addEventLines & yearmon index

[paessens]

Description

I could not use addEventLines having both xts' indexed with yearmon format

Expected behavior

same as with YYYY-MM-DD indexes

Minimal, reproducible example

require(magrittr)
require(xts)
require(ecb)

data.frame(
  begin = c("1998-10-01","2000-04-01","2001-10-01","2008-10-01","2009-10-01","2020-04-01"),
  events = c("LTCM","dot com bubble","9/11","Lehman Bros.","Eurozone Crisis","Pandemic")) %>%
  read.zoo(FUN=as.yearmon) %>%
  as.xts() -> historical

'ICP.M.U2.N.000000.4.ANR' %>% ecb::get_data() %>%
  .[c('obstime','obsvalue')] %>%
  read.zoo(FUN=as.yearmon) %>% as.xts() -> HICP

plot(HICP,
     col='navy',lty=1,lwd=1.5, cex=0.5,
     grid.ticks.lty="dotted")
addEventLines(historical, col="#3357FF", cex=1,lty=1.5,lwd=2, srt=90, pos=2,offset=-.6,on=0)

Session Info

R version 4.0.5 (2021-03-31) Platform: x86_64-pc-linux-gnu (64-bit) Running under: Debian GNU/Linux 10 (buster)

Matrix products: default BLAS: /usr/lib/x86_64-linux-gnu/openblas/libblas.so.3 LAPACK: /usr/lib/x86_64-linux-gnu/libopenblasp-r0.3.5.so

locale: [1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C LC_TIME=en_US.UTF-8 LC_COLLATE=en_US.UTF-8 LC_MONETARY=en_US.UTF-8
[6] LC_MESSAGES=en_US.UTF-8 LC_PAPER=en_US.UTF-8 LC_NAME=C LC_ADDRESS=C LC_TELEPHONE=C
[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C

attached base packages: [1] stats graphics grDevices datasets utils methods base

other attached packages: [1] magrittr_2.0.1 ecb_0.4.0 xts_0.12.1 zoo_1.8-9

loaded via a namespace (and not attached): [1] Rcpp_1.0.6 lattice_0.20-44 XML_3.99-0.6 rsvg_2.1.2 digest_0.6.27 plyr_1.8.6 R6_2.5.0 grid_4.0.5
[9] rsdmx_0.6 evaluate_0.14 httr_1.4.2 quantmod_0.4.18 rlang_0.4.11 cachem_1.0.4 renv_0.13.2 curl_4.3.1
[17] TTR_0.24.2 rmarkdown_2.8 tools_4.0.5 xfun_0.22 yaml_2.2.1 fastmap_1.1.0 compiler_4.0.5 htmltools_0.5.1.1 [25] memoise_2.0.0 knitr_1.33

[paessens]

error message:

Error in index<-.xts(*tmp*, value = order.by) : unsupported ‘index’ index type of class ‘integer’ In addition: Warning messages: 1: In as_numeric(YYYY) : NAs introduced by coercion 2: In as_numeric(YYYY) : NAs introduced by coercion 3: In as_numeric(YYYY) : NAs introduced by coercion 4: In .parseISO8601(ii, .index(x)[1], .index(x)[nr], tz = tz) : cannot determine first and last time from Jan 1997/Apr 2021

[paessens]

this works as expected (converting monthy data to daily, wrt date format)

require(magrittr) require(xts) require(ecb)

data.frame( begin = c("1998-10-01","2000-04-01","2001-10-01","2008-10-01","2009-10-01","2020-04-01"), events = c("LTCM","bubble.com ","9/11","Lehman Bros.","Eurozone Crisis","Pandemic")) %>% read.zoo() %>% as.xts() -> historical

'ICP.M.U2.N.000000.4.ANR' %>% ecb::get_data() %>% .[c('obstime','obsvalue')] -> HICP

HICP$obstime %<>% paste0('-01') HICP$obstime %<>% as.Date() HICP %<>% read.zoo() %>% as.xts()

plot(HICP, col='navy',lty=1,lwd=1.5,cex=0.5,grid.ticks.lty="dotted") addEventLines(historical, col="#FF480B", cex=1,lty=1.5,lwd=2, srt=90, pos=2,offset=-.6,on=0)

