GL078R100 27 GL078
Reproducible Data
structure(list(strain = structure(1:4, .Label = c("CK522R1",
"CN344attBR1", "GL065R13", "GL078R100"), class = "factor"), measurement = c(75,
50, 32, 27)), class = "data.frame", row.names = c(NA, -4L))

From d.b's comment:
library(dplyr)
df %>% mutate(mutant=sub("R\\d+$", "",strain),replicate=regmatches(strain, regexpr("R\\d+$", strain)))

Using values from two data files for one formula for calculation in R

I'm a trying-to-be R user. I never learned to code properly and have been just doing it by finding stuff online.
I encountered a problem that I would need some of you experts' help.
I have two data files.
Particulate matter (PM) concentrations (~20000 observations)
Coefficient combinations to use with the particulate matter concentrations to calculate final concentrations.
For example..
Data set 1.
ID PM
1 5
2 10
... ...
1500 25
Data set 2.
alpha beta
5 6
1 2
... ...
I ultimately have to use all the coefficient combinations (alpha and beta) for each of the IDs from data set 1. For example, if I have 10 observations in data set 1, and 10 coefficient combinations in data set 2, my output table should have 100 different output values (10*10=100).
for (i in cmaq$FID) {
mean=cmaq$PM*IER$alpha*IER$beta
}
I used the above code to do what I'm trying to do, but it only gave me 10 output values rather than 100. I think using the split function first, and somehow use that with the second dataset would work, but have not figured out how...
It may be a very very simple problem, but after spending hours to figure it out, I thought it may be a better strategy to get some help from R experts.
Thank you in advance!!!

You can do:
df1 = data.frame(
ID = c(1, 2, 1500),
PM = c(5, 10, 25)
)
df2 = data.frame(
alpha = c(5, 6),
beta = c(1, 2)
)
library(tidyverse)
library(dplyr)
df1 %>%
group_by(ID) %>%
do(data.frame(result = .$PM * df2$alpha * df2$beta,
alpha = df2$alpha,
beta = df2$beta))

Look for the term 'cross join' or 'cartesian join' (eg, How to do cross join in R?).
If that doesn't address the issue, please see https://stackoverflow.com/help/mcve. I think there is a mistake inside the loop. beta is free-floating, and not connected to the IER data.frame

We can do this with outer
data.frame(ID = rep(df1$ID, each = nrow(df2)), alpha = df2$alpha,
beta = df2$beta, result = c(t(outer(df1$PM, df2$alpha*df2$beta))))
# ID alpha beta result
#1 1 5 1 25
#2 1 6 2 60
#3 2 5 1 50
#4 2 6 2 120
#5 1500 5 1 125
#6 1500 6 2 300
data
df1 <- structure(list(ID = c(1, 2, 1500), PM = c(5, 10, 25)), .Names = c("ID",
"PM"), row.names = c(NA, -3L), class = "data.frame")
df2 <- structure(list(alpha = c(5, 6), beta = c(1, 2)), .Names = c("alpha",
"beta"), row.names = c(NA, -2L), class = "data.frame")

