function somersD returns NaN - r

I have the following dataframe:
> dput(master_credit)
structure(c(10, 10, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 12,
11, 11, 11, 11, 11, 12, 11, 11, 12, 11, 11, 11, 11, 11, 12, 12,
12, 11, 12, 12, 12, 11, 11, 11, 12, 11, 12, 12, 12, 12, 13, 12,
12, 12, 12, 12, 12, 11, 12, 12, 11, 12, 12, 14, 13, 12, 13, 13,
14, 13, 13, 12, 25, 26, 3, 21, 5, 9, 43, 15, 2, 6, 4, 27, 44,
1, 10, 31, 16, 12, 37, 7, 23, 54, 18, 19, 20, 14, 35, 52, 36,
32, 29, 50, 51, 30, 42, 24, 17, 63, 8, 62, 38, 34, 33, 49, 59,
58, 57, 60, 28, 61, 40, 41, 22, 11, 47, 13, 48, 45, 46, 65, 64,
53, 39, 56, 55), .Dim = c(65L, 2L), .Dimnames = list(NULL, c("master",
"credit")))
on which I am running the code:
library(InformationValue)
> somersD(master_credit[,"master"], master_credit[,"credit"])
[1] NaN
why does it return NaN?

The documentation of somersD says somersD(actuals, predictedScores), where actuals are binary flags which are either 1 or 0.
actuals: The actual binary flags for the response variable. It can take a numeric vector containing values of either 1 or 0, where 1 represents the 'Good' or 'Events' while 0 represents 'Bad' or 'Non-Events'.
Internally while calculating Somers D statistics, somersD function tries to find the number of rows containing, 1 and 0 in actuals column. This count is used in division. And since in your dataframe there is no such row, so you are basically dividing by zero, hence it returns NaN.

