I want to use the code below this message to make stacked bar plot, my
question is :
I want the stacked bar and its legend following the order as tr from
left to right like the following:
"100.0.250ng_CellLine_0" "75.25.250ng_CellLine_0"
"50.50.250ng_CellLine_0" "10.90.250ng_CellLine_0"
"1.99.25
I want the stacked bar and its legend following the order as tr from
left to right like the following:
"100.0.250ng_CellLine_0" "75.25.250ng_CellLine_0"
"50.50.250ng_CellLine_0" "10.90.250ng_CellLine_0"
"1.99.250ng_CellLine_0" "0.100.250ng_CellLine_0"
"100.0.500ng_CellLine_0" "75.25.500ng_CellLine
Thank you, it is very helpful.
I tried the following way to generate stacked bar plot for trt 'M6' and
'M12'
However, the label position of legend in 'M12' is not what I want,
actually in the legend I also want to keep "Others" in the bottom(like the
gene order in stacked bar)
In addition, how t
This is a **plain text list **. In future please post in plain text so that
your post does not get mangled.
Anyway,...
I don't know about "efficient, optimized", but here's one simple way to do
it using ?strsplit to unsplit and then ?paste to recombine:
df <- data.frame(ID=1:3, FOO=c('A_B','A_B_
The usual reason for the 'subscript out of bounds' error is that an array's
subscripts exceed the dimensions of the array. In this case
gee.fit$working.correlation is a 1 by 1 matrix, so subscripting with [1,2]
will cause the error.
Here is a self-contained example that you can send the package's
How about something like this?
df <- data.frame(ID=1:3, DTVAL=c("2009-03-21","2010-05-11","2020-05-05"))
df <- df %>% mutate(YEAR = as.numeric(format(as.Date(DTVAL,'%Y-%m-%d'),
'%Y')))
-Original Message-
From: R-help [mailto:r-help-boun...@r-project.org] On Behalf Of Charles Thuo
Sent:
Assuming, I have a data frame like this ..
df <- data.frame(ID=1:3, FOO=c('A_B','A_B_C','A_B_C_D_E'))
I want to do a 'cumulative split' of the values in column FOO based on the
delimiter '_'. The end result should be like this ..
ID FOO FOO_SPLIT1 FOO_SPLIT2 FOO_SPLIT
Hello,
Something like this?
g <- unique(as.character(df$gene))
i <- which(g == "Others")
g <- c(g[i], g[-i])
df$trt <- factor(df$trt,levels=unique(as.character(df$trt)))
df$gene <- factor(df$gene,levels = g)
ggplot(df, aes(x=trt,y=freq, fill = gene, group = gene)) +
geom_bar(stat = "identity
I did a regression analysis with categorical data with a glm model
approach, which worked fine. I have longitude and latitude coordinates for
each observation and I want to add their geographic spillover effect to the
model.
My sample data is structured:
Index DV IVI IVII IVIII IVIV Long Lat
1
Hello,
I have a dataframe in R that looks like the following
cluster id period u_3 timeID startTrt Ijterror y
1: 1 1 0 -1.26 11 0 1.2015 17.809
2: 1 2 0 -1.26 11 0 -1.6577 14.950
3: 1 3 0 -1.26 11 0
Press send too soon? This is not actually a question.
Do read the Posting Guide... for one thing you need to post in plain text
because the automatic text conversion tends to mess up what you send if it is
HTML.
On June 5, 2020 12:02:44 AM PDT, TJUN KIAT TEO wrote:
>Suppose I have a dataframe
Suppose I have a dataframe in this from
a b c
g 2 3
h 4 5
i 6 7
I want to apply a function to individual elements of column C where the
function value depends on the value of column A
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