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How to extract statistical summary from boxplot in R?
To extract statistical summary from boxplot we can use stats function with delta operator. For example, if we have a data frame called df that contains 5 columns then the boxplot for each column can be created by using the command boxplot(df) and if we want to extract the statistical summary from this boxplot then boxplot(df)$stats can be used.
Consider the below data frame −
Example
df<-data.frame(x=rnorm(20),y=rnorm(20,2,0.35),z=rnorm(20,5,0.87)) df
Output
x y z 1 0.42464003 2.174201 5.867968 2 -2.26742343 2.015934 5.016444 3 0.53905022 2.030312 5.317082 4 0.45316334 2.544108 6.561526 5 -0.20622226 2.523544 5.800500 6 -1.04035346 2.159960 4.796673 7 -1.55531189 2.079003 3.412160 8 -1.49530817 2.009581 4.052736 9 0.39796949 1.575125 5.328166 10 -0.33719074 1.667450 4.302307 11 -0.02416107 2.100736 2.979569 12 -0.19110426 2.148660 4.439635 13 0.12629817 1.593884 5.854684 14 -0.89502785 1.564742 3.298984 15 0.03870768 1.791996 4.968653 16 -0.24417567 1.315945 4.748624 17 0.44633643 2.128895 4.301884 18 2.01719942 2.139194 6.006298 19 -1.23681599 1.783813 6.557920 20 -0.10166870 1.502973 4.939246
Creating boxplot for columns in df −
Example
boxplot(df)
Output
Extracting the statistical summary from boxplot of df −
Example
Summary<-boxplot(df)$stats colnames(Summary)<-c("x","y","z") rownames(Summary)<-c("Min","First Quartile","Median","Third Quartile","Maximum") Summary
Output
x y z Min -2.2674234 1.315945 2.979569 First Quartile -0.9676907 1.630667 4.302095 Median -0.1463865 2.023123 4.953950 Third Quartile 0.4113048 2.143927 5.827592 Maximum 2.0171994 2.544108 6.561526
Example
Gender_data<-data.frame(Male=rpois(20,50),Female=rpois(20,50)) Gender_data
Output
Male Female 1 56 34 2 48 58 3 48 55 4 50 37 5 47 53 6 56 46 7 56 50 8 48 42 9 44 37 10 59 54 11 69 44 12 53 43 13 66 43 14 42 45 15 49 54 16 45 45 17 46 45 18 42 61 19 68 46 20 60 65
Example
Summary<-boxplot(Gender_data)
Output
Extracting the statistical summary from boxplot of df −
Example
Summary<-boxplot(Gender_data)$stats colnames(Summary)<-c("Male","Female") rownames(Summary)<-c("Min","First Quartile","Median","Third Quartile","Maximum") Summary
Output
Male Female Min 42.0 34.0 First Quartile 46.5 43.0 Median 49.5 45.5 Third Quartile 57.5 54.0 Maximum 69.0 65.0 attr(,"class") Male "integer"
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