Convert data frame to spatial lines data frame in R with x,y x,y coordintates

I have a data frame in R, one of the columns contains the coordinates for points along a line in the form:
x,y x,y x,y x,y
So the whole data frame looks like
id dist speed coord
1 45 6 1.294832,54.610240 -1.294883,54.610080 -1.294262,54.6482757
2 23 34 2.788732,34.787940 6.294883,24.567080 -5.564262,-45.7676757
I would like to convert this to a spatial lines data frame, and I assume that the fist step would be to separate the coordinates into two columns in the from:
x, x, x, x
y, y, y, y
But I am unsure how to proceed.
EDIT
For those requesting it a dput of the actual file
> finalsub <- final[final$rid <3,]
> dput(finalsub)
structure(list(rid = c(1, 2), start_id = c(1L, 1L), start_code = c("E02002536",
"E02002536"), end_id = c(106L, 106L), end_code = c("E02006909",
"E02006909"), strategy = c("fastest", "quietest"), distance = c(12655L,
12909L), time_seconds = c(2921L, 3422L), calories = c(211L, 201L
), document.id = c(1L, 1L), array.index = 1:2, start = c("Geranium Close",
"Geranium Close"), finish = c("Hylton Road", "Hylton Road"),
startBearing = c(0, 0), startSpeed = c(0, 0), start_longitude = c(-1.294832,
-1.294832), start_latitude = c(54.610241, 54.610241), finish_longitude = c(-1.249478,
-1.249478), finish_latitude = c(54.680691, 54.680691), crow_fly_distance = c(8362,
8362), event = c("depart", "depart"), whence = c(1473171787,
1473171787), speed = c(20, 20), itinerary = c(419956, 419957
), clientRouteId = c(0, 0), plan = c("fastest", "quietest"
), note = c("", ""), length = c(12655, 12909), time = c(2921,
3422), busynance = c(42172, 17242), quietness = c(30, 75),
signalledJunctions = c(3, 4), signalledCrossings = c(2, 0
), west = c(-1.300074, -1.294883), south = c(54.610006, 54.609851
), east = c(-1.232447, -1.232447), north = c(54.683814, 54.683814
), name = c("Geranium Close to Hylton Road", "Geranium Close to Hylton Road"
), walk = c(0, 0), leaving = c("2016-09-06 15:23:07", "2016-09-06 15:23:07"
), arriving = c("2016-09-06 16:11:48", "2016-09-06 16:20:09"
), coordinates = c("-1.294832,54.610240 -1.294883,54.610080 -1.294262,54.610016 -1.294141,54.610006 -1.293710,54.610038 -1.293726,54.610142 -1.293742,54.610247 -1.293510,54.610262 -1.293368,54.610258 -1.292816,54.610195 -1.292489,54.610152 -1.292298,54.610667 -1.292205,54.610951 -1.292182,54.611063 -1.292183,54.611153 -1.292239,54.611341 -1.292305,54.611447 -1.292375,54.611534 -1.292494,54.611639 -1.292739,54.611830 -1.292909,54.611980 -1.293010,54.612107 -1.293111,54.612262 -1.293192,54.612423 -1.293235,54.612546 -1.293267,54.612684 -1.293279,54.612818 -1.293510,54.612813 -1.293732,54.612790 -1.294324,54.612691 -1.295086,54.612568 -1.295313,54.612539 -1.295379,54.612543 -1.295889,54.612645 -1.295945,54.612648 -1.296006,54.612642 -1.297154,54.612414 -1.297502,54.612895 -1.297733,54.612847 -1.297990,54.612796 -1.298292,54.612747 -1.298515,54.612727 -1.299088,54.612681 -1.299564,54.612669 -1.299798,54.612663 -1.300006,54.612660 -1.300057,54.612809 -1.300056,54.613335 -1.300071,54.613693 -1.300074,54.614044 -1.300042,54.614482 -1.300015,54.614786 -1.299947,54.615220 -1.299907,54.615394 -1.299854,54.615644 -1.299730,54.616048 -1.299495,54.616700 -1.299196,54.617347 -1.298236,54.619313 -1.298010,54.619762 -1.297703,54.620418 -1.297520,54.620831 -1.297169,54.621690 -1.297061,54.621981 -1.296416,54.623873 -1.296310,54.624308 -1.296225,54.624888 -1.296215,54.625286 -1.296220,54.625546 -1.296241,54.625803 -1.296268,54.625913 -1.296323,54.626011 -1.296397,54.626096 -1.296540,54.626190 -1.296719,54.626323 -1.296893,54.626433 -1.297042,54.626589 -1.297111,54.626710 -1.297122,54.626825 -1.297110,54.626948 -1.297058,54.627052 -1.296961,54.627172 -1.296861,54.627258 -1.296760,54.627325 -1.296603,54.627397 -1.296491,54.627438 -1.296338,54.627472 -1.296154,54.627496 -1.295966,54.627513 -1.295746,54.627526 -1.295618,54.627522 -1.295421,54.627510 -1.295197,54.627466 -1.295102,54.627436 -1.294832,54.627376 -1.294665,54.627355 -1.294502,54.627350 -1.294331,54.627366 -1.294014,54.627415 -1.293557,54.627499 -1.293001,54.627611 -1.292613,54.627701 -1.291836,54.627902 -1.291248,54.628076 -1.290635,54.628269 -1.290142,54.628446 -1.289621,54.628649 -1.289031,54.628903 -1.288538,54.629137 -1.288132,54.629350 -1.287681,54.629604 -1.287262,54.629862 -1.286866,54.630124 -1.286103,54.630643 -1.285748,54.630868 -1.285396,54.631082 -1.284974,54.631322 -1.284541,54.631540 -1.284101,54.631752 -1.283390,54.632048 -1.282592,54.632385 -1.282161,54.632566 -1.281762,54.632734 -1.281111,54.633011 -1.280519,54.633274 -1.280009,54.633501 -1.279834,54.633579 -1.279392,54.633781 -1.278434,54.634210 -1.277896,54.634457 -1.276936,54.634898 -1.276210,54.635223 -1.275594,54.635485 -1.274596,54.635891 -1.273929,54.636180 -1.273392,54.636428 -1.272814,54.636726 -1.271627,54.637353 -1.271084,54.637605 -1.270550,54.637825 -1.269916,54.638054 -1.269389,54.638222 -1.268821,54.638383 -1.268165,54.638555 -1.265953,54.639131 -1.263766,54.639693 -1.262790,54.639953 -1.262005,54.640154 -1.261340,54.640329 -1.260658,54.640532 -1.260123,54.640712 -1.259489,54.640957 -1.258639,54.641312 -1.258010,54.641554 -1.257141,54.641861 -1.255996,54.642247 -1.254429,54.642787 -1.253524,54.643099 -1.252790,54.643343 -1.251636,54.643727 -1.250900,54.643982 -1.250258,54.644219 -1.249668,54.644419 -1.249123,54.644623 -1.248778,54.644762 -1.246709,54.645642 -1.244773,54.646492 -1.244140,54.646746 -1.243551,54.646973 -1.242738,54.647233 -1.242353,54.647360 -1.241810,54.647503 -1.241182,54.647642 -1.240373,54.647780 -1.239950,54.647854 -1.239961,54.647890 -1.239435,54.647967 -1.239583,54.649724 -1.239343,54.649878 -1.239011,54.650011 -1.237692,54.650177 -1.236610,54.650296 -1.236417,54.650323 -1.236257,54.650351 -1.236015,54.650414 -1.235833,54.650469 -1.235081,54.650723 -1.234846,54.650805 -1.234312,54.650977 -1.234094,54.651025 -1.233980,54.651044 -1.233308,54.651137 -1.233173,54.651160 -1.233063,54.651200 -1.232967,54.651252 -1.232849,54.651347 -1.232814,54.651423 -1.232810,54.651495 -1.232823,54.651569 -1.232840,54.651893 -1.232827,54.652010 -1.232504,54.653177 -1.232447,54.653500 -1.232451,54.653723 -1.232474,54.653943 -1.232535,54.654301 -1.232590,54.654635 -1.232903,54.654627 -1.232948,54.655599 -1.232982,54.656334 -1.232795,54.656365 -1.233131,54.658020 -1.233336,54.658428 -1.233507,54.658699 -1.233592,54.658803 -1.234197,54.659389 -1.234690,54.659825 -1.234979,54.660119 -1.235153,54.660314 -1.235343,54.660572 -1.235566,54.661037 -1.235656,54.661355 -1.235690,54.661638 -1.235677,54.661902 -1.235677,54.661984 -1.235683,54.663215 -1.235656,54.663632 -1.235639,54.664273 -1.235613,54.664639 -1.235593,54.664822 -1.235566,54.664957 -1.235508,54.665351 -1.235197,54.667327 -1.235120,54.668542 -1.235100,54.668897 -1.235199,54.669535 -1.235358,54.670231 -1.235437,54.670482 -1.235756,54.671241 -1.236144,54.672181 -1.236375,54.672971 -1.236309,54.673562 -1.236286,54.673704 -1.236127,54.674365 -1.235918,54.675272 -1.235827,54.675620 -1.235749,54.675960 -1.235735,54.676152 -1.235740,54.676328 -1.235754,54.676598 -1.235770,54.676987 -1.235771,54.677013 -1.235793,54.677480 -1.235758,54.677760 -1.235607,54.678134 -1.235470,54.678420 -1.235167,54.678875 -1.234263,54.679929 -1.234207,54.680065 -1.234175,54.680201 -1.234204,54.680465 -1.234300,54.681119 -1.234362,54.681549 -1.234427,54.681771 -1.234560,54.682172 -1.234782,54.682824 -1.236530,54.682837 -1.236725,54.682829 -1.237133,54.682813 -1.238813,54.683143 -1.241021,54.683814 -1.241819,54.683771 -1.242854,54.683717 -1.242946,54.683718 -1.243082,54.683716 -1.244694,54.683772 -1.244658,54.683077 -1.245038,54.682805 -1.245047,54.681990 -1.245011,54.681238 -1.245220,54.680975 -1.247056,54.680601 -1.248019,54.680404 -1.249478,54.680691",
