R: Using dplyr summarise_all

R: dplyr summarise_all

Peter Lin

2018/4/6

Using summarise_all in dplyr package

summarise vs summarise_all

---

first: let’s random look at the data

library(dplyr)

## 
## Attaching package: 'dplyr'

## The following objects are masked from 'package:stats':
## 
##     filter, lag

## The following objects are masked from 'package:base':
## 
##     intersect, setdiff, setequal, union

iris[sample(1:nrow(iris),10),]

##     Sepal.Length Sepal.Width Petal.Length Petal.Width    Species
## 50           5.0         3.3          1.4         0.2     setosa
## 138          6.4         3.1          5.5         1.8  virginica
## 83           5.8         2.7          3.9         1.2 versicolor
## 23           4.6         3.6          1.0         0.2     setosa
## 54           5.5         2.3          4.0         1.3 versicolor
## 97           5.7         2.9          4.2         1.3 versicolor
## 24           5.1         3.3          1.7         0.5     setosa
## 141          6.7         3.1          5.6         2.4  virginica
## 20           5.1         3.8          1.5         0.3     setosa
## 30           4.7         3.2          1.6         0.2     setosa

second: let’s using summarise

iris %>% group_by(Species) %>% summarise(SL.mean=mean(Sepal.Length))

## # A tibble: 3 x 2
##   Species    SL.mean
##   <fct>        <dbl>
## 1 setosa        5.01
## 2 versicolor    5.94
## 3 virginica     6.59

# if we calculate all ...
iris %>% group_by(Species) %>% summarise(SL.mean=mean(Sepal.Length),SW.mean=mean(Sepal.Width),PL.mean=mean(Petal.Length),PW.mean=mean(Petal.Width))

## # A tibble: 3 x 5
##   Species    SL.mean SW.mean PL.mean PW.mean
##   <fct>        <dbl>   <dbl>   <dbl>   <dbl>
## 1 setosa        5.01    3.43    1.46   0.246
## 2 versicolor    5.94    2.77    4.26   1.33 
## 3 virginica     6.59    2.97    5.55   2.03

finally: let’s using summarise_all

iris %>% group_by(Species) %>% summarise_all(mean)

## # A tibble: 3 x 5
##   Species    Sepal.Length Sepal.Width Petal.Length Petal.Width
##   <fct>             <dbl>       <dbl>        <dbl>       <dbl>
## 1 setosa             5.01        3.43         1.46       0.246
## 2 versicolor         5.94        2.77         4.26       1.33 
## 3 virginica          6.59        2.97         5.55       2.03