Please install the requirements using:
pip install pandas pydataset rpy2
Load rpy2
extension:
%%capture
%load_ext rpy2.ipython
Install the package (if not already installed):
%%R
if (!require(devtools, quietly=T)) install.packages("devtools")
if (!require(ComplexUpset, quietly=T)) devtools::install_github("krassowski/complex-upset")
from pydataset import data as load_data
= load_data('movies').dropna()
movies 3).T movies.head(
48 | 112 | 124 | |
---|---|---|---|
title | ’Til There Was You | 10 Things I Hate About You | 100 Mile Rule |
year | 1997 | 1999 | 2002 |
length | 113 | 97 | 98 |
budget | 2.3e+07 | 1.6e+07 | 1.1e+06 |
rating | 4.8 | 6.7 | 5.6 |
votes | 799 | 19095 | 181 |
r1 | 4.5 | 4.5 | 4.5 |
r2 | 4.5 | 4.5 | 4.5 |
r3 | 4.5 | 4.5 | 4.5 |
r4 | 14.5 | 4.5 | 4.5 |
r5 | 14.5 | 4.5 | 14.5 |
r6 | 14.5 | 14.5 | 24.5 |
r7 | 14.5 | 24.5 | 14.5 |
r8 | 4.5 | 14.5 | 14.5 |
r9 | 4.5 | 14.5 | 4.5 |
r10 | 14.5 | 14.5 | 14.5 |
mpaa | PG-13 | PG-13 | R |
Action | 0 | 0 | 0 |
Animation | 0 | 0 | 0 |
Comedy | 1 | 1 | 1 |
Drama | 0 | 0 | 0 |
Documentary | 0 | 0 | 0 |
Romance | 1 | 1 | 0 |
Short | 0 | 0 | 0 |
= list(movies.columns[-7:])
genres genres
['Action', 'Animation', 'Comedy', 'Drama', 'Documentary', 'Romance', 'Short']
Convert the genre indicator columns to use boolean values:
= movies[genres] == 1
movies[genres] 3).T movies[genres].head(
48 | 112 | 124 | |
---|---|---|---|
Action | False | False | False |
Animation | False | False | False |
Comedy | True | True | True |
Drama | False | False | False |
Documentary | False | False | False |
Romance | True | True | False |
Short | False | False | False |
There are two required arguments:
Additional arguments can be provided, such as name
(specifies xlab()
for intersection matrix) or
width_ratio
(specifies how much space should be occupied by
the set size panel). Other such arguments are discussed at length later
in this document.
%%R -w 800 -h 300
upset(movies, genres, name='genre', width_ratio=0.1)
We will focus on the intersections with at least ten members
(min_size=10)
and on a few variables which are
significantly different between the intersections (see 2. Running
statistical tests).
When using min_size
, the empty groups will be skipped by
default (e.g. Short movies would have no overlap with size of
10). To keep all groups pass keep_empty_groups=TRUE
:
%%R -w 800 -h 300
(upset(movies, genres, name='genre', width_ratio=0.1, min_size=10, wrap=TRUE, set_sizes=FALSE)
+ ggtitle('Without empty groups (Short dropped)')
+ # adding plots is possible thanks to patchwork
upset(movies, genres, name='genre', width_ratio=0.1, min_size=10, keep_empty_groups=TRUE, wrap=TRUE, set_sizes=FALSE)
+ ggtitle('With empty groups')
)
When empty columns are detected a warning will be issued. The silence
it, pass warn_when_dropping_groups=FALSE
. Complimentary
max_size
can be used in tandem.
