I am trying to plot the following variables:
> df1$var1
[1] "2012Q1" "2012Q2" "2012Q3" "2012Q4" "2013Q1" "2013Q2" "2013Q3" "2013Q4" "2014Q1" "2014Q2"
[11] "2014Q3" "2014Q4" "2015Q1" "2015Q2" "2015Q3" "2015Q4" "2016Q1" "2016Q2" "2016Q3" "2016Q4"
[21] "2017Q1" "2017Q2" "2017Q3" "2017Q4" "2018Q1" "2018Q2" "2018Q3" "2018Q4" "2019Q1" "2019Q2"
> df1$var2
[1] NA NA NA NA 444618.3 1556125.2 744145.1 844862.2 773188.2
[10] 1204732.2 1832308.2 1732186.6 1475089.7 1238791.2 772359.0 927111.5 982978.9 581415.1
[19] 489457.8 446419.0 403841.0 654630.9 753729.4 513755.0 587031.5 465808.7 462710.4
[28] 537923.9 409037.8 785118.7
using the following code:
plot(df1$var1,df1$var2,type="l",col="red")
which gives me the following error:
Error in plot.window(...) : need finite 'xlim' values
In addition: Warning messages:
1: In xy.coords(x, y, xlabel, ylabel, log) : NAs introduced by coercion
2: In min(x) : no non-missing arguments to min; returning Inf
3: In max(x) : no non-missing arguments to max; returning -Inf
how can I make it work?
User #zx8754 marked this question as a duplicate of this question and of this question.
The problem here is that var1 is of class "character", like in the questions believed to be duplicates, but it is obvious from its contents that what is needed is a year/quarter object.
Package zoo has a function ideal for this, as.yearqtr.
yq <- zoo::as.yearqtr(df1$var1)
plot(yq, df1$var2, type = "l", col = "red")
Data in dput format.
df1 <-
structure(list(var1 = c("2012Q1", "2012Q2", "2012Q3", "2012Q4",
"2013Q1", "2013Q2", "2013Q3", "2013Q4", "2014Q1", "2014Q2", "2014Q3",
"2014Q4", "2015Q1", "2015Q2", "2015Q3", "2015Q4", "2016Q1", "2016Q2",
"2016Q3", "2016Q4", "2017Q1", "2017Q2", "2017Q3", "2017Q4", "2018Q1",
"2018Q2", "2018Q3", "2018Q4", "2019Q1", "2019Q2"), var2 = c(NA,
NA, NA, NA, 444618.3, 1556125.2, 744145.1, 844862.2, 773188.2,
1204732.2, 1832308.2, 1732186.6, 1475089.7, 1238791.2, 772359,
927111.5, 982978.9, 581415.1, 489457.8, 446419, 403841, 654630.9,
753729.4, 513755, 587031.5, 465808.7, 462710.4, 537923.9, 409037.8,
785118.7)), class = "data.frame", row.names = c(NA, -30L))
Warning messages are a good information i want to know. But i just want to know it one time!
So this function throws 2 different warnings and repeats it 20 times.
How can i tell R to only print unique warnings. Im looking for a gerenal solution.
Warning messages:
1: NAs introduced by coercion
2: In sqrt(-1) : NaNs produced
Here is my example:
foobar <- function(n=20) {
for (i in 1:n) {
as.numeric("b")
sqrt(-1)
}
}
foobar()
To return only unique warning strings, use
unique(warnings())
Now, a problem you may have is that your function has more than 50 warnings, in which case warnings() will not catch them all. To workaround this, you can increase nwarnings in options to e.g. 10000 as suggested in the help page of warnings.
options(nwarnings = 10000)
Example:
foobar <- function(n=20) {
warning("First warning")
for (i in 1:n) {
as.numeric("b")
sqrt(-1)
}
warning("Last warning")
}
foobar(60)
unique(warnings())
## Warning messages:
## 1: In foobar(60) : First warning
## 2: NAs introduced by coercion
## 3: In sqrt(-1) : NaNs produced
op <- options(nwarnings = 10000)
foobar(60)
unique(warnings())
## Warning messages:
## 1: In foobar(60) : First warning
## 2: NAs introduced by coercion
## 3: In sqrt(-1) : NaNs produced
## 4: In foobar(60) : Last warning
options(op)
I have the following code, which is giving me the an error:
# Read input dataset from CSV file
input_dataset <-
read.csv("C:\\Users\\sw029693\\Desktop\\Overtime_work_hrs_analytics\\input_dataset.csv", header = TRUE)
wss <- (nrow(input_dataset)-1)*sum(apply(input_dataset,2,var))
which gives the following error:
Warning messages:
1: In FUN(newX[, i], ...) : NAs introduced by coercion
2: In FUN(newX[, i], ...) : NAs introduced by coercion
3: In FUN(newX[, i], ...) : NAs introduced by coercion
4: In FUN(newX[, i], ...) : NAs introduced by coercion
5: In FUN(newX[, i], ...) : NAs introduced by coercion
> wss
[1] NA
> colnames(input_dataset)
[1] "client" "domain" "user_name"
"cdf_display" "position" "shift_start"
[7] "shift_end" "shift_length_avg" "patients_seen_cnt"
It looks like the wss is NA, I am not sure why. Any ideas?
