How to make histograms of this table of column columns in R ggplot?

Question

I am trying to build descriptive variables in the first line with the following procedure. I also tried unsuccessfully with quoting column / row names

• rotate rows and columns in CSV data for correlation data structure (high table) required in the stream Very simple histogram with R? fromggplot

• to construct a histogram of events as a Absolutevariable the XOR ( Average, Min, Max)

  • If only the absolute value, just draw the absolute value in the histogram.
  • If (medium, minimum, and maximum), simply draw them in a histogram with a mustache (= whisker chart ), where the limits of the mustache are made with min and max.

Data

• data.csv

  "Vars"    , "Sleep", "Awake", "REM", "Deep"
  "Absolute",        ,       , 5     , 7
  "Average" , 7      , 12    ,       ,
  "Min"     , 4      , 5     ,       , 
  "Max"     , 10     , 15    ,       ,
  

•             V1       V2       V3       V4
  Vars  Absolute Average  Min      Max     
  Sleep     <NA>        7        4       10
  Awake     <NA>       12        5       15
  REM          5     <NA>     <NA>     <NA>
  Deep         7     <NA>     <NA>     <NA>
  

• R

   data <- structure(list(V1 = structure(c(3L, NA, NA, 1L, 2L), .Names = c("Vars", 
   "Sleep", "Awake", "REM", "Deep"), .Label = c(" 5", " 7", "Absolute"
   ), class = "factor"), V2 = structure(c(3L, 2L, 1L, NA, NA), .Names = c("Vars", 
   "Sleep", "Awake", "REM", "Deep"), .Label = c("12", " 7", "Average "
   ), class = "factor"), V3 = structure(c(3L, 1L, 2L, NA, NA), .Names = c("Vars", 
  "Sleep", "Awake", "REM", "Deep"), .Label = c(" 4", " 5", "Min     "
   ), class = "factor"), V4 = structure(c(3L, 1L, 2L, NA, NA), .Names = c("Vars", 
  "Sleep", "Awake", "REM", "Deep"), .Label = c("10", "15", "Max     "
   ), class = "factor")), .Names = c("V1", "V2", "V3", "V4"), row.names = c("Vars", 
  "Sleep", "Awake", "REM", "Deep"), class = "data.frame")
  

R

dat.m <- read.csv("data.csv")

# rotate rows and columns
dat.m <- as.data.frame(t(dat.m)) # https://stackoverflow.com/a/7342329/54964 Comment 42-

library("reshape2")
dat.m <- melt(dat.m, id.vars="Vars")

## Just plot values existing there correspondingly    
library("ggplot2")
# /questions/1017323/a-very-simple-histogram-with-r/3461332#3461332
# TODO following
#ggplot(dat.m, aes(x = "Vars", y = value,fill=variable)) 

Error: id variables not found in data: Vars
Execution halted

R: 3.3.3, 3.4.0 (backports)
: Debian 8.7
R reshape2, ggplot2,... sessionInfo()

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=C                 
 [9] LC_ADDRESS=C               LC_TELEPHONE=C            
[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C   

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
[1] ggplot2_2.1.0  reshape2_1.4.2

loaded via a namespace (and not attached):
 [1] colorspace_1.3-2 scales_0.4.1     magrittr_1.5     plyr_1.8.4      
 [5] tools_3.3.3      gtable_0.2.0     Rcpp_0.12.10     stringi_1.1.5   
 [9] grid_3.3.3       stringr_1.2.0    munsell_0.4.3    

HaberdashPI

1, Sleep Awake. NA, .

. 1 HaberdashPI

dat.m

'data.frame':   4 obs. of  5 variables:
 $ Absolute: Factor w/ 2 levels " 5"," 7": NA NA 1 2
  ..- attr(*, "names")= chr  "Sleep" "Awake" "REM" "Deep"
 $ Average : Factor w/ 2 levels "12"," 7": 2 1 NA NA
  ..- attr(*, "names")= chr  "Sleep" "Awake" "REM" "Deep"
 $ Min     : Factor w/ 2 levels " 4"," 5": 1 2 NA NA
  ..- attr(*, "names")= chr  "Sleep" "Awake" "REM" "Deep"
 $ Max     : Factor w/ 2 levels "10","15": 1 2 NA NA
  ..- attr(*, "names")= chr  "Sleep" "Awake" "REM" "Deep"
 $ Vars    : chr  "Sleep" "Awake" "REM" "Deep"
      Absolute Average  Min      Max       Vars
Sleep     <NA>        7        4       10 Sleep
Awake     <NA>       12        5       15 Awake
REM          5     <NA>     <NA>     <NA>   REM
Deep         7     <NA>     <NA>     <NA>  Deep

dat.m

'data.frame':   16 obs. of  3 variables:
 $ Vars    : chr  "Sleep" "Awake" "REM" "Deep" ...
 $ variable: Factor w/ 4 levels "Absolute","Average ",..: 1 1 1 1 2 2 2 2 3 3 ...
 $ value   : chr  NA NA " 5" " 7" ...