[joshuaulrich]

I can replicate. Here's minimal example that doesn't require installing several other packages:

library(xts)

historical <-
  data.frame(
  begin = c("1998-10-01","2000-04-01","2001-10-01","2008-10-01","2009-10-01","2020-04-01"),
  events = c("LTCM","dot com bubble","9/11","Lehman Bros.","Eurozone Crisis","Pandemic"))
historical <- as.xts(read.zoo(historical, FUN=as.yearmon))

HICP <-
structure(c(2, 1.8, 1.6, 1.3, 1.4, 1.4, 1.5, 1.7, 1.6, 1.5, 1.6, 1.5, 1.1, 1.1, 1.1, 1.4, 1.3, 1.3, 1.3,
    1.1, 1, 0.9, 0.8, 0.8, 0.8, 0.7, 0.9, 1.1, 0.9, 0.9, 1, 1.1, 1.2, 1.3, 1.5, 1.7, 1.9, 1.9, 2, 1.7,
    1.8, 2.1, 2.1, 2, 2.4, 2.4, 2.5, 2.5, 2, 2, 2.2, 2.7, 3.1, 2.9, 2.5, 2.3, 2.2, 2.2, 2, 2.1, 2.6,
    2.5, 2.5, 2.4, 2.1, 1.9, 2, 2.1, 2.1, 2.3, 2.3, 2.3, 2.1, 2.4, 2.4, 2.1, 1.8, 2, 1.9, 2, 2.1, 2,
    2.2, 2, 1.8, 1.6, 1.7, 2.1, 2.5, 2.4, 2.3, 2.4, 2.1, 2.4, 2.2, 2.3, 1.9, 2.1, 2.2, 2.1, 2, 2, 2.1,
    2.2, 2.6, 2.5, 2.3, 2.3, 2.4, 2.4, 2.2, 2.4, 2.5, 2.5, 2.4, 2.3, 1.8, 1.6, 1.8, 1.9, 1.8, 1.8, 1.9,
    1.9, 1.9, 1.9, 1.8, 1.7, 2.1, 2.5, 3.1, 3.1, 3.2, 3.3, 3.6, 3.3, 3.7, 3.9, 4.1, 3.8, 3.6, 3.2, 2.1,
    1.6, 1.1, 1.2, 0.6, 0.6, 0, -0.1, -0.6, -0.2, -0.3, -0.1, 0.5, 0.9, 0.9, 0.8, 1.6, 1.6, 1.7, 1.5,
    1.7, 1.6, 1.9, 1.9, 1.9, 2.2, 2.3, 2.4, 2.7, 2.8, 2.7, 2.7, 2.6, 2.5, 3, 3, 3, 2.8, 2.7, 2.7, 2.7,
    2.6, 2.4, 2.4, 2.4, 2.6, 2.6, 2.5, 2.2, 2.2, 2, 1.9, 1.7, 1.2, 1.4, 1.6, 1.6, 1.3, 1.1, 0.7, 0.9,
    0.8, 0.8, 0.7, 0.5, 0.7, 0.5, 0.5, 0.4, 0.4, 0.3, 0.4, 0.3, -0.2, -0.6, -0.3, -0.1, 0.2, 0.6, 0.5,
    0.5, 0.4, 0.2, 0.4, 0.1, 0.3, 0.3, -0.1, 0, -0.3, -0.1, 0, 0.2, 0.2, 0.4, 0.5, 0.6, 1.1, 1.7, 2,
    1.5, 1.9, 1.4, 1.3, 1.3, 1.5, 1.6, 1.4, 1.5, 1.3, 1.3, 1.1, 1.4, 1.2, 2, 2, 2.2, 2.1, 2.1, 2.3,
    1.9, 1.5, 1.4, 1.5, 1.4, 1.7, 1.2, 1.3, 1, 1, 0.8, 0.7, 1, 1.3, 1.4, 1.2, 0.7, 0.3, 0.1, 0.3, 0.4,
    -0.2, -0.3, -0.3, -0.3, -0.3, 0.9, 0.9, 1.3, 1.6, 2), .Dim = c(293L, 1L), .Dimnames = list( NULL, NULL),
    index = structure(c(852076800, 854755200, 857174400, 859852800, 862444800, 865123200, 867715200,
    870393600, 873072000, 875664000, 878342400, 880934400, 883612800, 886291200, 888710400, 891388800,
    893980800, 896659200, 899251200, 901929600, 904608000, 907200000, 909878400, 912470400, 915148800,
    917827200, 920246400, 922924800, 925516800, 928195200, 930787200, 933465600, 936144000, 938736000,
    941414400, 944006400, 946684800, 949363200, 951868800, 954547200, 957139200, 959817600, 962409600,
    965088000, 967766400, 970358400, 973036800, 975628800, 978307200, 980985600, 983404800, 986083200,
    988675200, 991353600, 993945600, 996624000, 999302400, 1001894400, 1004572800, 1007164800,
    1009843200, 1012521600, 1014940800, 1017619200, 1020211200, 1022889600, 1025481600, 1028160000,
    1030838400, 1033430400, 1036108800, 1038700800, 1041379200, 1044057600, 1046476800, 1049155200,
