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I have the results from a describe.by{psych} applied on a dataframe. The results is a list.
List of 1000
$ 1 :Classes ‘psych’, ‘describe’ and 'data.frame': 20 obs. of 13 variables:
..$ var : int [1:20] 1 2 3 4 5 6 7 8 9 10 ...
..$ n : num [1:20] 24 24 24 24 24 24 24 24 24 24 ...
..$ mean : num [1:20] 24 30.8 24 31.6 240 ...
..$ sd : num [1:20] 0.937 3.667 0.937 3.537 9.367 ...
..$ median : num [1:20] 23.9 31 23.9 31.9 238.6 ...
..$ trimmed : num [1:20] 24 30.9 24 31.7 239.7 ...
..$ mad : num [1:20] 1.11 4.12 1.11 3.29 11.09 ...
..$ min : num [1:20] 22.6 24 22.6 25.3 225.9 ...
..$ max : num [1:20] 25.6 36.9 25.6 36.9 256 ...
..$ range : num [1:20] 3 12.9 3 11.6 30 ...
..$ skew : num [1:20] 0.309 -0.258 0.309 -0.411 0.309 ...
..$ kurtosis: num [1:20] -1.163 -0.898 -1.163 -0.819 -1.163 ...
..$ se : num [1:20] 0.191 0.749 0.191 0.722 1.912 ...
$ 2 :Classes ‘psych’, ‘describe’ and 'data.frame': 20 obs. of 13 variables:
..$ var : int [1:20] 1 2 3 4 5 6 7 8 9 10 ...
..$ n : num [1:20] 7 7 7 7 7 7 7 7 7 7 ...
..$ mean : num [1:20] 16.3 39.3 16.3 40.7 162.9 ...
..$ sd : num [1:20] 0.609 8.045 0.609 8.394 6.086 ...
..$ median : num [1:20] 16.4 39.1 16.4 39.6 164.2 ...
..$ trimmed : num [1:20] 16.3 39.3 16.3 40.7 162.9 ...
I would like to plot a graph ( probably candlestick) or boxplots with this sample for each of the 13 metrics. Is there a package in which I can directly leverage the summary stats computed ?
You question is vague.
describeBy( describe.by is deprecated) , Report basic summary statistics by a grouping variable.
So I guess that a boxplot it is the nearest plot.
For example :
describeBy(sat.act,sat.act$gender)
group: 1
var n mean sd median trimmed mad min max range skew kurtosis se
gender 1 247 1.00 0.00 1 1.00 0.00 1 1 0 NaN NaN 0.00
education 2 247 3.00 1.54 3 3.12 1.48 0 5 5 -0.54 -0.60 0.10
age 3 247 25.86 9.74 22 24.23 5.93 14 58 44 1.43 1.43 0.62
ACT 4 247 28.79 5.06 30 29.23 4.45 3 36 33 -1.06 1.89 0.32
SATV 5 247 615.11 114.16 630 622.07 118.61 200 800 600 -0.63 0.13 7.26
SATQ 6 245 635.87 116.02 660 645.53 94.89 300 800 500 -0.72 -0.12 7.41
----------------------------------------------------------------------------------------------------------------------------------------------------------------------------
group: 2
var n mean sd median trimmed mad min max range skew kurtosis se
gender 1 453 2.00 0.00 2 2.00 0.00 2 2 0 NaN NaN 0.00
education 2 453 3.26 1.35 3 3.40 1.48 0 5 5 -0.74 0.27 0.06
age 3 453 25.45 9.37 22 23.70 5.93 13 65 52 1.77 3.03 0.44
ACT 4 453 28.42 4.69 29 28.63 4.45 15 36 21 -0.39 -0.42 0.22
SATV 5 453 610.66 112.31 620 617.91 103.78 200 800 600 -0.65 0.42 5.28
SATQ 6 442 596.00 113.07 600 602.21 133.43 200 800 600 -0.58 0.13 5.38
>
You can plot this like :
boxplot(sat.act,sat.act$gender, col ='pink')
Related
I am trying to run a shapiro-wilk normality test on R (Rcmdr to be more accurate) by going to "Statistics=>Summary=>Descriptive statistics" and then selecting one of my dependent variable and choosing "summary by group".