    Vars variable value
1  Sleep Absolute  <NA>
2  Awake Absolute  <NA>
3    REM Absolute     5
4   Deep Absolute     7
5  Sleep Average      7
6  Awake Average     12
7    REM Average   <NA>
8   Deep Average   <NA>
9  Sleep Min          4
10 Awake Min          5
11   REM Min       <NA>
12  Deep Min       <NA>
13 Sleep Max         10
14 Awake Max         15
15   REM Max       <NA>
16  Deep Max       <NA>

akash87

ds <- dat.m
str(ds)
ds
ds$variable
ds$variable %in% c("Min","Max")

, False

 $ Vars    : chr  "Sleep" "Awake" "REM" "Deep" ...
 $ variable: Factor w/ 4 levels "Absolute","Average ",..: 1 1 1 1 2 2 2 2 3 3 ...
 $ value   : chr  NA NA " 5" " 7" ...
    Vars variable value
1  Sleep Absolute  <NA>
2  Awake Absolute  <NA>
3    REM Absolute     5
4   Deep Absolute     7
5  Sleep Average      7
6  Awake Average     12
7    REM Average   <NA>
8   Deep Average   <NA>
9  Sleep Min          4
10 Awake Min          5
11   REM Min       <NA>
12  Deep Min       <NA>
13 Sleep Max         10
14 Awake Max         15
15   REM Max       <NA>
16  Deep Max       <NA>
[1] "hello 3"
 [1] Absolute Absolute Absolute Absolute Average  Average  Average  Average 
 [9] Min      Min      Min      Min      Max      Max      Max      Max     
Levels: Absolute Average  Min      Max     
 [1] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
[13] FALSE FALSE FALSE FALSE

, ds[ds$variable %in% c("Min","Max"), ] False , .

Uwe

data.table::dcast data.table::melt. sessionInfo() molten <- .... library(ggplot2) , molten <- ....

$ Rscript test111.r 
    Vars "Average" "Max" "Min" Absolute
1: Sleep         7    10     4       NA
2: Awake        12    15     5       NA
3:   REM        NA    NA    NA        5
4:  Deep        NA    NA    NA        7
R version 3.4.0 (2017-04-21)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Debian GNU/Linux 8 (jessie)

Matrix products: default
BLAS: /usr/lib/openblas-base/libblas.so.3
LAPACK: /usr/lib/libopenblasp-r0.2.12.so

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=C                 
 [9] LC_ADDRESS=C               LC_TELEPHONE=C            
[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C       

attached base packages:
[1] stats     graphics  grDevices utils     datasets  base     

other attached packages:
[1] data.table_1.10.4

loaded via a namespace (and not attached):
[1] compiler_3.4.0 methods_3.4.0 
Error in melt.data.table(transposed, measure.vars = c("Absolute", "Average")) : 
  One or more values in 'measure.vars' is invalid.
Calls: <Anonymous> -> melt.data.table
Execution halted

Uwe 2

molten <- structure(list(Vars = structure(c(1L, 2L, 1L, 2L, 1L, 2L), class = "factor", .Label = c("V1", "V2")), variable = structure(c(1L, 1L, 2L, 2L, 3L, 3L), class = "factor", .Label = c("ave", "ave_max", "lepo")), value = c(7L, 8L, 10L, 10L, 4L, 4L)), .Names = c("Vars", "variable", "value"), row.names = c(NA, -6L), class = c("data.table", "data.frame"))

print(molten)

library(ggplot2)
ggplot(molten, aes(x = Vars, y = value, fill = variable, ymin = lepo, ymax = ave_max)) + 
  geom_col() + geom_errorbar(width = 0.2)

  Vars variable value
1   V1      ave     7
2   V2      ave     8
3   V1  ave_max    10
4   V2  ave_max    10
5   V1     lepo     4
6   V2     lepo     4
Error in FUN(X[[i]], ...) : object 'lepo' not found
Calls: <Anonymous> ... by_layer -> f -> <Anonymous> -> f -> lapply -> FUN -> FUN
Execution halted

Answer 1

, "Vars" Vars gsplot aes. , . , ,... , . .

, :

#Data
data = cbind.data.frame(c("Sleep", "Awake", "REM", "Deep"),
                        c(NA, NA, 5, 7),
                        c(7, 12, NA, NA),
                        c(4, 5, NA, NA),
                        c(10, 15, NA, NA))
colnames(data) = c("Vars", "Absolute", "Average", "Min", "Max")

#reshape
dat.m <- melt(data, id.vars="Vars")
#Stacked plot
ggplot(dat.m, aes(x = Vars, y = value)) + geom_bar(aes(fill=variable), stat = "identity")

:

#Or multiple bars
ggplot(dat.m, aes(x = Vars, y = value)) + 
  geom_bar(aes(fill=variable), stat = "identity", position="dodge") 

#Or separated by Vars
ggplot(dat.m, aes(x = Vars, y = value)) + geom_bar(aes(fill=variable), stat = "identity", position="dodge") + facet_wrap( ~ Vars, scales="free")

. @Uwe .

