带有重塑::melt in r的连续警告信息

Question

我经常收到警告消息，如:

as.is should be specified by the caller using true 

代码如下:

difficulty_data <- data_original[,c(-1)] %>% colMeans() %>% t() %>% as.data.frame() %>% t() 
difficulty_data <- reshape::melt(difficulty_data, id.vars=c("id"))  %>% dplyr::select(-X2)

描述:

我想计算colmeans的，并将它们分隔在两个不同的列中。我删除了& X2"因为最后我想用ggplot把它们画出来。(结果与值和值的id结合)

Answer 1

问题在reshape::melt

的代码行中

dn[char] <- lapply(dn[char], type.convert)

应该是type.convert和as.is = TRUE

在下一步中，它显示了警告

indices <- do.call(expand.grid, dn)

警告消息:在type.convert.default(X[[i]]，…)中:"。Is '应该由调用者指定;使用真正的

。如果我们看源代码

getAnywhere("melt.matrix")[1]
function (data, varnames = names(dimnames(data)), ...) 
{
values <- as.vector(data)
dn <- dimnames(data)
if (is.null(dn)) 
dn <- vector("list", length(dim(data)))
dn_missing <- sapply(dn, is.null)
dn[dn_missing] <- lapply(dim(data), function(x) 1:x)[dn_missing]
char <- sapply(dn, is.character)
dn[char] <- lapply(dn[char], type.convert)
indices <- do.call(expand.grid, dn)
names(indices) <- varnames
data.frame(indices, value = values)
}

并尝试在mtcars

中重现该问题

data(mtcars)
difficulty_data <- mtcars %>%
colMeans() %>%
t() %>%
as.data.frame %>% 
t() 

---

数据是一个矩阵，有一列和rownames属性

> reshape::melt(difficulty_data)
X1 X2      value
1   mpg  1  20.090625
2   cyl  1   6.187500
3  disp  1 230.721875
4    hp  1 146.687500
5  drat  1   3.596563
6    wt  1   3.217250
7  qsec  1  17.848750
8    vs  1   0.437500
9    am  1   0.406250
10 gear  1   3.687500
11 carb  1   2.812500
Warning message:
In type.convert.default(X[[i]], ...) :
'as.is' should be specified by the caller; using TRUE

如上所述，修复方法是添加type.convertas.is = TRUE

data <- difficulty_data
varnames <- names(dimnames(data))
values <- as.vector(data)
dn <- dimnames(data)
if (is.null(dn)) 
dn <- vector("list", length(dim(data)))
dn_missing <- sapply(dn, is.null)
dn[dn_missing] <- lapply(dim(data), function(x) 1:x)[dn_missing]

char <- sapply(dn, is.character)
dn[char] <- lapply(dn[char], type.convert, as.is = TRUE) #change here
indices <- do.call(expand.grid, dn)
names(indices) <- varnames
data.frame(indices, value = values)
Var1 Var2      value
1   mpg    1  20.090625
2   cyl    1   6.187500
3  disp    1 230.721875
4    hp    1 146.687500
5  drat    1   3.596563
6    wt    1   3.217250
7  qsec    1  17.848750
8    vs    1   0.437500
9    am    1   0.406250
10 gear    1   3.687500
11 carb    1   2.812500

修复

没有警告

---

因此，我们可以创建该函数的副本并更改特定行

meltnew <- reshape::melt.matrix
body(meltnew)[8][[1]] <- dn[char] <- lapply(dn[char], type.convert, as.is = TRUE)

现在，测试它

> meltnew(difficulty_data)
X1 X2      value
1   mpg  1  20.090625
2   cyl  1   6.187500
3  disp  1 230.721875
4    hp  1 146.687500
5  drat  1   3.596563
6    wt  1   3.217250
7  qsec  1  17.848750
8    vs  1   0.437500
9    am  1   0.406250
10 gear  1   3.687500
11 carb  1   2.812500

没有警告

Answer 2

melt(as.data.frame(difficulty_data))

如果有人遇到同样的问题，也值得一试。

Answer 3

在上面的简单例子中，这似乎也起作用了:

#make data
data(mtcars)
difficulty_data <- mtcars %>%
colMeans() %>%
t() %>%
as.data.frame %>% 
t() 
#melt data
as.data.frame.table(difficulty_data)