Vorige: Functions and Variables for specific multivariate descriptive statistics, Nach oben: Package descriptive [Inhalt][Index]
Plots bars diagrams for discrete statistical variables, both for one or multiple samples.
data can be a list of outcomes representing one sample, or a matrix of m rows and n columns, representing n samples of size m each.
Available options are:
3/4
): relative width of rectangles. This
value must be in the range [0,1]
.
clustered
): indicates how multiple samples are
shown. Valid values are: clustered
and stacked
.
1
): a positive integer number representing
the gap between two consecutive groups of bars.
[]
): a list of colors for multiple samples.
When there are more samples than specified colors, the extra necesary colors
are chosen at random. See color
to learn more
about them.
absolute
): indicates the scale of the
ordinates. Possible values are: absolute
, relative
,
and percent
.
orderlessp
): possible values are
orderlessp
or ordergreatp
, indicating how statistical outcomes
should be ordered on the x
-axis.
[]
): a list with the strings to be used in
the legend. When the list length is other than 0
or the number of
samples, an error message is returned.
0
): indicates where the plot begins to be
plotted on the x
-axis.
draw
options, except xtics
, which is
internally assigned by barsplot
.
If you want to set your own values for this option or want to build
complex scenes, make use of barsplot_description
. See example below.
draw
options: key
, color
,
fill_color
, fill_density
and line_width
. See also
bars
.
Function barsplot_description
creates a graphic object
suitable for creating complex scenes, together with other
graphic objects. There is also a function wxbarsplot
for
creating embedded histograms in interfaces wxMaxima and iMaxima.
Examples:
Univariate sample in matrix form. Absolute frequencies.
(%i1) load ("descriptive")$ (%i2) m : read_matrix (file_search ("biomed.data"))$
(%i3) barsplot( col(m,2), title = "Ages", xlabel = "years", box_width = 1/2, fill_density = 3/4)$
Two samples of different sizes, with relative frequencies and user declared colors.
(%i1) load ("descriptive")$ (%i2) l1:makelist(random(10),k,1,50)$ (%i3) l2:makelist(random(10),k,1,100)$
(%i4) barsplot( l1,l2, box_width = 1, fill_density = 1, bars_colors = [black, grey], frequency = relative, sample_keys = ["A", "B"])$
Four non numeric samples of equal size.
(%i1) load ("descriptive")$
(%i2) barsplot( makelist([Yes, No, Maybe][random(3)+1],k,1,50), makelist([Yes, No, Maybe][random(3)+1],k,1,50), makelist([Yes, No, Maybe][random(3)+1],k,1,50), makelist([Yes, No, Maybe][random(3)+1],k,1,50), title = "Asking for something to four groups", ylabel = "# of individuals", groups_gap = 3, fill_density = 0.5, ordering = ordergreatp)$
Stacked bars.
(%i1) load ("descriptive")$
(%i2) barsplot( makelist([Yes, No, Maybe][random(3)+1],k,1,50), makelist([Yes, No, Maybe][random(3)+1],k,1,50), makelist([Yes, No, Maybe][random(3)+1],k,1,50), makelist([Yes, No, Maybe][random(3)+1],k,1,50), title = "Asking for something to four groups", ylabel = "# of individuals", grouping = stacked, fill_density = 0.5, ordering = ordergreatp)$
barsplot
in a multiplot context.
(%i1) load ("descriptive")$ (%i2) l1:makelist(random(10),k,1,50)$ (%i3) l2:makelist(random(10),k,1,100)$ (%i4) bp1 : barsplot_description( l1, box_width = 1, fill_density = 0.5, bars_colors = [blue], frequency = relative)$
(%i5) bp2 : barsplot_description( l2, box_width = 1, fill_density = 0.5, bars_colors = [red], frequency = relative)$
(%i6) draw(gr2d(bp1), gr2d(bp2))$
For bars diagrams related options, see bars
of package draw
.
See also functions histogram
and piechart
.
This function plots box-and-whishker diagrams. Argument data can be a
list, which is not of great interest, since these diagrams are mainly used for
comparing different samples, or a matrix, so it is possible to compare
two or more components of a multivariate statistical variable.