#data
data <- structure(list(Vars = structure(1:2, class = "factor", .Label = c("V1", "V2")), ave = c(7L, 8L), ave_max = c(10L, 10L), lepo = c(4L, 4L)), .Names = c("Vars", "ave", "ave_max", "lepo"), row.names = c(NA, -2L), class = c("data.table", "data.frame"), sorted = "Vars")
#Melt
library(data.table)
mo = data.table::melt(data, measure.vars = c("ave"))
ggplot(mo, aes(x = Vars, y = value, fill = variable, ymin = lepo, ymax = ave_max)) + geom_col() + geom_errorbar(width = 0.2)

:

Answer 2

, dat.m <- as.data.frame(t(dat.m)). .

( histogram?), , , , , , , :

library(ggplot2)
library(reshape2)

dat.m <- read.csv("data.csv")

m <- t(dat.m)
dat.m <- data.frame(m[2:nrow(m),])
names(dat.m) <- m[1,]
dat.m$Vars <- rownames(m)[2:nrow(m)]

dat.m <- melt(dat.m, id.vars="Vars")
ggplot(dat.m, aes(x = Vars, y = value,fill=variable)) + geom_bar(stat='identity')

:

(names(data.m) <- etc...) Vars, dat.m, , melt ( , Vars). , .

, , . , - (Excel?), , , , , R , min .. R, , R. , , .

ggplot , : dplyr tidyr.

Answer 3

.

> data
  Vars variable value
 Sleep Absolute  <NA>
 Awake Absolute  <NA>
   REM Absolute     5
  Deep Absolute     7
 Sleep  Average     7
 Awake  Average    12
   REM  Average  <NA>
  Deep  Average  <NA>
 Sleep      Min     4
 Awake      Min     5
   REM      Min  <NA>
  Deep      Min  <NA>
 Sleep      Max    10
 Awake      Max    15
   REM      Max  <NA>
  Deep      Max  <NA>

minmax <- ds[ds$variable %in% c("Min","Max"), ]
absol  <- ds[ds$variable %in% c("Average", "Absolute"), ]
minm   <- dcast(minmax, Vars ~ variable)
absol <- merge(absol, minm, by = "Vars", all.x = T)
>absol

      Vars variable value Max Min
     Awake  Average    12  15   5
      Deep Absolute     7  NA  NA
       REM Absolute     5  NA  NA
     Sleep  Average     7  10   4

ggplot2,

ggplot(absol, aes(x = Vars, y = value, fill = variable)) +
       geom_bar(stat = "identity") +
       geom_errorbar(aes(ymin = Min, ymax = Max), width = .25)

Answer 4

data.table:

library(data.table)

# read data and transpose
transposed <- data.table::dcast(data.table::melt(fread("data2.csv"), id.vars = "Vars"), 
                                variable ~ ...)
setnames(transposed, "variable", "Vars")
# reshape to long for plotting
molten <- data.table::melt(transposed, measure.vars = c("Absolute", "Average"))

. , , , melt() dcast(). , data.table . , OP , reshape2 data.table. data.table reshape2::dcast() reshape2::melt(). - , .

library(ggplot2)
ggplot(molten, aes(Vars, value, fill = variable, ymin = Min, ymax = Max)) + 
  geom_col() + geom_errorbar(width = 0.2)

" csv. fread(), . , data2.csv :

Vars    ,   Sleep,  Awake,    REM, Deep 
Absolute,        ,       , 5     , 7
Average , 7      , 12    ,       , 
Min     , 4      , 5     ,       , 
Max     , 10     , 15    ,       , 

Answer 5

The completion of the akash87 code because the data conversion is not explicit in its response from the original dta set p>

library("ggplot2")

dat.m <- read.csv("data.csv", strip.white=TRUE)

m <- t(dat.m)
dat.m <- data.frame(m[2:nrow(m),])
names(dat.m) <- m[1,]
dat.m$Vars <- rownames(m)[2:nrow(m)]

library("reshape2")
dat.m <- melt(dat.m, id.vars="Vars")

ds <- dat.m
# http://stackoverflow.com/a/44090815/54964
minmax <- ds[ds$variable %in% c("Min","Max"), ]
absol  <- ds[ds$variable %in% c("Average", "Absolute"), ]
minm   <- dcast(minmax, Vars ~ variable)
absol <- merge(absol, minm, by = "Vars", all.x = T)

absol

ggplot(absol, aes(x = Vars, y = value, fill = variable)) +
       geom_bar(stat = "identity") +
       geom_errorbar(aes(ymin = Min, ymax = Max), width = .25)

Conclusion: the same as in akash87 aswer.