"-1.294832,54.610240 -1.294883,54.610080 -1.294262,54.610016 -1.294141,54.610006 -1.293710,54.610038 -1.293726,54.610142 -1.293742,54.610247 -1.293510,54.610262 -1.293368,54.610258 -1.292816,54.610195 -1.292489,54.610152 -1.292298,54.610667 -1.292167,54.610651 -1.291371,54.610562 -1.291240,54.610556 -1.291107,54.610564 -1.290983,54.610581 -1.290467,54.610665 -1.290253,54.610690 -1.290017,54.610689 -1.289770,54.610665 -1.289500,54.610620 -1.289281,54.610570 -1.289124,54.610514 -1.288957,54.610440 -1.288611,54.610277 -1.288420,54.610222 -1.287445,54.610110 -1.287259,54.610664 -1.286758,54.610611 -1.285446,54.610462 -1.285308,54.610459 -1.283356,54.610475 -1.283159,54.610475 -1.283156,54.610324 -1.283153,54.610119 -1.282818,54.610118 -1.282560,54.610114 -1.282110,54.610131 -1.281962,54.610153 -1.281788,54.610200 -1.281639,54.610257 -1.281298,54.609964 -1.281196,54.609851 -1.280586,54.610008 -1.280272,54.610054 -1.279816,54.610091 -1.279480,54.610104 -1.279112,54.610121 -1.278953,54.610146 -1.278815,54.610183 -1.278669,54.610225 -1.278524,54.610279 -1.278428,54.610326 -1.278327,54.610377 -1.278042,54.610237 -1.277946,54.610211 -1.277849,54.610204 -1.277454,54.610206 -1.277268,54.610211 -1.276621,54.610222 -1.276217,54.610233 -1.276085,54.610240 -1.275571,54.610315 -1.275426,54.610347 -1.275334,54.610373 -1.275248,54.610417 -1.275204,54.610477 -1.275066,54.610765 -1.274836,54.611248 -1.274811,54.611349 -1.274833,54.611414 -1.274925,54.611607 -1.274953,54.611664 -1.274669,54.611698 -1.272541,54.610433 -1.271290,54.610716 -1.270069,54.611677 -1.269365,54.611847 -1.268450,54.612165 -1.267142,54.612923 -1.266539,54.613386 -1.265920,54.614177 -1.265663,54.614259 -1.264195,54.616131 -1.263730,54.616670 -1.263665,54.616739 -1.263407,54.617051 -1.262407,54.618192 -1.262185,54.618424 -1.262077,54.618537 -1.261506,54.619136 -1.261394,54.619342 -1.261507,54.619520 -1.261799,54.620013 -1.261791,54.620138 -1.261695,54.620233 -1.261342,54.620279 -1.261237,54.620334 -1.261175,54.620442 -1.261128,54.620493 -1.260857,54.620616 -1.260783,54.620697 -1.260729,54.620807 -1.260729,54.620942 -1.260677,54.621042 -1.260600,54.621109 -1.260457,54.621250 -1.260409,54.621298 -1.260364,54.621336 -1.260140,54.621409 -1.260052,54.621475 -1.259959,54.621607 -1.259881,54.621722 -1.259603,54.622326 -1.259445,54.622670 -1.259349,54.623096 -1.259359,54.623266 -1.259490,54.623825 -1.259497,54.623856 -1.259882,54.624563 -1.259894,54.624684 -1.259646,54.624993 -1.259529,54.625176 -1.259093,54.625999 -1.258939,54.626244 -1.258780,54.626429 -1.258157,54.626772 -1.257604,54.627106 -1.256140,54.627787 -1.255933,54.627903 -1.255874,54.627953 -1.255754,54.628092 -1.255576,54.628504 -1.255534,54.628645 -1.255601,54.629176 -1.255572,54.629415 -1.255265,54.630017 -1.255104,54.630209 -1.254200,54.630725 -1.254084,54.630831 -1.254037,54.630915 -1.254018,54.631129 -1.254128,54.631712 -1.254107,54.631961 -1.253979,54.632187 -1.253594,54.632613 -1.253530,54.632749 -1.253501,54.632882 -1.253404,54.633827 -1.253482,54.634447 -1.253483,54.634654 -1.253445,54.634902 -1.253389,54.635040 -1.253275,54.635186 -1.252555,54.635902 -1.252473,54.636063 -1.252330,54.636859 -1.252273,54.637015 -1.252176,54.637175 -1.251977,54.637365 -1.251763,54.637507 -1.251314,54.637755 -1.250800,54.638114 -1.250487,54.638358 -1.250153,54.638709 -1.249968,54.638840 -1.249562,54.639001 -1.248455,54.639365 -1.248124,54.639494 -1.247386,54.639821 -1.246797,54.640013 -1.246610,54.640098 -1.246513,54.640170 -1.246574,54.640279 -1.247014,54.640580 -1.247341,54.641088 -1.247564,54.641365 -1.248256,54.642661 -1.248319,54.642919 -1.247650,54.643048 -1.246829,54.643234 -1.245867,54.643306 -1.245202,54.643286 -1.243595,54.643087 -1.243282,54.643073 -1.242962,54.643076 -1.242041,54.643065 -1.241790,54.643031 -1.241369,54.642888 -1.240421,54.642544 -1.240237,54.642499 -1.240075,54.642497 -1.239926,54.642545 -1.239858,54.642627 -1.239837,54.642696 -1.239909,54.642989 -1.239960,54.643498 -1.239964,54.643532 -1.239983,54.644175 -1.239936,54.644470 -1.239883,54.644807 -1.239842,54.645116 -1.239825,54.645489 -1.239748,54.646014 -1.239733,54.646299 -1.239798,54.646734 -1.239789,54.646896 -1.239705,54.647229 -1.239683,54.647331 -1.239608,54.647496 -1.239566,54.647621 -1.239562,54.647760 -1.239618,54.647903 -1.239421,54.647932 -1.239435,54.647967 -1.239583,54.649724 -1.239343,54.649878 -1.239011,54.650011 -1.237692,54.650177 -1.236610,54.650296 -1.236417,54.650323 -1.236257,54.650351 -1.236015,54.650414 -1.235833,54.650469 -1.235081,54.650723 -1.234846,54.650805 -1.234312,54.650977 -1.234094,54.651025 -1.233980,54.651044 -1.233308,54.651137 -1.233173,54.651160 -1.233063,54.651200 -1.232967,54.651252 -1.232849,54.651347 -1.232814,54.651423 -1.232810,54.651495 -1.232823,54.651569 -1.232840,54.651893 -1.232827,54.652010 -1.232504,54.653177 -1.232447,54.653500 -1.232451,54.653723 -1.232474,54.653943 -1.232535,54.654301 -1.232590,54.654635 -1.232619,54.654960 -1.232723,54.655606 -1.232795,54.656365 -1.233131,54.658020 -1.233336,54.658428 -1.233507,54.658699 -1.233592,54.658803 -1.234197,54.659389 -1.234690,54.659825 -1.234979,54.660119 -1.235153,54.660314 -1.235343,54.660572 -1.235566,54.661037 -1.235656,54.661355 -1.235690,54.661638 -1.235677,54.661902 -1.235677,54.661984 -1.235683,54.663215 -1.235656,54.663632 -1.235639,54.664273 -1.235613,54.664639 -1.235593,54.664822 -1.235566,54.664957 -1.235508,54.665351 -1.235197,54.667327 -1.235120,54.668542 -1.235100,54.668897 -1.235199,54.669535 -1.235358,54.670231 -1.235437,54.670482 -1.235756,54.671241 -1.236144,54.672181 -1.236375,54.672971 -1.236309,54.673562 -1.236286,54.673704 -1.236127,54.674365 -1.235918,54.675272 -1.235827,54.675620 -1.235749,54.675960 -1.235735,54.676152 -1.235740,54.676328 -1.235754,54.676598 -1.235770,54.676987 -1.235771,54.677013 -1.235793,54.677480 -1.235758,54.677760 -1.235607,54.678134 -1.235470,54.678420 -1.235167,54.678875 -1.234263,54.679929 -1.234207,54.680065 -1.234175,54.680201 -1.234204,54.680465 -1.234300,54.681119 -1.234362,54.681549 -1.234427,54.681771 -1.234560,54.682172 -1.234782,54.682824 -1.236530,54.682837 -1.236725,54.682829 -1.237133,54.682813 -1.238813,54.683143 -1.241021,54.683814 -1.241819,54.683771 -1.242854,54.683717 -1.242946,54.683718 -1.243082,54.683716 -1.244694,54.683772 -1.244658,54.683077 -1.245038,54.682805 -1.245047,54.681990 -1.245011,54.681238 -1.245220,54.680975 -1.247056,54.680601 -1.248019,54.680404 -1.249478,54.680691"
), grammesCO2saved = c(2359, 2406), calories = c(211, 201
), type = c("route", "route")), .Names = c("rid", "start_id",
"start_code", "end_id", "end_code", "strategy", "distance", "time_seconds",
"calories", "document.id", "array.index", "start", "finish",
"startBearing", "startSpeed", "start_longitude", "start_latitude",
"finish_longitude", "finish_latitude", "crow_fly_distance", "event",
"whence", "speed", "itinerary", "clientRouteId", "plan", "note",
"length", "time", "busynance", "quietness", "signalledJunctions",
"signalledCrossings", "west", "south", "east", "north", "name",
"walk", "leaving", "arriving", "coordinates", "grammesCO2saved",
"calories", "type"), row.names = 1:2, class = "data.frame")
>

