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Build a data frame

Source: R/fortify-data-frame-dendrogram.R
fortify_data_frame.dendrogram.Rd

[Stable]

This function converts various objects to a data frame.

Usage

# S3 method for class 'dendrogram'
fortify_data_frame(
  data,
  ...,
  priority = "right",
  center = FALSE,
  type = "rectangle",
  leaf_pos = NULL,
  leaf_braches = NULL,
  reorder_branches = TRUE,
  branch_gap = NULL,
  root = NULL,
  double = TRUE,
  data_arg = NULL,
  call = NULL
)

# S3 method for class 'hclust'
fortify_data_frame(data, ...)

Arguments

data

A hclust or a dendrogram object.

...

Additional arguments passed to dendrogram method.

priority

A string of "left" or "right". if we draw from right to left, the left will override the right, so we take the "left" as the priority. If we draw from left to right, the right will override the left, so we take the "right" as priority. This is used by align_dendro() to provide support of facet operation in ggplot2.

center

A boolean value. if TRUE, nodes are plotted centered with respect to all leaves/tips in the branch. Otherwise (default), plot them in the middle of the direct child nodes.

type

A string indicates the plot type, "rectangle" or "triangle".

leaf_pos

The x-coordinates of the leaf node. Must be the same length of the number of observations in data.

leaf_braches

Branches of the leaf node. Must be the same length of the number of observations in data. Usually come from cutree.

reorder_branches

A single boolean value, indicates whether reorder the provided leaf_braches based on the actual index.

branch_gap

A single numeric value indicates the gap between different branches.

root

A length one string or numeric indicates the root branch.

double

A single logical value indicating whether horizontal lines should be doubled when segments span multiple branches. If TRUE, the horizontal lines will be repeated for each branch that the segment spans. If FALSE, only one horizontal line will be drawn. This is used by align_dendro() to provide support of facet operation in ggplot2.

data_arg

The argument name for data. Developers can use it to improve messages. Not used by the user.

call

The execution environment where data and other arguments for the method are collected. Developers can use it to improve messages. Not used by the user.

Value

A data frame with the node coordinates:

  • .panel: Similar with panel column, but always give the correct panel for usage of the ggplot facet.

  • .index: the original index in the tree for the the node

  • label: node label text

  • x and y: x-axis and y-axis coordinates for the node

  • branch: which branch the node is. You can use this column to color different groups.

  • panel: which panel the node is, if we split the plot into panel using facet_grid, this column will show which panel the node is from. Note: some nodes may fall outside panel (between two panels), so there are possible NA values in this column.

  • leaf: A logical value indicates whether the node is a leaf.

ggalign attributes

edge: A data frame for edge coordinates:

  • .panel: Similar with panel column, but always give the correct panel for usage of the ggplot facet.

  • x and y: x-axis and y-axis coordinates for the start node of the edge.

  • xend and yend: the x-axis and y-axis coordinates of the terminal node for edge.

  • branch: which panel the edge is. You can use this column to color different groups.

  • panel1 and panel2: The panel1 and panel2 columns have the same functionality as panel, but they are specifically for the edge data and correspond to both nodes of each edge.

See also

Other fortify_data_frame() methods: fortify_data_frame.GRanges(), fortify_data_frame.character(), fortify_data_frame.default(), fortify_data_frame.matrix(), fortify_data_frame.phylo()

