Stem and Leaf Display
DESCRIPTION:
Prints a stem-and-leaf display for the given data. The form of the display can be produced automatically, or be controlled by the user.
USAGE: 
stem(x, nl=<<see below>>, scale=<<see below>>, twodig=F,
      fence=2, head=T, depth=F)
REQUIRED ARGUMENTS:
x:
numeric vector to be displayed. Missing values (NAs) are allowed.
OPTIONAL ARGUMENTS:
nl:
number of different leaf values on a stem. Allowed values are 2, 5, 10. The default is to determine an appropriate value automatically.
scale:
position at which the break occurs between the stem and the leaves, counting to the right from the decimal point; e.g., -1 would break between the tens and the units digit. By default, a suitable position is chosen from the range of the data.
twodig:
logical flag: if TRUE, two digits are printed for each observation.
fence:
the multiple of the inter-quartile range used to determine outliers. By default, any point further than 2 inter-quartile ranges from the nearest quartile is considered an outlier, and is printed separately from the body of the stem-and-leaf display. If the inter-quartile range is zero, the algorithm performs outlier detection by means of quartiles of the remainder of the data after exclusion of values equal to the median and quartiles.
head:
if TRUE, print a heading giving median, quartiles, and counts of data values and NAs.
depth:
if TRUE, precede each line with depth and count. The count is the number of data values on a line. The depth is the cumulative sum of the counts to the nearer extreme.
SIDE EFFECTS:
a stem and leaf display of x is printed. Stem and leaf displays are very similar to histograms, but retain more information, and are very easy to produce by hand.
DETAILS:
The number of missing values is stated in the printout if head is TRUE.

A number that is precisely zero is identified by z (or zz if twodig is TRUE). An error occurs if there is only one unique value in the data.

REFERENCES:
Hoaglin, D. C., Mosteller, F. and Tukey, J. W., editors (1983). Understanding Robust and Exploratory Data Analysis. Wiley, New York.

Mosteller, F. and Tukey, J. W. (1977). Data Analysis and Regression. Addison-Wesley, Reading, Mass.

Velleman, P. F. and Hoaglin, D. C. (1981). Applications, Basics, and Computing of Exploratory Data Analysis. Duxbury, Boston.

SEE ALSO:
hist , boxplot .

EXAMPLES: 
  stem(lottery.payoff)


N = 254   Median = 270.25
Quartiles = 194, 365


Decimal point is 2 places to the right of the colon


   0 : 8
   1 : 000011122233333333333344444
   1 : 55555566666677777778888888899999999999
   2 : 0000000111111111111222222233333333444444444
   2 : 555556666666666777778889999999999999999
   3 : 000000001111112222333333333444
   3 : 55555555666667777777888888899999999
   4 : 0122234
   4 : 55555678888889
   5 : 111111134
   5 : 555667
   6 : 44
   6 : 7


High: 756.0 869.5