K-means only supports numerical data.
You columns user_name etc. probably are not numerical.
Bring your data into the appropriate format first.
I'm trying to use secr.fit() in secr package.
> C<- read.capthist('captfile4.txt', 'trapfile2.txt',detector = 'proximity')
No errors found :-)
> secr0 <- secr.fit(C, model = g0~1, buffer = 100, trace = FALSE)"
"Error in uniroot(naiveRPSVcall, lower = obsRPSV/10, upper = obsRPSV * : f() values at end points not of opposite sign
In addition: Warning messages:
1: In min(x) : no non-missing arguments to min; returning Inf
2: In max(x) : no non-missing arguments to max; returning -Inf
3: In min(x) : no non-missing arguments to min; returning Inf
4: In max(x) : no non-missing arguments to max; returning -Inf
Error in naivecap2(0.001, sigma = tempsigma, cap = cpa) : NA/NaN/Inf in foreign function call (arg 3)" .
Can anyone please tell me why I get this error? Thank You.
I would like to chart SPX using quantmod::chart_Series() and below draw changes in GDP and 12 month SMA of changes of GDP. No matter how I try to do it (what combinations I use) eithe errors occur or quantmod::chart_Series() displays just partial plot.
require(quantmod)
FRED.symbols <- c("GDPC96")
getSymbols(FRED.symbols, src="FRED")
SPX <- getSymbols("^GSPC", auto.assign=FALSE, from="1900-01-01")
subset="2000/"
chart_Series(SPX, subset=subset)
add_TA(GDPC96)
add_TA(ROC(GDPC96, type="discrete"))
add_TA(SMA(ROC(GDPC96, type="discrete"), n=4), on=3, col="blue")
EDIT: Actually, it seems to me that this is a quantmod::chart_series() problem when using quarterly data:
subset <- "2000/"
chart_Series(to.quarterly(SPX, drop.time=TRUE), subset=subset)
add_TA(SMA(Cl(to.quarterly(SPX, drop.time=TRUE))))
> subset <- "2000/"
> chart_Series(to.quarterly(SPX, drop.time=TRUE), subset=subset)
> add_TA(SMA(Cl(to.quarterly(SPX, drop.time=TRUE))))
Error in xy.coords(x, y) : 'x' and 'y' lengths differ
In addition: Warning messages:
1: In as_numeric(H) : NAs introduced by coercion
2: In as_numeric(H) : NAs introduced by coercion
3: In as_numeric(H) : NAs introduced by coercion
This does produce SPX plot on main panel, but leaves empty second and third panel.
Then I tried to play around with having same index on data, same lengths etc.
chart_Series(head(to.quarterly(SPX, drop.time="TRUE"), -1), subset=subset)
add_TA(to.quarterly(GDPC96, drop.time="TRUE", OHLC=FALSE))
add_TA(ROC(to.quarterly(GDPC96, drop.time="TRUE", OHLC=FALSE), type="discrete"))
add_TA(SMA(ROC(to.quarterly(GDPC96, drop.time="TRUE", OHLC=FALSE), type="discrete"), n=4), on=3, col="blue")
And result is errors all over:
> chart_Series(head(to.quarterly(SPX, drop.time="TRUE"), -1), subset=subset)
> add_TA(to.quarterly(GDPC96, drop.time="TRUE", OHLC=FALSE))
Error in xy.coords(x, y) : 'x' and 'y' lengths differ
In addition: Warning messages:
1: In as_numeric(H) : NAs introduced by coercion
2: In as_numeric(H) : NAs introduced by coercion
3: In as_numeric(H) : NAs introduced by coercion
> add_TA(ROC(to.quarterly(GDPC96, drop.time="TRUE", OHLC=FALSE), type="discrete"))
Error in xy.coords(x, y) : 'x' and 'y' lengths differ
In addition: Warning messages:
1: In as_numeric(H) : NAs introduced by coercion
2: In as_numeric(H) : NAs introduced by coercion
3: In as_numeric(H) : NAs introduced by coercion
> add_TA(SMA(ROC(to.quarterly(GDPC96, drop.time="TRUE", OHLC=FALSE), type="discrete"), n=4), on=3, col="blue")
Error in xy.coords(x, y) : 'x' and 'y' lengths differ
In addition: Warning messages:
1: In as_numeric(H) : NAs introduced by coercion
2: In as_numeric(H) : NAs introduced by coercion
3: In as_numeric(H) : NAs introduced by coercion
Using
tail(to.quarterly(SPX, drop.time="TRUE"))
tail(to.quarterly(GDPC96, drop.time="TRUE", OHLC=FALSE))
tail(ROC(to.quarterly(GDPC96, drop.time="TRUE", OHLC=FALSE), type="discrete"))
tail(SMA(ROC(to.quarterly(GDPC96, drop.time="TRUE", OHLC=FALSE), type="discrete"), n=4))
dput(to.quarterly(SPX, drop.time="TRUE"))
dput(to.quarterly(GDPC96, drop.time="TRUE", OHLC=FALSE))
dput(ROC(to.quarterly(GDPC96, drop.time="TRUE", OHLC=FALSE), type="discrete"))
dput(SMA(ROC(to.quarterly(GDPC96, drop.time="TRUE", OHLC=FALSE), type="discrete"), n=4))
all looks good to me.