Related

error in densityplot mice- missing data example

I have the following data:
dput(example)
structure(list(q1 = c(5, 22, 16, 24, 9, 20, 21, 16, 28, 28, 24,
25, 34, 22, 29, NA, 24, 13, 10, 17, 24, 21, 22, 35, 20, 25, 25,
23, 22, 20, 27, 22, 20, 23, 5, 21, 19, 17, 27, 20, 35, 35, 10,
16, 22, 34, 34, 23, 25, 23, 25, 30, 18, 21, 15, 23, 5, 35, 5,
30), q2 = c(5, 5, 24, 15, 5, 5, 26, 23, 24, 9, 24, 5, 15, 26,
30, 14, 14, 19, 11, 25, 20, 5, 14, 13, 11, 10, 13, 16, 16, 21,
10, 12, 20, 9, 15, 5, 13, 5, 30, 18, 12, 27, 10, 9, 20, 5, 9,
10, 11, 26, 22, 8, 6, 5, 15, 6, 5, 35, 10, 18), q3 = c(11, 22,
NA, 22, 6, 18, 30, 6, 26, NA, 17, 22, 33, 19, 22, 25, 23, 13,
13, 15, 16, 16, 23, 24, 6, 25, 27, 12, 25, 17, 28, 15, 20, 31,
5, 17, 17, 20, 24, 7, 35, 35, 10, 10, 20, 10, 31, 21, 16, 32,
25, 30, 10, 24, 15, 24, 5, 35, 9, 26), q4 = c(14, 15, 23, 21,
NA, 25, 30, 23, 28, 20, 25, 5, 35, 30, 19, 23, 30, 5, 23, 18,
30, 15, 30, 22, 8, 29, 35, 23, 23, 24, 25, 25, 20, 25, 5, 15,
34, 8, 32, 35, 35, 35, 10, 6, 21, 10, 24, 27, 10, 30, 35, 15,
6, 21, 15, 15, 5, 35, 19, 26), q5 = c(5, 18, 21, 19, 5, 6, 5,
29, 20, 23, 22, 5, 16, 22, 12, 13, 18, 5, 17, 15, 18, 16, 20,
8, 12, 19, 12, 23, 9, 16, 5, 29, 20, 5, 5, 5, 5, 5, 30, 22, 32,
35, 10, 13, 20, 13, 12, 16, 5, 24, 22, 17, 5, 20, 14, 5, 5, 35,
15, 16), q6 = c(15, 9, 25, 26, 6, 17, 28, 32, 26, 28, 24, 25,
11, 24, 31, 18, 19, 6, 20, 26, 29, 17, 21, 24, 7, 29, 17, 17,
14, 25, 24, 35, 24, 6, 16, 6, 9, 6, 38, 19, 30, 42, 12, 20, 27,
26, 25, 13, 9, 36, 27, 27, 7, 24, 22, 6, 16, 42, 14, 11)), class = "data.frame", row.names = c(NA,
-60L))
I then use mice:
*edit: forgot the complete line
library(mice)
imp <- mice(example,m=5,maxit=50,meth='pmm',seed=500)
example_i <- complete(imp,1)
But when trying to get a densityplot I get the following error:
densityplot(imp)
Error in str2lang(x) : <text>:2:0: unexpected end of input
1: ~
^
My questions are:
Is there something fundamentally wrong about my approach to impute missing data? (this is just a small example)
Am I using properly the MICE arguments?
What am I doing wrong with the density plot, as I have gotten it for all of the other scales I am working with?
Answer
You need to supply a formula to densityplot, otherwise it will plot all variables with > 2 missing values. Since you don't have any variables with 2 > missing values, and since densityplot doesn't expect that, it produces this cryptic error.
Example that works
example$q4[1:10] <- NA
imp <- mice(example, m = 5, maxit = 50, meth = "pmm", seed = 500)
densityplot(imp)
# equivalent: densityplot(imp, ~ q4)
Rationale
imp is of class mids, so you are calling densityplot.mids. Normally, densityplot.mids requires you to provide a formula (data argument), so that it knows which variables to plot (see ?densityplot.mids). If you want to plot q4, then the code is densityplot(imp, ~ q4).
Inside densityplot.mids, we see:
if (missing(data)) {
vnames <- vnames[!allfactors & x$nmis > 2 & x$nmis <
nrow(x$data) - 1]
formula <- as.formula(paste("~", paste(vnames,
collapse = "+", sep = ""), sep = ""))
}
If we use traceback() right after getting your error, then you will see that the last line above is the line that throws the error.
In the first line, you can see the condition xnmis > 2, which means that it will grab all the columns with more than 2 missing values. When no columns satisfy the conditions, then vnames will evaluate to character(0), and so the subsequent line yields as output ~, i.e. the code that you see in your error.
So, why does it give an error when there are too few missings? That's because densityplot plots a distribution, and plotting a distribution of 1 or 2 points is just not doable.
Suggestion
The package maintainers could improve the error by simply checking whether vnames has any content, and if not, they can throw an error that is informative. You may want to add this as an issue on Github if you think it is useful.

Inline data.frame inclusion in R script

While there are functions for saving data as a separate CSV file (write.table) or as an R-data file (save, saveRDS), I have not found a way to store or print a data frame as R code that recreates this data frame.
Background of my question is that I want to include data with a script (instead of storing it in a separate file), and am thus looking for a way to generate the specific code provided the data frame already exists. I could hack on with sed or other external tools, but I wonder whether someone knows of a built-in method in R.
Try with "dput" like so:
dput(cars)
# Returns:
structure(list(speed = c(4, 4, 7, 7, 8, 9, 10, 10, 10, 11, 11,
12, 12, 12, 12, 13, 13, 13, 13, 14, 14, 14, 14, 15, 15, 15, 16,
16, 17, 17, 17, 18, 18, 18, 18, 19, 19, 19, 20, 20, 20, 20, 20,
22, 23, 24, 24, 24, 24, 25), dist = c(2, 10, 4, 22, 16, 10, 18,
26, 34, 17, 28, 14, 20, 24, 28, 26, 34, 34, 46, 26, 36, 60, 80,
20, 26, 54, 32, 40, 32, 40, 50, 42, 56, 76, 84, 36, 46, 68, 32,
48, 52, 56, 64, 66, 54, 70, 92, 93, 120, 85)), class = "data.frame",
row.names = c(NA, -50L))

