问题
I am following a tutorial and I am trying to apply this part to my data/problem
kclusts <- tibble(k = 1:9) %>%
mutate(
kclust = map(k, ~kmeans(points, .x)),
tidied = map(kclust, tidy),
glanced = map(kclust, glance),
augmented = map(kclust, augment, points)
)
However my data is slightly different to that of the tutorials. I am trying to apply the final line augmented = map(kclust, augment, points).
Code which Works (without the final line):
kclust <- results %>%
as_tibble() %>%
select(-id_row) %>%
group_by(year_row) %>%
nest(.key = "value") %>%
filter(map_int(value, nrow) > 4) %>%
mutate(kmeans = map(value, ~kmeans(.x[[1]], centers = 4, iter.max = 10, nstart = 1)),
tidied = map(kmeans, tidy),
glanced = map(kmeans, glance))
Code which does not work (with my attempt at the augment part:
kclust <- results %>%
as_tibble() %>%
select(-id_row) %>%
group_by(year_row) %>%
nest(.key = "value") %>%
filter(map_int(value, nrow) > 4) %>%
mutate(kmeans = map(value, ~kmeans(.x[[1]], centers = 4, iter.max = 10, nstart = 1)),
tidied = map(kmeans, tidy),
glanced = map(kmeans, glance),
augmented = map(1:nrow(kclust, function(x) {augment(kclust$kmeans[[x]], kclust$value[[x]])})))
The following Works outside of the tibble but I cannot get it working inside;
augment(kclust$kmeans[[1]], kclust$value[[1]])
fun <- function(x) {augment(kclust$kmeans[[x]], kclust$value[[x]])}
ag <- map(1:3, fun)
ag
My goal is to plot the ggplot plot at the very end of the tutorial, where each year Will be one facet.
p1 <- ggplot(assignments, aes(x1, x2)) +
geom_point(aes(color = .cluster)) +
facet_wrap(~ k)
p1
Data:
structure(list(id_row = c("1000228", "1000228", "1000228", "1000228",
"1000228", "1000228", "1000228", "1000228", "1000228", "1000228",
"1000228", "1000228", "1000228", "100493", "100493", "100493",
"100493", "100493", "1011006", "1011006", "1011006", "1011006",
"1011006", "1011006", "1011006", "1011006", "1037949", "1037949",
"1037949", "1037949", "1037949", "1037949", "1037949", "1037949",
"1037949", "11199", "11199", "11199", "11199", "11199", "11199",
"11199", "11199", "1403161", "1403161", "1403161", "1403161",
"1403161", "1403161", "1403161", "1403161", "1403161", "1403161",
"1403161", "1403161", "1403161", "1403161", "1403161", "14693",
"14693", "14693", "14693", "14693", "14693", "14693", "14693",
"14693", "14693", "14693", "14693", "14693", "14693", "14693",
"14693", "14693", "14693", "14693", "1603923", "1603923", "1603923",
"1603923", "1603923", "1603923", "1603923", "1603923", "1603923",
"1603923", "1603923", "1603923", "1603923", "217346", "217346",
"217346", "217346", "217346", "217346", "217346", "217346", "217346",
"217346", "217346", "217346", "217346", "2969", "2969", "2969",
"2969", "2969", "2969", "2969", "2969", "2969", "2969", "2969",
"2969", "2969", "2969", "2969", "2969", "318154", "318154", "318154",
"42582", "42582", "42582", "42582", "42582", "42582", "42582",
"42582", "42582", "42582", "42582", "42582", "42582", "42582",
"42582", "42582", "42582", "5513", "5513", "5513", "5513", "5513",
"5513", "5513", "5513", "5513", "5513", "5513", "5513", "5513",
"5513", "5513", "5513", "717423", "717423", "717423", "717423",
"717423", "717423", "717423", "717423", "717423", "80661", "80661",
"80661", "80661", "80661", "80661", "80661", "80661", "80661",
"80661", "80661", "80661", "80661", "80661", "80661", "80661",
"823768", "823768", "823768", "823768", "823768", "823768", "860730",
"860730", "860730", "860730", "860730", "860730", "860730", "860730",
"860730", "860730", "860730", "860730", "860730", "860730", "860730",
"860730", "860730", "860730", "860730", "860730", "860730", "863157",
"863157", "863157", "863157", "863157", "863157", "863157", "891024",
"891024", "891024", "891024", "891024", "891024", "891024", "891024",
"891024", "891024", "891024", "891024", "891024", "891024", "891024",
"891024", "891024", "912242", "912242", "912242", "912242", "912242",
"912242", "912242", "912242", "912242", "912242", "912242", "912242",