My sessionInfo():
> sessionInfo()
R version 2.15.0 (2012-03-30)
Platform: x86_64-pc-linux-gnu (64-bit)
locale:
[1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C
[3] LC_TIME=en_US.UTF-8 LC_COLLATE=en_US.UTF-8
[5] LC_MONETARY=en_US.UTF-8 LC_MESSAGES=en_US.UTF-8
[7] LC_PAPER=en_US.UTF-8 LC_NAME=en_US.UTF-8
[9] LC_ADDRESS=en_US.UTF-8 LC_TELEPHONE=en_US.UTF-8
[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=en_US.UTF-8
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] quantmod_0.3-18 TTR_0.21-0 xts_0.8-7 zoo_1.7-7
[5] Defaults_1.1-1 rj_1.1.0-4
loaded via a namespace (and not attached):
[1] grid_2.15.0 lattice_0.20-0 tools_2.15.0
Any ideas what might be the solution for these issues?
EDIT: This seems to be a quantmod::chart_Series() bug. If I do this:
subset <- "1990/"
test <- cbind(head(to.quarterly(SPX, drop.time="TRUE"), -1)[subset],
to.quarterly(GDPC96, drop.time="TRUE", OHLC=FALSE)[subset],
ROC(to.quarterly(GDPC96, drop.time="TRUE", OHLC=FALSE), type="discrete")[subset],
SMA(ROC(to.quarterly(GDPC96, drop.time="TRUE", OHLC=FALSE), type="discrete"), n=4)[subset])
test$test <- 1
subset <- "2000/"
chart_Series(OHLC(test), subset=subset)
add_TA(test$test)
add_TA(test$GDPC96)
> test$test <- 1
> subset <- "2000/"
> chart_Series(OHLC(test), subset=subset)
> add_TA(test$test)
Error in xy.coords(x, y) : 'x' and 'y' lengths differ
In addition: Warning messages:
1: In as_numeric(H) : NAs introduced by coercion
2: In as_numeric(H) : NAs introduced by coercion
3: In as_numeric(H) : NAs introduced by coercion
> add_TA(test$GDPC96)
Error in xy.coords(x, y) : 'x' and 'y' lengths differ
In addition: Warning messages:
1: In as_numeric(H) : NAs introduced by coercion
2: In as_numeric(H) : NAs introduced by coercion
3: In as_numeric(H) : NAs introduced by coercion
> traceback()
14: stop("'x' and 'y' lengths differ") at chart_Series.R#510
13: xy.coords(x, y) at chart_Series.R#510
12: plot.xy(xy.coords(x, y), type = type, ...) at chart_Series.R#510
11: lines.default(ta.x, as.numeric(ta.y[, i]), col = col, ...) at chart_Series.R#510
10: lines(ta.x, as.numeric(ta.y[, i]), col = col, ...) at chart_Series.R#510
9: plot_ta(x = current.chob(), ta = get("x"), on = NA, taType = NULL,
col = 1) at replot.R#238
8: eval(expr, envir, enclos) at replot.R#238
7: eval(aob, env) at replot.R#238
6: FUN(X[[12L]], ...) at replot.R#230
5: lapply(x$Env$actions, function(aob) {
if (attr(aob, "frame") > 0) {
x$set_frame(attr(aob, "frame"), attr(aob, "clip"))
env <- attr(aob, "env")
if (is.list(env)) {
env <- unlist(lapply(env, function(x) eapply(x, eval)),
recursive = FALSE)
}
eval(aob, env)
}
}) at replot.R#230
4: plot.replot(x, ...)
3: plot(x, ...)
2: print.replot(<environment>)
1: print(<environment>)
Any ideas on how to get this fixed?
I had a similar error several days ago. I found that the problem was in add_TA with the line:
ta.x <- as.numeric(na.approx(ta.adj[, 1]))
na.approx uses approx with rule = 1 by default, which leaves trailing NAs in the list if the last timestamp in the original data is before the last timestamp in the TA data. Changing that line to set rule = 2 fixed the problem.
ta.x <- as.numeric(na.approx(ta.adj[, 1], rule=2))
I just wrote a long "answer" confirming your problems, even after some data massaging, and even using the older chartSeries function. Then I realized that add_TA() is perhaps the wrong function. This approach works:
par(mfrow=c(2,1))
chart_Series(SPX)
chart_Series(GDPC96)
(See R/quantmod: multiple charts all using the same y-axis for an alternative approach using the layout command.)
Or with the subset:
par(mfrow=c(2,1))
chart_Series(SPX,subset="2000/")
chart_Series(GDPC96,subset="2000/")
(NB. the two datasets end at different place, so don't quite line up.)
Incidentally, there is one definite bug in chart_Series with quarterly data: the x-axis labels look like "%n%b%n2010".
q.SPX=to.quarterly(SPX)
chart_Series(q.SPX)