You can also select intersections by degree (min_degree
and max_degree
):
%%R -w 800 -h 300
upset(
width_ratio=0.1,
movies, genres, min_degree=3,
)
Or request a constant number of intersections with
n_intersections
:
%%R -w 800 -h 300
upset(
width_ratio=0.1,
movies, genres, n_intersections=15
)
There are four modes defining the regions of interest on corresponding Venn diagram:
exclusive_intersection
region: intersection elements
that belong to the sets defining the intersection but not to any other
set (alias: distinct), default
inclusive_intersection
region: intersection elements
that belong to the sets defining the intersection including overlaps
with other sets (alias: intersect)exclusive_union
region: union elements that belong to
the sets defining the union, excluding those overlapping with
any other setinclusive_union
region: union elements that belong to
the sets defining the union, including those overlapping with
any other set (alias: union)Example: given three sets \(A\), \(B\) and \(C\) with number of elements defined by the Venn diagram below
%%R
= create_upset_abc_example()
abc_data
= (
abc_venn ggplot(arrange_venn(abc_data))
+ coord_fixed()
+ theme_void()
+ scale_color_venn_mix(abc_data)
)
(
abc_venn+ geom_venn_region(data=abc_data, alpha=0.05)
+ geom_point(aes(x=x, y=y, color=region), size=1)
+ geom_venn_circle(abc_data)
+ geom_venn_label_set(abc_data, aes(label=region))
+ geom_venn_label_region(
aes(label=size),
abc_data, outwards_adjust=1.75,
position=position_nudge(y=0.2)
)+ scale_fill_venn_mix(abc_data, guide='none')
)
For the above sets \(A\) and \(B\) the region selection modes correspond to region of Venn diagram defined as follows:
and have the total number of elements as in the table below:
members mode | exclusive int. | inclusive int. | exclusive union | inclusive union |
---|---|---|---|---|
(A, B) | 10 | 11 | 110 | 123 |
(A, C) == (B, C) | 6 | 7 | 256 | 273 |
(A) == (B) | 50 | 67 | 50 | 67 |
(C) | 200 | 213 | 200 | 213 |
(A, B, C) | 1 | 1 | 323 | 323 |
() | 2 | 2 | 2 | 2 |
%%R -w 600 -h 650
= (
simple_venn
abc_venn+ geom_venn_region(data=abc_data, alpha=0.3)
+ geom_point(aes(x=x, y=y), size=0.75, alpha=0.3)
+ geom_venn_circle(abc_data)
+ geom_venn_label_set(abc_data, aes(label=region), outwards_adjust=2.55)
)= function(regions) scale_fill_venn_mix(
highlight guide='none', highlight=regions, inactive_color='NA'
abc_data,
)
(
(+ highlight(c('A-B')) + labs(title='Exclusive intersection of A and B')
simple_venn | simple_venn + highlight(c('A-B', 'A-B-C')) + labs(title='Inclusive intersection of A and B')
/
)
(+ highlight(c('A-B', 'A', 'B')) + labs(title='Exclusive union of A and B')
simple_venn | simple_venn + highlight(c('A-B', 'A-B-C', 'A', 'B', 'A-C', 'B-C')) + labs(title='Inclusive union of A and B')
) )
When customizing the intersection_size()
it is important
to adjust the mode accordingly, as it defaults to
exclusive_intersection
and cannot be automatically deduced
when user customizations are being applied:
%%R -w 800 -h 450
= function(mode) upset(
abc_upset c('A', 'B', 'C'), mode=mode, set_sizes=FALSE,
abc_data, encode_sets=FALSE,
queries=list(upset_query(intersect=c('A', 'B'), color='orange')),
base_annotations=list(
'Size'=(
intersection_size(
mode=mode,
mapping=aes(fill=exclusive_intersection),
size=0,
text=list(check_overlap=TRUE)
+ scale_fill_venn_mix(
) data=abc_data,
guide='none',
colors=c('A'='red', 'B'='blue', 'C'='green3')
)
)
)
)
(abc_upset('exclusive_intersection') | abc_upset('inclusive_intersection'))
(/
abc_upset('exclusive_union') | abc_upset('inclusive_union'))
( )
To display all possible intersections (rather than only the observed
ones) use intersections='all'
.
Note 1: it is usually desired to filter all the
possible intersections down with max_degree
and/or
min_degree
to avoid generating all combinations as those
can easily use up all available RAM memory when dealing with multiple
sets (e.g. all human genes) due to sheer number of possible
combinations
Note 2: using intersections='all'
is
only reasonable for mode different from the default exclusive
intersection.