Rcmdr automatically triggers the following code :
normalityTest(Algometre.J0 ~ Modalite, test="shapiro.test",
data=Dataset)
And I am getting the following error message :
'groups' must be a factor.
I have already categorized my independant variable as a factor (I swear, I did !)
Any idea what's wrong ?
Thanx in advance
Here is what str(Dataset) shows :
'data.frame': 76 obs. of 11 variables:
$ Modalite : chr "C" "C" "C" "C" ...
$ Angle.J0 : num 20.1 20.5 21 22.5 19.1 ...
$ Angle.J1 : num 21.7 22.6 22.8 23.3 20.5 ...
$ Angle.J2 : num 22.3 23 23.9 24.2 21 ...
$ Epaisseur.J0: num 1.97 1.54 1.76 1.89 1.53 1.87 1.54 2 1.79 1.41 ...
$ Epaisseur.J1: num 2.07 1.49 1.87 1.91 1.54 1.9 1.51 2.03 1.71 1.48 ...
$ Epaisseur.J2: num 2.08 1.69 1.77 2 1.61 1.99 1.38 2.06 1.86 1.53 ...
$ Algometre.J0: num 45 40 105 165 66.3 ...
$ Algometre.J1: num 32.7 39.7 91.7 124 63.7 ...
$ Algometre.J2: num 51.3 58.7 101 138 60.3 ...
$ ObsNumber : int 1 2 3 4 5 6 7 8 9 10 ...
What does that mean ?
I am trying to do sensitivity analysis using R. My data set has few continuous explanatory variables and a categorical response variable (7 categories).
I tried to run the below mentioned code.
model=train(factor(mode)~Time+Cost+Age+Income,
method="nnet",
preProcess("center","scale"),
data=train,
verbose=F,
trControl=trainControl(method='cv', verboseIter = F),
tuneGrid=expand.grid(.size=c(1:20), .decay=c(0,0.001,0.01,0.1)))
After getting the output through this code, I tried to develop Lek's profile using the below mentioned code.
Lekprofile(model)
However, I got the error stating "Errors in xvars[, x_names]: subscript out of bound"
Please help me to resolve the error.
It doesn't work for a classification model , for example, if we use a regression model:
library(caret)
library(NeuralNetTools)
library(mlbench)
data(BostonHousing)
str(BostonHousing)
'data.frame': 506 obs. of 14 variables:
$ crim : num 0.00632 0.02731 0.02729 0.03237 0.06905 ...
$ zn : num 18 0 0 0 0 0 12.5 12.5 12.5 12.5 ...
$ indus : num 2.31 7.07 7.07 2.18 2.18 2.18 7.87 7.87 7.87 7.87 ...
$ chas : Factor w/ 2 levels "0","1": 1 1 1 1 1 1 1 1 1 1 ...
$ nox : num 0.538 0.469 0.469 0.458 0.458 0.458 0.524 0.524 0.524 0.524 ...
$ rm : num 6.58 6.42 7.18 7 7.15 ...
$ age : num 65.2 78.9 61.1 45.8 54.2 58.7 66.6 96.1 100 85.9 ...
$ dis : num 4.09 4.97 4.97 6.06 6.06 ...
$ rad : num 1 2 2 3 3 3 5 5 5 5 ...
$ tax : num 296 242 242 222 222 222 311 311 311 311 ...
$ ptratio: num 15.3 17.8 17.8 18.7 18.7 18.7 15.2 15.2 15.2 15.2 ...
$ b : num 397 397 393 395 397 ...