    1051747200, 1054425600, 1057017600, 1059696000, 1062374400, 1064966400, 1067644800, 1070236800,
    1072915200, 1075593600, 1078099200, 1080777600, 1083369600, 1086048000, 1088640000, 1091318400,
    1093996800, 1096588800, 1099267200, 1101859200, 1104537600, 1107216000, 1109635200, 1112313600,
    1114905600, 1117584000, 1120176000, 1122854400, 1125532800, 1128124800, 1130803200, 1133395200,
    1136073600, 1138752000, 1141171200, 1143849600, 1146441600, 1149120000, 1151712000, 1154390400,
    1157068800, 1159660800, 1162339200, 1164931200, 1167609600, 1170288000, 1172707200, 1175385600,
    1177977600, 1180656000, 1183248000, 1185926400, 1188604800, 1191196800, 1193875200, 1196467200,
    1199145600, 1201824000, 1204329600, 1207008000, 1209600000, 1212278400, 1214870400, 1217548800,
    1220227200, 1222819200, 1225497600, 1228089600, 1230768000, 1233446400, 1235865600, 1238544000,
    1241136000, 1243814400, 1246406400, 1249084800, 1251763200, 1254355200, 1257033600, 1259625600,
    1262304000, 1264982400, 1267401600, 1270080000, 1272672000, 1275350400, 1277942400, 1280620800,
    1283299200, 1285891200, 1288569600, 1291161600, 1293840000, 1296518400, 1298937600, 1301616000,
    1304208000, 1306886400, 1309478400, 1312156800, 1314835200, 1317427200, 1320105600, 1322697600,
    1325376000, 1328054400, 1330560000, 1333238400, 1335830400, 1338508800, 1341100800, 1343779200,
    1346457600, 1349049600, 1351728000, 1354320000, 1356998400, 1359676800, 1362096000, 1364774400,
    1367366400, 1370044800, 1372636800, 1375315200, 1377993600, 1380585600, 1383264000, 1385856000,
    1388534400, 1391212800, 1393632000, 1396310400, 1398902400, 1401580800, 1404172800, 1406851200,
    1409529600, 1412121600, 1414800000, 1417392000, 1420070400, 1422748800, 1425168000, 1427846400,
    1430438400, 1433116800, 1435708800, 1438387200, 1441065600, 1443657600, 1446336000, 1448928000,
    1451606400, 1454284800, 1456790400, 1459468800, 1462060800, 1464739200, 1467331200, 1470009600,
    1472688000, 1475280000, 1477958400, 1480550400, 1483228800, 1485907200, 1488326400, 1491004800,
    1493596800, 1496275200, 1498867200, 1501545600, 1504224000, 1506816000, 1509494400, 1512086400,
    1514764800, 1517443200, 1519862400, 1522540800, 1525132800, 1527811200, 1530403200, 1533081600,
    1535760000, 1538352000, 1541030400, 1543622400, 1546300800, 1548979200, 1551398400, 1554076800,
    1556668800, 1559347200, 1561939200, 1564617600, 1567296000, 1569888000, 1572566400, 1575158400,
    1577836800, 1580515200, 1583020800, 1585699200, 1588291200, 1590969600, 1593561600, 1596240000,
    1598918400, 1601510400, 1604188800, 1606780800, 1609459200, 1612137600, 1614556800, 1617235200,
    1619827200), tzone = "UTC", tclass = "yearmon"), class = c("xts", "zoo"))

