How to get the summary statistics including all basic statistical values for R data frame columns?
When we apply summary function in R, the output gives minimum, first quartile, median, mean, third quartile, and maximum but there are many other basic statistical values that help us to understand the variable such as range, sum, standard error of mean, variance, standard deviation, and coefficient of variation. Therefore, if we want to find all the values then we can use stat.desc function of pastecs package as shown in the below examples.
Example1
Consider the below data frame −
Live Demo
> x1<-rnorm(20)
> x2<-rnorm(20)
> x3<-rnorm(20)
> df1<-data.frame(x1,x2,x3)
> df1
Output
x1 x2 x3
1 1.37057327 0.96585723 -1.6824440
2 0.43258556 -2.54077794 -1.5962218
3 0.68188832 1.08144561 -0.9956110
4 0.24553258 0.07541754 -0.3527252
5 -0.19946765 0.49262220 -0.7946248
6 -1.93924451 0.13544724 -0.4184053
7 0.27443524 0.08363552 0.8696729
8 -2.02613035 -0.67827697 -0.8940207
9 0.33772301 -1.51171368 0.4032073
10 -0.44463177 1.69245587 1.7037202
11 1.69256604 -0.60384845 0.7247898
12 0.11356829 1.05543184 0.9780191
13 -0.01516246 0.92529906 0.4805570
14 -0.78159893 -0.55414738 -0.4680645
15 -0.08974609 0.76847977 -0.2780631
16 -0.45456509 1.08361106 -1.6672789
17 1.13920983 0.24680491 1.3922984
18 0.55562889 -0.06529163 -0.7083794
19 -0.11607439 1.09421670 2.1602874
20 -0.78351132 0.48005020 0.3453250
Finding summary of df1 using summary function −
> summary(df1)
Output
x1 x2 x3
Min. :-2.0261304 Min. :-2.5408 Min. :-1.6824
1st Qu.:-0.4471151 1st Qu.:-0.1875 1st Qu.:-0.8195
Median : 0.0492029 Median : 0.3634 Median :-0.3154
Mean :-0.0003211 Mean : 0.2113 Mean :-0.0399
3rd Qu.: 0.4633464 3rd Qu.: 0.9883 3rd Qu.: 0.7610
Max. : 1.6925660 Max. : 1.6925 Max. : 2.1603
Loading pastecs package and finding the statistical summary of df1 using stat.desc function −
> library(pastecs)
> stat.desc(df1)
Output
x1 x2 x3
nbr.val 2.000000e+01 20.0000000 20.00000000
nbr.null 0.000000e+00 0.0000000 0.00000000
nbr.na 0.000000e+00 0.0000000 0.00000000
min -2.026130e+00 -2.5407779 -1.68244397
max 1.692566e+00 1.6924559 2.16028742
range 3.718696e+00 4.2332338 3.84273139
sum -6.421540e-03 4.2267187 -0.79796158
median 4.920292e-02 0.3634276 -0.31539416
mean -3.210770e-04 0.2113359 -0.03989808
SE.mean 2.103941e-01 0.2262258 0.25081489
CI.mean.0.95 4.403600e-01 0.4734961 0.52496160
var 8.853137e-01 1.0235624 1.25816219
std.dev 9.409111e-01 1.0117126 1.12167829
coef.var -2.930484e+03 4.7872246 -28.11359138
Example2
Live Demo
> y1<-rpois(20,5)
> y2<-rpois(20,2)
> y3<-rpois(20,10)
> y4<-rpois(20,8)
> df2<-data.frame(y1,y2,y3,y4)
> df2
Output
y1 y2 y3 y4
1 4 4 10 6
2 4 1 9 8
3 2 3 12 9
4 4 0 11 4
5 7 3 7 7
6 6 0 9 18
7 5 1 7 3
8 6 2 5 10
9 5 1 10 5
10 6 1 12 7
11 11 2 8 7
12 4 2 10 11
13 4 3 7 6
14 4 0 11 15
15 10 1 8 8
16 5 0 6 8
17 3 1 13 14
18 4 1 8 5
19 5 1 5 4
20 8 2 13 5
Finding the statistical summary of df2 using stat.desc function −
> stat.desc(df2)
Output
y1 y2 y3 y4
nbr.val 20.0000000 20.0000000 20.0000000 20.0000000
nbr.null 0.0000000 4.0000000 0.0000000 0.0000000
nbr.na 0.0000000 0.0000000 0.0000000 0.0000000
min 2.0000000 0.0000000 5.0000000 3.0000000
max 11.0000000 4.0000000 13.0000000 18.0000000
range 9.0000000 4.0000000 8.0000000 15.0000000
sum 107.0000000 29.0000000 181.0000000 160.0000000
median 5.0000000 1.0000000 9.0000000 7.0000000
mean 5.3500000 1.4500000 9.0500000 8.0000000
SE.mean 0.4988144 0.2562380 0.5547641 0.8795932
CI.mean.0.95 1.0440305 0.5363122 1.1611345 1.8410097
var 4.9763158 1.3131579 6.1552632 15.4736842
std.dev 2.2307657 1.1459310 2.4809803 3.9336604
coef.var 0.4169656 0.7902973 0.2741415 0.4917076
Published on 05-Mar-2021 07:10:19
Data Structure
Networking
RDBMS
Operating System
Java
iOS
HTML
CSS
Android
Python
C Programming
C++
C#
MongoDB
MySQL
Javascript
PHP