"912242", "912242", "912242"), year_row = c("2004", "2005", "2006",
"2007", "2011", "2012", "2013", "2014", "2015", "2016", "2017",
"2018", "2019", "2006", "2006", "2007", "2008", "2019", "2012",
"2013", "2014", "2015", "2016", "2017", "2018", "2019", "2011",
"2012", "2013", "2014", "2015", "2016", "2017", "2018", "2019",
"2007", "2008", "2009", "2010", "2011", "2012", "2013", "2014",
"2007", "2008", "2008", "2009", "2009", "2010", "2011", "2012",
"2013", "2014", "2015", "2016", "2017", "2018", "2019", "2002",
"2003", "2004", "2005", "2006", "2007", "2008", "2009", "2010",
"2010", "2011", "2011", "2012", "2013", "2014", "2015", "2016",
"2017", "2018", "2002", "2003", "2004", "2007", "2008", "2011",
"2012", "2013", "2014", "2015", "2016", "2017", "2018", "2007",
"2008", "2009", "2010", "2011", "2012", "2013", "2014", "2015",
"2016", "2017", "2018", "2019", "2004", "2005", "2006", "2006",
"2007", "2007", "2008", "2009", "2010", "2011", "2012", "2013",
"2014", "2015", "2016", "2017", "2013", "2014", "2015", "2003",
"2004", "2005", "2006", "2007", "2008", "2009", "2010", "2011",
"2012", "2013", "2014", "2015", "2016", "2017", "2018", "2019",
"2003", "2004", "2005", "2006", "2007", "2008", "2009", "2010",
"2011", "2012", "2013", "2014", "2015", "2016", "2017", "2018",
"2011", "2012", "2013", "2014", "2015", "2016", "2017", "2018",
"2019", "2004", "2005", "2006", "2009", "2010", "2011", "2012",
"2013", "2014", "2015", "2016", "2016", "2017", "2017", "2018",
"2019", "2003", "2004", "2005", "2006", "2007", "2008", "2014",
"2015", "2015", "2016", "2016", "2016", "2016", "2016", "2016",
"2017", "2017", "2017", "2017", "2017", "2017", "2018", "2018",
"2018", "2018", "2019", "2019", "2013", "2014", "2015", "2016",
"2017", "2018", "2019", "2003", "2004", "2005", "2006", "2007",
"2008", "2009", "2010", "2011", "2012", "2013", "2014", "2015",
"2016", "2017", "2018", "2019", "2005", "2006", "2007", "2008",
"2009", "2010", "2011", "2012", "2013", "2014", "2015", "2016",
"2017", "2018", "2019"), id_col = c("1000228", "1000228", "1000228",
"1000228", "1000228", "1000228", "1000228", "1000228", "1000228",
"1000228", "1000228", "1000228", "1000228", "100493", "100493",
"100493", "100493", "100493", "1011006", "1011006", "1011006",
"1011006", "1011006", "1011006", "1011006", "1011006", "1037949",
"1037949", "1037949", "1037949", "1037949", "1037949", "1037949",
"1037949", "1037949", "11199", "11199", "11199", "11199", "11199",
"11199", "11199", "11199", "1403161", "1403161", "1403161", "1403161",
"1403161", "1403161", "1403161", "1403161", "1403161", "1403161",
"1403161", "1403161", "1403161", "1403161", "1403161", "14693",
"14693", "14693", "14693", "14693", "14693", "14693", "14693",
"14693", "14693", "14693", "14693", "14693", "14693", "14693",
"14693", "14693", "14693", "14693", "1603923", "1603923", "1603923",
"1603923", "1603923", "1603923", "1603923", "1603923", "1603923",
"1603923", "1603923", "1603923", "1603923", "217346", "217346",
"217346", "217346", "217346", "217346", "217346", "217346", "217346",
"217346", "217346", "217346", "217346", "2969", "2969", "2969",
"2969", "2969", "2969", "2969", "2969", "2969", "2969", "2969",
"2969", "2969", "2969", "2969", "2969", "318154", "318154", "318154",
"42582", "42582", "42582", "42582", "42582", "42582", "42582",
"42582", "42582", "42582", "42582", "42582", "42582", "42582",
"42582", "42582", "42582", "5513", "5513", "5513", "5513", "5513",
"5513", "5513", "5513", "5513", "5513", "5513", "5513", "5513",
"5513", "5513", "5513", "717423", "717423", "717423", "717423",
"717423", "717423", "717423", "717423", "717423", "80661", "80661",
"80661", "80661", "80661", "80661", "80661", "80661", "80661",
"80661", "80661", "80661", "80661", "80661", "80661", "80661",
"823768", "823768", "823768", "823768", "823768", "823768", "860730",
"860730", "860730", "860730", "860730", "860730", "860730", "860730",
"860730", "860730", "860730", "860730", "860730", "860730", "860730",