How to get the true node value in igraph

So I have read in a network data in iGraph(R) and would like to store the nodes into a list. Here's what I have done:
G = read_graph("somegraph.graphml",format="graphml")
x = list(V(G))
> x
+ 15/15 vertices, from ecb3920:
[1] 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
My question is, how do I get the true value, i.e. the actually node id in my data, from V(G). Thanks.
> dput(G)
structure(list(15, FALSE, c(13, 7, 9, 14, 10, 5, 4, 11, 6, 7,
14, 4, 13, 9, 10, 5, 5, 13, 9, 6, 7, 14, 12, 10, 14, 10, 11,
13, 9, 10, 12, 14, 8, 7, 11, 12, 8, 13, 14, 9, 11, 13, 13, 12,
14, 10, 13, 12, 14, 12, 13, 13, 14, 14), c(0, 0, 2, 2, 2, 2,
2, 3, 3, 3, 3, 3, 3, 3, 3, 3, 4, 4, 4, 4, 4, 4, 4, 4, 5, 5, 6,
6, 6, 6, 6, 6, 6, 6, 7, 7, 7, 7, 7, 7, 8, 8, 9, 9, 9, 9, 10,
10, 10, 11, 11, 12, 12, 13), c(6, 11, 5, 15, 16, 8, 19, 1, 9,
20, 33, 32, 36, 2, 13, 18, 28, 39, 4, 14, 23, 25, 29, 45, 7,
26, 34, 40, 22, 30, 35, 43, 47, 49, 0, 12, 17, 27, 37, 41, 42,
46, 50, 51, 3, 10, 21, 24, 31, 38, 44, 48, 52, 53), c(1, 0, 6,
5, 2, 4, 3, 11, 15, 8, 9, 13, 14, 7, 12, 10, 16, 19, 20, 18,
23, 22, 17, 21, 25, 24, 33, 32, 28, 29, 26, 30, 27, 31, 36, 39,
34, 35, 37, 38, 40, 41, 45, 43, 42, 44, 47, 46, 48, 49, 50, 51,
52, 53), c(0, 0, 0, 0, 0, 2, 5, 7, 11, 13, 18, 24, 28, 34, 44,
54), c(0, 2, 2, 7, 16, 24, 26, 34, 40, 42, 46, 49, 51, 53, 54,
54), list(c(1, 0, 1), structure(list(), .Names = character(0)),
structure(list(id = c("1351920706", "500102244", "1454425532",
"1625050630", "510838353", "1262640078", "681721364", "1351920717",
"1260750116", "1524975171", "1070293410", "727198538", "715215233",
"1351920666", "500920034")), .Names = "id"), list()), <environment>), class = "igraph")
Just for closure (and to summarise from our chat): Based on the sample data you give, you can extract additional data for every vertex by indexing the corresponding element.
So
V(g)$id
returns
#[1] "1351920706" "500102244" "1454425532" "1625050630" "510838353"
#[6] "1262640078" "681721364" "1351920717" "1260750116" "1524975171"
#[11] "1070293410" "727198538" "715215233" "1351920666" "500920034"