$ lstat : num 4.98 9.14 4.03 2.94 5.33 ...
$ medv : num 24 21.6 34.7 33.4 36.2 28.7 22.9 27.1 16.5 18.9 ...
We train the model, exclude the categorical chas:
model = train(medv ~ .,data=BostonHousing[,-4],method="nnet",
trControl=trainControl(method="cv",number=10),
tuneGrid=data.frame(size=c(5,10,20),decay=0.1))
lekprofile(model)
You can see the y-axis is meant to be continuous. We can try to discretize our response variable medv and you can see it crashes:
BostonHousing$medv = cut(BostonHousing$medv,4)
model = train(medv ~ .,data=BostonHousing[,-4],method="nnet",
trControl=trainControl(method="cv",number=10),
tuneGrid=data.frame(size=c(5,10,20),decay=0.1))
lekprofile(model)
Error in `[.data.frame`(preds, , ysel, drop = FALSE) :
undefined columns selected
I've been trying to use irmi from VIM package to replace NA's.
My data looks something like this:
> str(sub_mex)
'data.frame': 21 obs. of 83 variables:
$ pH : num 7.2 7.4 7.4 7.36 7.2 7.82 7.67 7.73 7.79 7.7 ...
$ Cond : num 1152 1078 1076 1076 1018 ...
$ CO3 : num NA NA NA NA NA ...
$ Mg : num 25.8 24.9 24.3 24.8 23.4 ...
$ NO3 : num 49.7 25.6 27.1 39.6 52.8 ...
$ Cd : num 0.0088 0.0104 0.0085 0.0092 0.0086 ...
$ As_H : num 0.006 0.0059 0.0056 0.0068 0.0073 ...
$ As_F : num 0.0056 0.0058 0.0057 0.0066 0.0065 0.004 0.004 0.004 0.0048 0.0078 ...
$ As_FC : num NA NA NA NA NA NA NA NA NA 0.0028 ...
$ Pb : num 0.0097 0.0096 0.0092 0.01 0.0093 0.0275 0.024 0.0255 0.031 0.024 ...
$ Fe : num 0.39 0.26 0.27 0.28 0.32 0.135 0.08 NA 0.13 NA ...
$ No_EPT : int 0 0 0 0 0 0 0 0 0 0 ...
I've subset my sub_mex dataset to analyze observations separately, so i have sub_t dataset. Which look something like this
> str(sub_t)
'data.frame': 5 obs. of 83 variables:
$ pH : num 7.82 7.67 7.73 7.79 7.7
$ CO3 : num 45 NA 37.2 41.9 40.3
$ Mg : num 41.3 51.4 47.7 51.8 53
$ NO3 : num 47.1 40.7 39.9 42.1 37.6
$ Cd : num 0.0173 0.0145 0.016 0.016 0.0154
$ As_H : num 0.00949 0.01009 0.00907 0.00972 0.00954
$ As_F : num 0.004 0.004 0.004 0.0048 0.0078
$ As_FC : num NA NA NA NA 0.0028
$ Pb : num 0.0275 0.024 0.0255 0.031 0.024
$ Fe : num 0.135 0.08 NA 0.13 NA
$ No_EPT : int 0 0 0 0 0
I impute NA's of the sub_mex dataset using:
imp_mexi <- irmi(sub_mex) which works fine
However when I try to impute the subset sub_t I got the following error message:
> imp_t <- irmi(sub_t)
Error in indexNA2s[, variable[j]] : subscript out of bounds
Does anyone have an idea of how to solve this? I want to impute my data sub_t and I don't want to use a subset of the ìmp_mexi imputed dataset.
Any help will be deeply appreciated.
I had a similar issue and discovered that one of the columns in my dataframe was entirely missing- hence the out of bounds error.