"860730", "860730", "860730", "860730", "860730", "860730", "863157",
"863157", "863157", "863157", "863157", "863157", "863157", "891024",
"891024", "891024", "891024", "891024", "891024", "891024", "891024",
"891024", "891024", "891024", "891024", "891024", "891024", "891024",
"891024", "891024", "912242", "912242", "912242", "912242", "912242",
"912242", "912242", "912242", "912242", "912242", "912242", "912242",
"912242", "912242", "912242"), year_col = c("2003", "2004", "2005",
"2006", "2010", "2011", "2012", "2013", "2014", "2015", "2016",
"2017", "2018", "2005", "2005", "2006", "2007", "2018", "2011",
"2012", "2013", "2014", "2015", "2016", "2017", "2018", "2010",
"2011", "2012", "2013", "2014", "2015", "2016", "2017", "2018",
"2006", "2007", "2008", "2009", "2010", "2011", "2012", "2013",
"2006", "2007", "2007", "2008", "2008", "2009", "2010", "2011",
"2012", "2013", "2014", "2015", "2016", "2017", "2018", "2001",
"2002", "2003", "2004", "2005", "2006", "2007", "2008", "2009",
"2009", "2010", "2010", "2011", "2012", "2013", "2014", "2015",
"2016", "2017", "2001", "2002", "2003", "2006", "2007", "2010",
"2011", "2012", "2013", "2014", "2015", "2016", "2017", "2006",
"2007", "2008", "2009", "2010", "2011", "2012", "2013", "2014",
"2015", "2016", "2017", "2018", "2003", "2004", "2005", "2005",
"2006", "2006", "2007", "2008", "2009", "2010", "2011", "2012",
"2013", "2014", "2015", "2016", "2012", "2013", "2014", "2002",
"2003", "2004", "2005", "2006", "2007", "2008", "2009", "2010",
"2011", "2012", "2013", "2014", "2015", "2016", "2017", "2018",
"2002", "2003", "2004", "2005", "2006", "2007", "2008", "2009",
"2010", "2011", "2012", "2013", "2014", "2015", "2016", "2017",
"2010", "2011", "2012", "2013", "2014", "2015", "2016", "2017",
"2018", "2003", "2004", "2005", "2008", "2009", "2010", "2011",
"2012", "2013", "2014", "2015", "2015", "2016", "2016", "2017",
"2018", "2002", "2003", "2004", "2005", "2006", "2007", "2013",
"2014", "2014", "2015", "2015", "2015", "2015", "2015", "2015",
"2016", "2016", "2016", "2016", "2016", "2016", "2017", "2017",
"2017", "2017", "2018", "2018", "2012", "2013", "2014", "2015",
"2016", "2017", "2018", "2002", "2003", "2004", "2005", "2006",
"2007", "2008", "2009", "2010", "2011", "2012", "2013", "2014",
"2015", "2016", "2017", "2018", "2004", "2005", "2006", "2007",
"2008", "2009", "2010", "2011", "2012", "2013", "2014", "2015",
"2016", "2017", "2018"), value = c(0.216923921856892, 0.0603860767654988,
0.0867705092874343, 0.0554689419488736, 0.266461630651174, 0.232882353118748,
0.233228956106436, 0.429109851221986, 0.143603832921258, 0.103581819938778,
0.120198289568911, 0.282929320804091, 0.0588034678951873, 0.12687772731908,
0.125590088599959, 0.152638288234646, 0.0573970894882795, 0.0223190695082444,
0.0772388947602825, 0.0610470146184067, 0.0498844812709738, 0.0417502588683055,
0.0709093243272215, 0.0479449809497808, 0.0446101230405492, 0.0688431182443062,
0.322153599918842, 0.918497422437913, 0.191262613179677, 0.174156380277032,
0.100398155108399, 0.211635149112375, 0.151663657345723, 0.135964184604919,
0.198866500317427, 0.552660373888907, 0.11297372482846, 0.136211462866787,
0.176921966808464, 0.0955796571576842, 0.0626512313467531, 0.056475829268418,
0.0515077695785625, 0.989753358949878, 0.704651534011912, 0.711391842791094,
0.18960162095846, 0.398094129350466, 0.277168236576228, 0.140473154935381,
0.37418849888887, 0.020866808171222, 0.811997463208844, 0.0925009217897454,
0.0557398356908807, 0.131320037363996, 0.0250001227960738, 0.380924496028996,
0.0457087256845359, 0.0533845514626979, 0.0592889458291134, 0.074605511680385,
0.149848111459932, 0.293446525042805, 0.0450946810591767, 0.0445204835445374,
0.0167243483862213, 0.108009105253104, 0.209377934871732, 0.0724495760891165,
0.0365343767242302, 0.0680387334780893, 0.0359449679962688, 0.0914223347587717,
0.250090013711688, 0.0285907018967329, 0.0332181584655898, 0.999507574272309,
0.105444012216585, 0.187575638790271, 0.162379131764237, 0.102700208200375,
