na

I have a data.table that contains some groups. I operate on each group and some groups return numbers, others return NA . For some reason data.table has trouble putting everything back together. Is this a bug or am I misunderstanding? Here is an example: dtb <- data.table(a=1:10) f <- function(x) {if (x==9) {return(NA)} else { return(x)}} dtb[,f(a),by=a] Error in `[.data.table`(dtb, , f(a), by = a) : columns of j don't evaluate to consistent types for each group: result for group 9 has column 1 type 'logical' but expecting type 'integer' My understanding was that NA is compatible with numbers

I'm using ggplot to map data values to a (fortified) SpatialPolygonsDataFrame, but many of the polygons have NA values because there is no data available. I used na.value = "white" to display the missing data correctly, but I'd like to add a box with a white fill in the legend (or a separate legend) with the label "no data". library(ggplot2) india.df <- read.csv('india.df.csv') # (I don't know how to provide this file to make the code reproducible) ggplot() + geom_polygon(data=india.df, aes(x = long, y = lat, group = group, fill=Area_pct)) + scale_fill_gradient(low="orange2", high="darkblue",

To simplify, I have a data set which is as follows: b <- 1:6 # > b # [1] 1 2 3 4 5 6 jnk <- c(2, 4, 5, NA, 7, 9) # > jnk # [1] 2 4 5 NA 7 9 When I try: cor(b, jnk, na.rm=TRUE) I get: > cor(b, jnk, na.rm=T) Error in cor(b, jnk, na.rm = T) : unused argument (na.rm = T) I've also tried na.action = na.exclude , etc. None seem to work. It'd be really helpful to know what the issue is and how I can fix it. Thanks. Spacedman TL; DR: Use instead: cor(b, jnk, use="complete.obs") Read ?cor : cor(x, y = NULL, use = "everything", method = c("pearson", "kendall", "spearman")) It doesn't have na.rm , it has

I'm trying to plot a v. simple boxplot in ggplot2. I have species richness vs. landuse class. However, I have 2 NA's in my data. For some strange reason, they're being plotted, even when they're being understood as NA's by R. Any suggestion to remove them? The code I'm using is: ggplot(data, aes(x=luse, y=rich))+ geom_boxplot(mapping = NULL, data = NULL, stat = "boxplot", position = "dodge", outlier.colour = "red", outlier.shape = 16, outlier.size = 2, notch = F, notchwidth = 0.5)+ scale_x_discrete("luse", drop=T)+ geom_smooth(method="loess",aes(group=1)) However, the graph includes 2 NA's for

I need to fill in NA rows with the previous row value, but only until a criteria is not changed. As a simple example for days of week, meals and prices: Day = c("Mon", "Tues", "Wed", "Thus", "Fri", "Sat","Sun","Mon", "Tues", "Wed", "Thus", "Fri", "Sat","Sun") Meal = c("B","B","B","B","B","D","D","D","D","L","L", "L","L","L") Price = c(NA, 20, NA,NA,NA,NA,NA,15,NA,NA,10,10,NA,10) df = data.frame(Meal,Day ,Price ) df Meal Day Price 1 B Mon NA 2 B Tues 20 3 B Wed NA 4 B Thus NA 5 B Fri NA 6 D Sat NA 7 D Sun NA 8 D Mon 15 9 D Tues NA 10 L Wed NA 11 L Thus 10 12 L Fri 10 13 L Sat NA 14 L Sun 10 I

I am computing a dplyr::summarize across a dataframe of sales data. I do a group-by (S,D,Y), then within each group, compute medians and means for weeks 5..43, then merge those back into the parent df. Variable X is sales. X is never NA (i.e. there are no explicit NAs anywhere in df), but if there is no data (as in, no sales) for that S,D,Y and set of weeks, there will simply be no row with those values in df (take it that means zero sales for that particular set of parameters). In other words, impute X=0 in any structurally missing rows (but I hope I don't need to melt/cast the original df,

I have a data frame with several factor columns containing NaN 's that I would like to convert to NA 's (the NaN seems to be a problem for using linear regression objects to predict on new data). > tester1 <- c("2", "2", "3", "4", "2", "3", NaN) > tester1 [1] "2" "2" "3" "4" "2" "3" "NaN" > tester1[is.nan(tester1)] = NA > tester1 [1] "2" "2" "3" "4" "2" "3" "NaN" > tester1[is.nan(tester1)] = "NA" > tester1 [1] "2" "2" "3" "4" "2" "3" "NaN" Here's the problem: Your vector is character in mode, so of course it's "not a number". That last element got interpreted as the string "NaN". Using is.nan