当我们在R中应用汇总函数时，输出会给出最小值，第一四分位数，中位数，均值，第三四分位数和最大值，但是还有许多其他基本统计值可帮助我们理解变量，例如范围，总和，均值的标准误，方差，标准差和变异系数。因此，如果要查找所有值，则可以使用stat.descpastecs软件包的功能，如以下示例所示。
考虑以下数据帧-
> x1<-rnorm(20) > x2<-rnorm(20) > x3<-rnorm(20) > df1<-data.frame(x1,x2,x3) > df1输出结果
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
使用摘要功能查找df1的摘要-
> summary(df1)输出结果
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
加载pastecs软件包并使用stat.desc函数查找df1的统计摘要-
> library(pastecs) > stat.desc(df1)输出结果
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
> y1<-rpois(20,5) > y2<-rpois(20,2) > y3<-rpois(20,10) > y4<-rpois(20,8) > df2<-data.frame(y1,y2,y3,y4) > df2输出结果
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
使用stat.desc函数查找df2的统计摘要-
> stat.desc(df2)输出结果
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