plot(HICP, col='navy',lty=1,lwd=1.5,cex=0.5,grid.ticks.lty="dotted")
addEventLines(historical, col="#FF480B", cex=1,lty=1.5,lwd=2, srt=90, pos=2,offset=-.6,on=0)

Looks like the problem is this line in addEventLines():

    # xdata is HICP and xsubset is ""
    # result is "Jan 1997/May 2021"
    subset.range <- paste(start(xdata[xsubset]), end(xdata[xsubset]),sep="/")

[paessens]

Much appreciated, Joshua

I certainly bear on xts for plotting and analysing time series, however, the work around is easy. But the code looks more concise without work arounds ;-) Here is a glimpse of the most recent project ... https://ilj.at/we1

[joshuaulrich]

You're welcome! I'd appreciate it if you could test the patch on other data, especially other frequencies (e.g. quarters, days, hours).

[paessens]

will do next week if you provide the patch

On 13. Jun 2021, at 18:56, Joshua Ulrich @.***> wrote:

You're welcome! I'd appreciate it if you could test the patch on other data, especially other frequencies (e.g. quarters, days, hours).

— You are receiving this because you authored the thread. Reply to this email directly, view it on GitHub https://github.com/joshuaulrich/xts/issues/353#issuecomment-860241016, or unsubscribe https://github.com/notifications/unsubscribe-auth/ABVW6OYT3LLJIDNGZNM7P2DTSTPL7ANCNFSM446DBCOA.

[joshuaulrich]

Patch is on branch 353-addEventLines-yearmon, in the commit referenced in this issue: 81ef49af39cd6ba6d1b118eb3c4f1d27a54c3564

[paessens]

copy that

On 13. Jun 2021, at 19:17, Joshua Ulrich @.***> wrote:

Patch is on branch 353-addEventLines-yearmon, in the commit referenced in this issue: 81ef49a https://github.com/joshuaulrich/xts/commit/81ef49af39cd6ba6d1b118eb3c4f1d27a54c3564 — You are receiving this because you authored the thread. Reply to this email directly, view it on GitHub https://github.com/joshuaulrich/xts/issues/353#issuecomment-860243599, or unsubscribe https://github.com/notifications/unsubscribe-auth/ABVW6OYI3WEWVHDVJNBFUALTSTR3ZANCNFSM446DBCOA.

[joshuaulrich]

@paessens, have you had a chance to test this?

[paessens]

Oh oh, sorry, missed that. Will do tomorrow and come back to you, I promise.

Heinrich

On 30. Jun 2021, at 13:28, Joshua Ulrich @.***> wrote:

@paessens https://github.com/paessens, have you had a chance to test this?

— You are receiving this because you were mentioned. Reply to this email directly, view it on GitHub https://github.com/joshuaulrich/xts/issues/353#issuecomment-871321997, or unsubscribe https://github.com/notifications/unsubscribe-auth/ABVW6O7F2KKWWPJBR7E6KUDTVL5VJANCNFSM446DBCOA.

[paessens]

alright -- tested and the plot is as expected (three cases: simple date, yearmon and date+time) script and data is attached for replication tst-xts.R.txt ecb_2021-07-02.RData.zip Rplot-date.pdf Rplot-yearmon.pdf Rplot-posix.pdf

well done Joshua many thanks - much appreciated Heinrich

[joshuaulrich]

Thanks for testing! I've merged this and it will be in the next release.

[paessens]

awesome