Examples

fortify_data_frame(hclust(dist(USArrests), "ave"))
#>    .index          label         x         y branch  leaf panel .panel
#> 1       9        Florida  1.000000  0.000000   root  TRUE  root   root
#> 2      33 North Carolina  2.000000  0.000000   root  TRUE  root   root
#> 3      NA           <NA>  1.500000 38.527912   root FALSE  root   root
#> 4       5     California  3.000000  0.000000   root  TRUE  root   root
#> 5      20       Maryland  4.000000  0.000000   root  TRUE  root   root
#> 6       3        Arizona  5.000000  0.000000   root  TRUE  root   root
#> 7      31     New Mexico  6.000000  0.000000   root  TRUE  root   root
#> 8      NA           <NA>  5.500000 13.896043   root FALSE  root   root
#> 9      NA           <NA>  4.750000 15.453120   root FALSE  root   root
#> 10     NA           <NA>  3.875000 28.012211   root FALSE  root   root
#> 11      8       Delaware  7.000000  0.000000   root  TRUE  root   root
#> 12      1        Alabama  8.000000  0.000000   root  TRUE  root   root
#> 13     18      Louisiana  9.000000  0.000000   root  TRUE  root   root
#> 14     NA           <NA>  8.500000 15.454449   root FALSE  root   root
#> 15     NA           <NA>  7.750000 16.891499   root FALSE  root   root
#> 16     13       Illinois 10.000000  0.000000   root  TRUE  root   root
#> 17     32       New York 11.000000  0.000000   root  TRUE  root   root
#> 18     NA           <NA> 10.500000  6.236986   root FALSE  root   root
#> 19     22       Michigan 12.000000  0.000000   root  TRUE  root   root
#> 20     28         Nevada 13.000000  0.000000   root  TRUE  root   root
#> 21     NA           <NA> 12.500000 13.297368   root FALSE  root   root
#> 22     NA           <NA> 11.500000 18.417331   root FALSE  root   root
#> 23     NA           <NA>  9.625000 26.363428   root FALSE  root   root
#> 24      2         Alaska 14.000000  0.000000   root  TRUE  root   root
#> 25     24    Mississippi 15.000000  0.000000   root  TRUE  root   root
#> 26     40 South Carolina 16.000000  0.000000   root  TRUE  root   root
#> 27     NA           <NA> 15.500000 21.167192   root FALSE  root   root
#> 28     NA           <NA> 14.750000 28.095803   root FALSE  root   root
#> 29     NA           <NA> 12.187500 39.394633   root FALSE  root   root
#> 30     NA           <NA>  8.031250 44.283922   root FALSE  root   root
#> 31     NA           <NA>  4.765625 77.605024   root FALSE  root   root
#> 32     47     Washington 17.000000  0.000000   root  TRUE  root   root
#> 33     37         Oregon 18.000000  0.000000   root  TRUE  root   root
#> 34     50        Wyoming 19.000000  0.000000   root  TRUE  root   root
#> 35     36       Oklahoma 20.000000  0.000000   root  TRUE  root   root
#> 36     46       Virginia 21.000000  0.000000   root  TRUE  root   root
#> 37     NA           <NA> 20.500000  7.355270   root FALSE  root   root
#> 38     NA           <NA> 19.750000 10.736739   root FALSE  root   root
#> 39     NA           <NA> 18.875000 12.878100   root FALSE  root   root
#> 40     NA           <NA> 17.937500 16.425489   root FALSE  root   root
#> 41     39   Rhode Island 22.000000  0.000000   root  TRUE  root   root
#> 42     21  Massachusetts 23.000000  0.000000   root  TRUE  root   root
#> 43     30     New Jersey 24.000000  0.000000   root  TRUE  root   root
#> 44     NA           <NA> 23.500000 11.456439   root FALSE  root   root
#> 45     NA           <NA> 22.750000 22.595978   root FALSE  root   root
#> 46     NA           <NA> 20.343750 26.713777   root FALSE  root   root
#> 47     25       Missouri 25.000000  0.000000   root  TRUE  root   root
#> 48      4       Arkansas 26.000000  0.000000   root  TRUE  root   root