I have an output generated by the cuts functions which is the one below...lets call this ouput 'data'.
cuts: [20,25)
Time Kilometres
21 20 7.3
22 21 8.4
23 22 9.5
24 23 10.6
25 24 11.7
------------------------------------------------------------
cuts: [25,30)
Time Kilometres
26 25 12.8
27 26 13.9
28 27 15.0
29 28 16.1
30 29 17.2
------------------------------------------------------------
cuts: [30,35)
Time Kilometres
31 30 18.3
32 31 19.4
33 32 20.5
34 33 21.6
35 34 22.7
How could I access the data in each cut..like get the kilometres data from cuts:[20,25]..etc I tried doing data$Kilometres...but this does not work...So I basically want a new data frame where I could use the kilometres data seperately for each cut
The output of by here is a list, so you can use basic list indexing, either by number or name. Using the data from your question from a few hours ago, and the answer from Matthew Lundberg, we can index as follows:
> x[[1]]
Time Velocity
1 0.0 0.00
2 1.5 1.21
3 3.0 1.26
4 4.5 1.31
> x[["[6,12)"]]
Time Velocity
5 6.0 1.36
6 7.5 1.41
7 9.0 1.46
8 10.5 1.51
You can review the structure of objects in R by using str. This is usually useful to help you decide how you can extract certain information. Here's str(x):
> str(x)
List of 7
$ [0,6) :Classes ‘AsIs’ and 'data.frame': 4 obs. of 2 variables:
..$ Time : num [1:4] 0 1.5 3 4.5
..$ Velocity: num [1:4] 0 1.21 1.26 1.31
$ [6,12) :Classes ‘AsIs’ and 'data.frame': 4 obs. of 2 variables:
..$ Time : num [1:4] 6 7.5 9 10.5
..$ Velocity: num [1:4] 1.36 1.41 1.46 1.51
$ [12,18):Classes ‘AsIs’ and 'data.frame': 6 obs. of 2 variables:
..$ Time : num [1:6] 12 13 14 15 16 17
..$ Velocity: num [1:6] 1.56 1.61 1.66 1.71 1.76 1.81
$ [18,24):Classes ‘AsIs’ and 'data.frame': 5 obs. of 2 variables:
..$ Time : num [1:5] 18 19 20 21 22.5
..$ Velocity: num [1:5] 1.86 1.91 1.96 2.01 2.06
$ [24,30):Classes ‘AsIs’ and 'data.frame': 4 obs. of 2 variables:
..$ Time : num [1:4] 24 25.5 27 28.5
..$ Velocity: num [1:4] 2.11 2.16 2.21 2.26
$ [30,36):Classes ‘AsIs’ and 'data.frame': 4 obs. of 2 variables:
..$ Time : num [1:4] 30 31.5 33 34.5
..$ Velocity: num [1:4] 2.31 2.36 2.41 2.42
$ [36,42):Classes ‘AsIs’ and 'data.frame': 1 obs. of 2 variables:
..$ Time : num 36
..$ Velocity: num 2.43
- attr(*, "dim")= int 7
- attr(*, "dimnames")=List of 1
..$ cuts: chr [1:7] "[0,6)" "[6,12)" "[12,18)" "[18,24)" ...
- attr(*, "call")= language by.data.frame(data = mydf, INDICES = cuts, FUN = I)
- attr(*, "class")= chr "by"
From this we can see that we have a named list of seven items, and each list contains a data.frame. Thus, if we wanted a vector of just the "Velocity" variable (second column) for the third interval, we would use something like:
> x[[3]][[2]]
[1] 1.56 1.61 1.66 1.71 1.76 1.81
I have wavelenghts from 350 to 2500 each one have data:
x350 x351 x352 x353 x354 ...... x2500
0.18 0.17 0.17 0.17 0.16 ...... 0.3
0.16 0.15 0.15 0.15 0.15 ...... 0.47
0.14 0.14 0.13 0.13 0.13 ...... 0.35
I need to make one column without the name of the wavelenght and give to this new colum a name:
Wave
0.18
0.16
0.14
0.17
0.15
0.14
0.17
0.15
0.13
0.16
0.15
0.13
.