But it is also allowed data to be a list of samples with
possible different sample sizes, in fact this is the only function
in package descriptive
that admits this type of data structure.
Available options are:
3/4
): relative width of boxes.
This value must be in the range [0,1]
.
vertical
): possible values:
vertical
and horizontal
.
draw
options, except points_joined
, point_size
,
point_type
, xtics
, ytics
, xrange
, and yrange
,
which are internally assigned by boxplot
.
If you want to set your own values for this options or want to build
complex scenes, make use of boxplot_description
.
draw
options: key
, color
,
and line_width
.
Function boxplot_description
creates a graphic object
suitable for creating complex scenes, together with other
graphic objects. There is also a function wxboxplot
for
creating embedded histograms in interfaces wxMaxima and iMaxima.
Examples:
Box-and-whishker diagram from a multivariate sample.
(%i1) load ("descriptive")$ (%i2) s2 : read_matrix(file_search("wind.data"))$
(%i3) boxplot(s2, box_width = 0.2, title = "Windspeed in knots", xlabel = "Stations", color = red, line_width = 2)$
Box-and-whishker diagram from three samples of different sizes.
(%i1) load ("descriptive")$
(%i2) A : [[6, 4, 6, 2, 4, 8, 6, 4, 6, 4, 3, 2], [8, 10, 7, 9, 12, 8, 10], [16, 13, 17, 12, 11, 18, 13, 18, 14, 12]]$
(%i3) boxplot (A, box_orientation = horizontal)$
This function plots an histogram from a continuous sample. Sample data must be stored in a list of numbers or an one dimensional matrix.
Available options are:
10
): number of classes of the histogram, or
a list indicating the limits of the classes and the number of them, or
only the limits.
absolute
): indicates the scale of the
ordinates. Possible values are: absolute
, relative
,
and percent
.
auto
): format of the histogram tics. Possible
values are: auto
, endpoints
, intervals
, or a list
of labels.
draw
options, except xrange
, yrange
,
and xtics
, which are internally assigned by histogram
.
If you want to set your own values for these options, make use of
histogram_description
. See examples bellow.
draw
options: key
, color
,
fill_color
, fill_density
and line_width
. See also
bars
.
Function histogram_description
creates a graphic object
suitable for creating complex scenes, together with other
graphic objects. There is also a function wxhistogram
for
creating embedded histograms in interfaces wxMaxima and iMaxima.
Examples:
A simple with eight classes:
(%i1) load ("descriptive")$ (%i2) s1 : read_list (file_search ("pidigits.data"))$ (%i3) histogram ( s1, nclasses = 8, title = "pi digits", xlabel = "digits", ylabel = "Absolute frequency", fill_color = grey, fill_density = 0.6)$
Setting the limits of the histogram to -2 and 12, with 3 classes. Also, we introduce predefined tics:
(%i1) load ("descriptive")$ (%i2) s1 : read_list (file_search ("pidigits.data"))$ (%i3) histogram ( s1, nclasses = [-2,12,3], htics = ["A", "B", "C"], terminal = png, fill_color = "#23afa0", fill_density = 0.6)$
We make use of histogram_description
for setting
the xrange
and adding an explicit curve into the scene:
(%i1) load ("descriptive")$ (%i2) ( load("distrib"), m: 14, s: 2, s2: random_normal(m, s, 1000) ) $ (%i3) draw2d( grid = true, xrange = [5, 25], histogram_description( s2, nclasses = 9, frequency = relative, fill_density = 0.5), explicit(pdf_normal(x,m,s), x, m - 3*s, m + 3* s))$
Similar to barsplot
, but plots sectors instead of rectangles.
Available options are:
[]
): a list of colors for sectors.
When there are more sectors than specified colors, the extra necesary colors
are chosen at random. See color
to learn more
about them.
[0,0]
): diagram’s center.
1
): diagram’s radius.
draw
options, except key
, which is
internally assigned by piechart
.
If you want to set your own values for this option or want to build
complex scenes, make use of piechart_description
.
draw
options: key
, color
,
fill_density
and line_width
. See also
ellipse
.
Function piechart_description
creates a graphic object
suitable for creating complex scenes, together with other
graphic objects. There is also a function wxpiechart
for
creating embedded histograms in interfaces wxMaxima and iMaxima.