#> 49     42      Tennessee 27.000000  0.000000   root  TRUE  root   root
#> 50     NA           <NA> 26.500000 12.614278   root FALSE  root   root
#> 51     NA           <NA> 25.750000 20.198479   root FALSE  root   root
#> 52     10        Georgia 28.000000  0.000000   root  TRUE  root   root
#> 53      6       Colorado 29.000000  0.000000   root  TRUE  root   root
#> 54     43          Texas 30.000000  0.000000   root  TRUE  root   root
#> 55     NA           <NA> 29.500000 14.501034   root FALSE  root   root
#> 56     NA           <NA> 28.750000 23.972143   root FALSE  root   root
#> 57     NA           <NA> 27.250000 29.054195   root FALSE  root   root
#> 58     NA           <NA> 23.796875 44.837933   root FALSE  root   root
#> 59     12          Idaho 31.000000  0.000000   root  TRUE  root   root
#> 60     27       Nebraska 32.000000  0.000000   root  TRUE  root   root
#> 61     17       Kentucky 33.000000  0.000000   root  TRUE  root   root
#> 62     26        Montana 34.000000  0.000000   root  TRUE  root   root
#> 63     NA           <NA> 33.500000  3.834058   root FALSE  root   root
#> 64     NA           <NA> 32.750000 12.438692   root FALSE  root   root
#> 65     NA           <NA> 31.875000 15.026107   root FALSE  root   root
#> 66     35           Ohio 35.000000  0.000000   root  TRUE  root   root
#> 67     44           Utah 36.000000  0.000000   root  TRUE  root   root
#> 68     NA           <NA> 35.500000  6.637771   root FALSE  root   root
#> 69     14        Indiana 37.000000  0.000000   root  TRUE  root   root
#> 70     16         Kansas 38.000000  0.000000   root  TRUE  root   root
#> 71     NA           <NA> 37.500000  3.929377   root FALSE  root   root
#> 72      7    Connecticut 39.000000  0.000000   root  TRUE  root   root
#> 73     38   Pennsylvania 40.000000  0.000000   root  TRUE  root   root
#> 74     NA           <NA> 39.500000  8.027453   root FALSE  root   root
#> 75     NA           <NA> 38.500000 13.352260   root FALSE  root   root
#> 76     NA           <NA> 37.000000 15.122897   root FALSE  root   root
#> 77     NA           <NA> 34.437500 20.598507   root FALSE  root   root
#> 78     11         Hawaii 41.000000  0.000000   root  TRUE  root   root
#> 79     48  West Virginia 42.000000  0.000000   root  TRUE  root   root
#> 80     19          Maine 43.000000  0.000000   root  TRUE  root   root
#> 81     41   South Dakota 44.000000  0.000000   root  TRUE  root   root
#> 82     NA           <NA> 43.500000  8.537564   root FALSE  root   root
#> 83     NA           <NA> 42.750000 10.771175   root FALSE  root   root
#> 84     34   North Dakota 45.000000  0.000000   root  TRUE  root   root
#> 85     45        Vermont 46.000000  0.000000   root  TRUE  root   root
#> 86     NA           <NA> 45.500000 13.044922   root FALSE  root   root
#> 87     23      Minnesota 47.000000  0.000000   root  TRUE  root   root
#> 88     49      Wisconsin 48.000000  0.000000   root  TRUE  root   root
#> 89     15           Iowa 49.000000  0.000000   root  TRUE  root   root
#> 90     29  New Hampshire 50.000000  0.000000   root  TRUE  root   root
#> 91     NA           <NA> 49.500000  2.291288   root FALSE  root   root
#> 92     NA           <NA> 48.750000 10.184218   root FALSE  root   root
#> 93     NA           <NA> 47.875000 18.993398   root FALSE  root   root
#> 94     NA           <NA> 46.687500 27.779904   root FALSE  root   root
#> 95     NA           <NA> 44.718750 33.117815   root FALSE  root   root
#> 96     NA           <NA> 42.859375 41.094765   root FALSE  root   root
#> 97     NA           <NA> 38.648438 54.746831   root FALSE  root   root
#> 98     NA           <NA> 31.222656 89.232093   root FALSE  root   root