.
.
0.3
0.47
0.35
m is my file and the columns of the wavelenghts are from 17 col to 2167 col. I tried:
a <- list(m[1:16,17:2167])
but I get the list with the names of the columns in between:
list(structure(list(X350 = c(0.15723315, 0.138406682, 0.174909807,
0.143139974, 0.123193808, 0.154449448, 0.163255619, 0.126194713,
0.14327512, 0.066265248, 0.139851395, 0.158271497, 0.158060045,
0.145313933, 0.143890661), X351 = c(0.154324452, 0.135509959,
0.173350322, 0.139867145, 0.121439474, 0.15276091, 0.160391152,
0.125592826, 0.140349489, 0.065316491, 0.137927937, 0.158400317,
0.156211611, 0.142498763, 0.141353986), X352 = c(0.151243533....
How can I get just one column with one name from 2465 columns?
More info
str(m)
'data.frame': 16 obs. of 2167 variables:
$ pott : int 48 49 50 51 52 53 54 55 56 57 ...
$ b : chr "B1" "B1" "B1" "B1" ...
$ F : int 1 1 1 1 1 1 1 1 1 1 ...
$ G : chr "Sunstar" "Quarrion" "Nacozari" "W130114" ...
$ R : int 3 3 3 3 3 3 3 3 3 3 ...
$ D : int 80 80 81 80 81 80 82 82 82 82 ...
$ W: num 1.8 1.5 1.3 1.9 1.8 1.25 1.85 2.1 1.6 2.4 ...
$ S : num 43.4 35.7 44.7 48.6 45.3 35.5 49.2 49.1 46.8 41.5 ...
$ R : num -0.327 1.149 2.348 1.636 1.952 ...
$ V : num 76.4 49 118.9 108 114.5 ...
$ J : num 158 114 191 169 183 ...
$ P: num 19.9 10.6 24.1 21.1 23.6 ...
$ Ce : num 0.367 0.13 0.466 0.36 0.462 ...
$ Ci : num 273 246 280 263 272 ...
$ S : num 23.5 29 30.9 29.4 24.1 ...
$ L : num 42.5 34.4 32.4 34 41.4 ...
$ X350 : num 0.176 0.157 0.138 0.175 0.143 ...
$ X351 : num 0.172 0.154 0.136 0.173 0.14 ...
$ X352 : num 0.169 0.151 0.133 0.172 0.138 ...
$ X353 : num 0.167 0.147 0.132 0.17 0.137 ...
$ X354 : num 0.165 0.147 0.13 0.167 0.133 ...
$ X355 : num 0.162 0.146 0.127 0.166 0.13 ...
$ X356 : num 0.159 0.144 0.126 0.164 0.128 ...
$ X357 : num 0.158 0.14 0.125 0.161 0.125 ...
$ X358 : num 0.155 0.138 0.123 0.159 0.124 ...
$ X359 : num 0.153 0.137 0.121 0.157 0.123 ...
$ X360 : num 0.15 0.135 0.12 0.154 0.122 ...
....$2500
I guess your data are in a text file
data <- read.table("your_file", header=T, quote="\"")
so, data will look like
structure(list(x350 = c(0.18, 0.16, 0.14), x351 = c(0.17, 0.15,
0.14), x352 = c(0.17, 0.15, 0.13), x353 = c(0.17, 0.15, 0.13)), .Names = c("x350",
"x351", "x352", "x353"), class = "data.frame", row.names = c(NA,
-3L))
and
result <- data.frame(Wave = unlist(data,use.names=FALSE))
will produce
Wave
1 0.18
2 0.16
3 0.14
4 0.17
5 0.15
6 0.14
7 0.17
8 0.15
9 0.13
10 0.17
11 0.15
12 0.13