Example:
(%i1) load ("descriptive")$ (%i2) s1 : read_list (file_search ("pidigits.data"))$ (%i3) piechart( s1, xrange = [-1.1, 1.3], yrange = [-1.1, 1.1], title = "Digit frequencies in pi")$
See also function barsplot
.
Plots scatter diagrams both for univariate (list) and multivariate (matrix) samples.
Available options are the same admitted by histogram
.
Function scatterplot_description
creates a graphic object
suitable for creating complex scenes, together with other
graphic objects. There is also a function wxscatterplot
for
creating embedded histograms in interfaces wxMaxima and iMaxima.
Examples:
Univariate scatter diagram from a simulated Gaussian sample.
(%i1) load ("descriptive")$ (%i2) load ("distrib")$
(%i3) scatterplot( random_normal(0,1,200), xaxis = true, point_size = 2, dimensions = [600,150])$
Two dimensional scatter plot.
(%i1) load ("descriptive")$ (%i2) s2 : read_matrix (file_search ("wind.data"))$
(%i3) scatterplot( submatrix(s2, 1,2,3), title = "Data from stations #4 and #5", point_type = diamant, point_size = 2, color = blue)$
Three dimensional scatter plot.
(%i1) load ("descriptive")$ (%i2) s2 : read_matrix (file_search ("wind.data"))$ (%i3) scatterplot(submatrix (s2, 1,2), nclasses=4)$
Five dimensional scatter plot, with five classes histograms.
(%i1) load ("descriptive")$ (%i2) s2 : read_matrix (file_search ("wind.data"))$
(%i3) scatterplot( s2, nclasses = 5, frequency = relative, fill_color = blue, fill_density = 0.3, xtics = 5)$
For plotting isolated or line-joined points in two and three dimensions,
see points
. See also histogram
.
Plots star diagrams for discrete statistical variables, both for one or multiple samples.
data can be a list of outcomes representing one sample, or a matrix of m rows and n columns, representing n samples of size m each.
Available options are:
[]
): a list of colors for multiple samples.
When there are more samples than specified colors, the extra necesary colors
are chosen at random. See color
to learn more
about them.
absolute
): indicates the scale of the
radii. Possible values are: absolute
and relative
.
orderlessp
): possible values are
orderlessp
or ordergreatp
, indicating how statistical outcomes
should be ordered.
[]
): a list with the strings to be used in
the legend. When the list length is other than 0 or the number of samples, an
error message is returned.
[0,0]
): diagram’s center.
1
): diagram’s radius.
draw
options, except points_joined
, point_type
,
and key
, which are internally assigned by starplot
.
If you want to set your own values for this options or want to build
complex scenes, make use of starplot_description
.
draw
option: line_width
.
Function starplot_description
creates a graphic object
suitable for creating complex scenes, together with other
graphic objects. There is also a function wxstarplot
for
creating embedded histograms in interfaces wxMaxima and iMaxima.
Example:
Plot based on absolute frequencies. Location and radius defined by the user.
(%i1) load ("descriptive")$ (%i2) l1: makelist(random(10),k,1,50)$ (%i3) l2: makelist(random(10),k,1,200)$
(%i4) starplot( l1, l2, stars_colors = [blue,red], sample_keys = ["1st sample", "2nd sample"], star_center = [1,2], star_radius = 4, proportional_axes = xy, line_width = 2 ) $
Plots stem and leaf diagrams. Unique available option is:
1
): indicates the unit of the leaves;
must be a power of 10
.
Example:
(%i1) load ("descriptive")$ (%i2) load("distrib")$ (%i3) stemplot( random_normal(15, 6, 100), leaf_unit = 0.1); -5|4 0|37 1|7 3|6 4|4 5|4 6|57 7|0149 8|3 9|1334588 10|07888 11|01144467789 12|12566889 13|24778 14|047 15|223458 16|4 17|11557 18|000247 19|4467799 20|00 21|1 22|2335 23|01457 24|12356 25|455 27|79 key: 6|3 = 6.3 (%o3) done
Vorige: Functions and Variables for specific multivariate descriptive statistics, Nach oben: Package descriptive [Inhalt][Index]