I believe what you want to end up with is a column in your data frame that for each row is a list (or data frame) with x.coord and y.coord columns. To achieve that, we can use unnest and nest from tidyr with dplyr:
library(dplyr)
library(tidyr)
result <- finalsub %>% mutate(coordinates = strsplit(coordinates,split=" ",fixed=TRUE)) %>%
unnest(coordinates) %>%
mutate(coordinates = strsplit(coordinates,split=",",fixed=TRUE),
x.coord = as.numeric(unlist(coordinates)[c(TRUE,FALSE)]),
y.coord = as.numeric(unlist(coordinates)[c(FALSE,TRUE)])) %>%
select(-coordinates) %>%
nest(x.coord,y.coord,.key=coordinates)
Notes:
The first mutate splits the character vector in your coordinates column by " " to separate each coordinate x,y resulting in a list of these.
unnest separates this list into rows.
In the second mutate, we first split each coordinate x,y, this time by "," to separate each coordinate into x and y. Then we create separate x.coord and y.coord columns to hold these. Note the conversion to numeric here.
Finally, we use nest to collect the x.coord and y.coord columns as a list under the column named coordinates. Note that we first have to remove the original coordinates column.
The result using your dput data, printing only the coordinates column:
print(result$coordinates)
##[[1]]
### A tibble: 284 x 2
## x.coord y.coord
## <dbl> <dbl>
##1 -1.294832 54.61024
##2 -1.294883 54.61008
##3 -1.294262 54.61002
##4 -1.294141 54.61001
##5 -1.293710 54.61004
##6 -1.293726 54.61014
##7 -1.293742 54.61025
##8 -1.293510 54.61026
##9 -1.293368 54.61026
##10 -1.292816 54.61019
### ... with 274 more rows
##
##[[2]]
### A tibble: 322 x 2
## x.coord y.coord
## <dbl> <dbl>
##1 -1.294832 54.61024
##2 -1.294883 54.61008
##3 -1.294262 54.61002
##4 -1.294141 54.61001
##5 -1.293710 54.61004
##6 -1.293726 54.61014
##7 -1.293742 54.61025
##8 -1.293510 54.61026
##9 -1.293368 54.61026
##10 -1.292816 54.61019
### ... with 312 more rows

