2.3 Familiarize Yourself with the Data

Let’s take an initial look at the structure of our data object using str()

str(wisc3raw)

## 'data.frame':    204 obs. of  20 variables:
##  $ id      : int  1 2 3 4 5 6 7 8 9 10 ...
##  $ verb1   : num  24.4 12.4 32.4 22.7 28.2 ...
##  $ verb2   : num  27 14.4 33.5 28.4 37.8 ...
##  $ verb4   : num  39.6 21.9 34.3 42.2 41.1 ...
##  $ verb6   : num  55.6 37.8 50.2 44.7 71 ...
##  $ perfo1  : num  19.8 5.9 27.6 33.2 27.6 ...
##  $ perfo2  : num  23 13.4 45 29.7 44.4 ...
##  $ perfo4  : num  43.9 18.3 47 46 65.5 ...
##  $ perfo6  : num  44.2 40.4 77.7 61.7 64.2 ...
##  $ info1   : num  31.3 13.8 35 24.8 25.3 ...
##  $ comp1   : num  25.6 14.8 34.7 31.4 30.3 ...
##  $ simu1   : num  22.93 7.58 28.05 8.21 15.98 ...
##  $ voca1   : num  22.2 15.4 26.8 20.2 35.4 ...
##  $ info6   : num  69.9 41.9 60.4 52.9 67.4 ...
##  $ comp6   : num  44.4 44.9 50.3 42.7 86.7 ...
##  $ simu6   : num  68 33.9 35.8 45.8 72.4 ...
##  $ voca6   : num  51.2 37.7 55.5 36 60.4 ...
##  $ momed   : num  9.5 5.5 14 14 11.5 14 9.5 5.5 9.5 11.5 ...
##  $ grad    : int  0 0 1 1 0 1 0 0 0 0 ...
##  $ constant: int  1 1 1 1 1 1 1 1 1 1 ...

From the output, we can also see that the data frame consists of 204 observations (rows) and 20 variables (columns). Each variable’s name and data type is also listed. Methods like the ones above can be an effective way to initially familiarize yourself with the main features of a dataset.