r subset `x` and `labels` must be same type

I am trying to subset my dataset as follows
df[df$Age > 19,]
I am seeing an error , Error: x and labels must be same type
I am not sure I understand this, any suggestions are much appreciated.
=================
dput(df$Age)
c(20, 11, 10, 15, 6, 23, 45, 30, 18, 11, 15, 20, 7, 18, 19, 30,
40, 16, 14, 33, 12, 22, 12, 5, NA, 18, 30, 26, 25, 27, 12, 27,
13, 15, 32, 19, NA, 18, 13, 30, 10, 16, 47, 24, 64, 21, 9, 30,
12, 33, 16, 20, 14, 10, 19, 18, 20, 18, 10, 15, 55, 18, 50, 14,
35, 18, 21, 17, 14, 9, 25, 17, 10, 16, 12, 30, 38, 10, 27, 20,
27, 16, 30, 11, 5, 20, 30, 12, 24, 11, 7, 26, 48, 25, 20, 18,
27, 18, 28, 15, 17, 46, 30, 20, 20, 14, 35, 31, 10, 26, 13, NA,
15, 3, 30, 33, 15, 43, 19, 40, 8, 16, 8, 3, 37, 40, 58, 18, 12,
19, 14, 24, 34, 30, 23, 28, 47, 29, 21, 35, 23, 47, 11, 30, 16,
25, 30, 30, 8, 18, 20, 12, 8, 18, 30, 6, 54, 60, 18, 27, 42,
6, 42, 13, 21, 15, 17, 10, 33, 15, 16, 36, 16, 52, 4, 30, 28,
30, 14, 13, 14, NA, 15, 20, 20, 24, 27, 23, 10, 13, 22, 30, 45,
10, 23, 14, 27, 19, 12, 25, 10, 10, 14, 16, 16, 19, 18, 12, 65,
18, 35, 20, 31, NA, 21, 40, 8, 13, 25, 8, 13, 15, 19, 25, 10,
9, 24, 8, 25, 30, 38, 35, 20, 12, 15, 25, 27, 39, 8, 10, NA,
12, 50, 16, 14, 22, 12, 20, 44, 13, 8, 43, 48, 13, 21, 20, 42,
11, 20, 35, 53, 22, 17, 5, NA, 14, 10, 21, 33, 21, 69, 24, 15,
12, 8, 28, 11, 32, 25, 26, 21, 36, 12, 24, 20, 23, 14, 30, 50,
26, NA, 30, 22, 44, 22, 14, 30, 28, 10, 16, 32, 35, 40, 16, 40,
33, 23, 25, 10, 17, 10, 14, 22, 14, 25, 20, 39, 24, 52, 16, 34,
26, 23, 11, 12, 70, 59, 12, 38, 22, 13, 40, 57, 30, 7, 21, 20,
30, 12, 13, 5, 19, 35, 56, 17, 40, 48, 19, 8, 30, 21, 5, 40,
16, 22, 20, 17, 16, 30, 18, 13, 17, NA, 40, 9, 24, 26, 20, 22,
17, 44, 45, 18, 26, 50, 10, 21, 15, NA, 20, 12, 16, 54, 15, 16,
33, 22, 26, 60, 35, 11, 30, 16, 48, 16, 16, 16, 10, 14, 15, 23,
17, 18, NA, 49, 12, 7, 18, 24, 17, 14, 30, 13, 6, 51, 36, 16,
10, 43, 34, 15, 12, 15, 15, 17, 40, 58, 15, 33, 16, 48, 25, 15,
16, 5, NA, 40, 34, 10, 30, 30, 30, 15, 15, 12, 5, 10, 20, 18,
20, 16, 20, 26, 12, 14, 14, 20, 12, 30, 30, 29, 22, 19, 26, 11,
23, 40, 30, 16, 50, 20, 25, 29, 40, 44, 20, 40, 8, 16, 15, 38,
11, 27, 63, 16, NA, 47, 65, 21, 29, 30, 16, 21, 25, 16, 23, 5,
17, 22, 12, 14, 27, NA, 16, 9, 33, 11, 15, 34, 41, 30, 33, 15,
25, 40, 25, 12, 12, 17, 14)

How do you include data frame output inside warnings and errors?

How can I include array or data frame output in a message, warning or error?
By default, the output is collapsed by deparseing each column, which isn't useful. Here's an example, using the cars dataset.
message(cars)
## c(4, 4, 7, 7, 8, 9, 10, 10, 10, 11, 11, 12, 12, 12, 12, 13, 13, 13, 13, 14, 14, 14, 14, 15, 15, 15, 16, 16, 17, 17, 17, 18, 18, 18, 18, 19, 19, 19, 20, 20, 20, 20, 20, 22, 23, 24, 24, 24, 24, 25)c(2, 10, 4, 22, 16, 10, 18, 26, 34, 17, 28, 14, 20, 24, 28, 26, 34, 34, 46, 26, 36, 60, 80, 20, 26, 54, 32, 40, 32, 40, 50, 42, 56, 76, 84, 36, 46, 68, 32, 48, 52, 56, 64, 66, 54, 70, 92, 93, 120, 85)
Print the output, recapture it using capture.output(), and collapse into a single string separated by newlines.
print_and_capture <- function(x)
{
paste(capture.output(print(x)), collapse = "\n")
}
message(print_and_capture(cars))
## speed dist
## 1 4 2
## 2 4 10
## # etc.
stop("An error was found in the cars dataset:\n", print_and_capture(cars))
## Error: An error was found in the cars dataset:
## speed dist
## 1 4 2
## 2 4 10
## # etc.
print_and_capture() is now available in assertive.base.

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