df1 <- data.frame(id= c(1,2), dist =c(45,23), speed = c(6,24) ,do.call(rbind,strsplit(df$cord,split = " ")))
library(reshape2)
df1 <- melt(df1,id=c("id","dist","speed"))
df2<- data.frame(do.call(rbind,strsplit(df1$value, split=",")))
df1$value <- NULL
df1 <- cbind(df1,df2)
names(df1)[5:6] <- c("x","y")
id dist speed variable x y
1 1 45 6 X1 1.294832 54.610240
2 2 23 24 X1 2.788732 34.787940
3 1 45 6 X2 -1.294883 54.610080
4 2 23 24 X2 6.294883 24.567080
5 1 45 6 X3 -1.294262 54.6482757
6 2 23 24 X3 -5.564262 -45.7676757

Comparing pairs of rows in a list of data frames

I have a list that's 1314 element long. Each element is a data frame consisting of two rows and four columns.
Game.ID Team Points Victory
1 201210300CLE CLE 94 0
2 201210300CLE WAS 84 0
I would like to use the lapply function to compare points for each team in each game, and change Victory to 1 for the winning team.
I'm trying to use this function:
test_vic <- lapply(all_games, function(x) {if (x[1,3] > x[2,3]) {x[1,4] = 1}})
But the result it produces is a list 1314 elements long with just the Game ID and either a 1 or a null, a la:
$`201306200MIA`
[1] 1
$`201306160SAS`
NULL
How can I fix my code so that each data frame maintains its shape. (I'm guessing solving the null part involves if-else, but I need to figure out the right syntax.)
Thanks.

Try
lapply(all_games, function(x) {x$Victory[which.max(x$Points)] <- 1; x})
Or another option would be to convert the list to data.table by using rbindlist and then do the conversion
library(data.table)
rbindlist(all_games)[,Victory:= +(Points==max(Points)) ,Game.ID][]
data
all_games <- list(structure(list(Game.ID = c("201210300CLE",
"201210300CLE"
), Team = c("CLE", "WAS"), Points = c(94L, 84L), Victory = c(0L,
0L)), .Names = c("Game.ID", "Team", "Points", "Victory"),
class = "data.frame", row.names = c("1",
"2")), structure(list(Game.ID = c("201210300CME", "201210300CME"
), Team = c("CLE", "WAS"), Points = c(90, 92), Victory = c(0L,
0L)), .Names = c("Game.ID", "Team", "Points", "Victory"),
row.names = c("1", "2"), class = "data.frame"))

You could try dplyr:
library(dplyr)
all_games %>%
bind_rows() %>%
group_by(Game.ID) %>%
mutate(Victory = row_number(Points)-1)
Which gives:
#Source: local data frame [4 x 4]
#Groups: Game.ID
#
# Game.ID Team Points Victory
#1 201210300CLE CLE 94 1
#2 201210300CLE WAS 84 0
#3 201210300CME CLE 90 0
#4 201210300CME WAS 92 1

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