0.09178360736775, 0.163465216529218, 0.0729776861513878, 0.236016339389482,
0.0588574175467754, 0.0550992673681143, 0.122626443155744, 0.0918424812269966,
0.146120253221757, 0.0577653939175298, 0.0348411397934349, 0.0473716341969161,
0.0178728863162361, 0.0527367807713118, 0.0479903568707429, 0.0730610057439529,
0.0930097224453987, 0.0658436634783048, 0.190704292535876, 0.0358726716365566,
0.0307972881129445, 0.0189626337594551, 0.000000000000000111022302462516,
0.000000000000000111022302462516, 0.762963505977553, 0.000000000000000111022302462516,
0.762963505977553, 0.000000000000000111022302462516, 0.000000000000000111022302462516,
0.000000000000000111022302462516, 0.000000000000000111022302462516,
0.000000000000000111022302462516, 0.000000000000000111022302462516,
0.000000000000000111022302462516, 0.000000000000000111022302462516,
0.000000000000000111022302462516, 0.000000000000000111022302462516,
0.0145186393898035, 0.0188147774806442, 0.00921565692607718,
0.16582527531479, 0.0687727632750558, 0.204529458170385, 0.0716012445553365,
0.0718954998189065, 0.0277281993654519, 0.0674740371917119, 0.072012888372702,
0.0734119880053119, 0.0673902818072857, 0.0331949118036344, 0.0574456113479402,
0.0551005875496144, 0.0830738397892672, 0.0612316674931673, 0.0375821407994346,
0.0540598964852267, 0.937300545235406, 0.764273407958804, 0.310278765419343,
0.115409839050865, 0.180334165153821, 0.0744074972905282, 0.0539052279373005,
0.1155899920352, 0.607098700786289, 0.475193951744525, 0.500999897379361,
0.452694613243503, 0.339737698721805, 0.119110509053642, 0.414782001570446,
0.176478247451898, 0.0118929448699869, 0.0646300143287915, 0.0658444055780221,
0.0365112498265521, 0.0290522222936732, 0.0361261162544974, 0.55126787604404,
0.00787685460932497, 0.0125336454598935, 0.171603271017195, 0.318299749392132,
0.0664370130236998, 0.0919497640181351, 0.211041532792102, 0.269396236145632,
0.187866298055647, 0.059969004318524, 0.0559161287155419, 0.0885832743614622,
0.451411471333919, 0.439612859187183, 0.0514195289243331, 0.0498694766579967,
0.0919350781544515, 0.223510070474301, 0, 1, 0.0646708402796897,
0.0825731393695558, 0.10537056250177, 0.0696122176816857, 0.0424418302212671,
0.0478766288959678, 0.955958881662633, 0.0138346259942443, 0.0138346259942443,
0.95933698140034, 0.95556392397955, 0.95556392397955, 0.0612316691720032,
0.0327534828616965, 0.959216097627497, 0.0327534828616965, 0.959216097627497,
0.958839379113644, 0.0494138799831281, 0.0702859969103062, 0.957760286279822,
0.959990040058998, 0.0665164367326447, 0.953377974332167, 0.0852324991199898,
0.0335958391478673, 0.0938256364517924, 0.0288861431449183, 0.0927286486173231,
0.10569451898322, 0.0495326021541909, 0.0472476582675493, 0.17378604346306,
0.403552152727797, 0.264561987793531, 0.122322841743767, 0.0776316684095162,
0.205840395760264, 0.17260647446031, 0.105649001057342, 0.0647680128457088,
0.0386101299858582, 0.0355308548901323, 0.179115185681647, 0.0360302297350318,
0.0428351049609113, 0.0731618616948397, 0.098280569756635, 0.120526033566675,
0.0522118355470956, 0.403101292203212, 0.0891701855562025, 0.0810865491545684,
0.096919562507692, 0.122031932526703, 0.16186248758732, 0.168732393772878,
0.0279987511755512, 0.0309210793450959, 0.341002639185584, 0.0546379469643276,
0.0305462198188776, 0.031657147750161, 0.0364650920878082)), row.names = c(NA,
-246L), class = "data.frame")
回答1:
We need a map2 at the end because we are applying augment on corresponding list elements of 'kmeans' and 'value' column
library(tidyverse)
library(broom)
kclust2 <- results %>%
as_tibble() %>%
select(-id_row) %>%
group_by(year_row) %>%
nest(.key = "value") %>%
filter(map_int(value, nrow) > 4) %>%
mutate(kmeans = map(value, ~kmeans(.x[[1]],
centers = 4, iter.max = 10, nstart = 1)),
tidied = map(kmeans, tidy),
glanced = map(kmeans, glance),
augmented = map2(kmeans, value, augment))
来源：https://stackoverflow.com/questions/55775654/custom-function-in-mutate-tibble