%%R -w 800 -h 300
upset(
movies, genres,width_ratio=0.1,
min_size=10,
mode='inclusive_union',
base_annotations=list('Size'=(intersection_size(counts=FALSE, mode='inclusive_union'))),
intersections='all',
max_degree=3
)
We can add multiple annotation components (also called panels) using one of the three methods demonstrated below:
%%R -w 800 -h 800
set.seed(0) # keep the same jitter for identical plots
upset(
movies,
genres,annotations = list(
# 1st method - passing list:
'Length'=list(
aes=aes(x=intersection, y=length),
# provide a list if you wish to add several geoms
geom=geom_boxplot(na.rm=TRUE)
),# 2nd method - using ggplot
'Rating'=(
# note that aes(x=intersection) is supplied by default and can be skipped
ggplot(mapping=aes(y=rating))
# checkout ggbeeswarm::geom_quasirandom for better results!
+ geom_jitter(aes(color=log10(votes)), na.rm=TRUE)
+ geom_violin(alpha=0.5, na.rm=TRUE)
),# 3rd method - using `upset_annotate` shorthand
'Budget'=upset_annotate('budget', geom_boxplot(na.rm=TRUE))
),min_size=10,
width_ratio=0.1
)
You can also use barplots to demonstrate differences in proportions of categorical variables:
%%R -w 800 -h 500
upset(
movies,
genres,annotations = list(
'MPAA Rating'=(
ggplot(mapping=aes(fill=mpaa))
+ geom_bar(stat='count', position='fill')
+ scale_y_continuous(labels=scales::percent_format())
+ scale_fill_manual(values=c(
'R'='#E41A1C', 'PG'='#377EB8',
'PG-13'='#4DAF4A', 'NC-17'='#FF7F00'
))+ ylab('MPAA Rating')
)
),width_ratio=0.1
)
Use upset_mode
to change the mode of the annotation:
%%R -w 800 -h 800
set.seed(0)
upset(
movies,
genres,mode='inclusive_intersection',
annotations = list(
# if not specified, the mode will follow the mode set in `upset()` call (here: `inclusive_intersection`)
'Length (inclusive intersection)'=(
ggplot(mapping=aes(y=length))
+ geom_jitter(alpha=0.2, na.rm=TRUE)
),'Length (exclusive intersection)'=(
ggplot(mapping=aes(y=length))
+ geom_jitter(alpha=0.2, na.rm=TRUE)
+ upset_mode('exclusive_intersection')
),'Length (inclusive union)'=(
ggplot(mapping=aes(y=length))
+ geom_jitter(alpha=0.2, na.rm=TRUE)
+ upset_mode('inclusive_union')
)
),min_size=10,
width_ratio=0.1
)
%R upset_test(movies, genres)
[1] "year, length, budget, rating, votes, r1, r2, r3, r4, r5, r6, r7, r8, r9, r10, mpaa differ significantly between intersections"
variable | p.value | statistic | test | fdr | |
---|---|---|---|---|---|
length | length | 6.511525e-71 | 422.884445 | Kruskal-Wallis rank sum test | 1.106959e-69 |
rating | rating | 1.209027e-46 | 301.727638 | Kruskal-Wallis rank sum test | 1.027673e-45 |
budget | budget | 3.899860e-44 | 288.974760 | Kruskal-Wallis rank sum test | 2.209921e-43 |
r8 | r8 | 9.900004e-39 | 261.288151 | Kruskal-Wallis rank sum test | 4.207502e-38 |
mpaa | mpaa | 3.732200e-35 | 242.779393 | Kruskal-Wallis rank sum test | 1.268948e-34 |
r9 | r9 | 1.433256e-30 | 218.781602 | Kruskal-Wallis rank sum test | 4.060891e-30 |
r1 | r1 | 2.211600e-23 | 180.327398 | Kruskal-Wallis rank sum test | 5.371029e-23 |
r4 | r4 | 1.008119e-18 | 154.627715 | Kruskal-Wallis rank sum test | 2.142254e-18 |
r3 | r3 | 2.568227e-17 | 146.702174 | Kruskal-Wallis rank sum test | 4.851095e-17 |
r5 | r5 | 9.823827e-16 | 137.663096 | Kruskal-Wallis rank sum test | 1.670051e-15 |
r7 | r7 | 9.201549e-14 | 126.192430 | Kruskal-Wallis rank sum test | 1.422058e-13 |
r2 | r2 | 2.159955e-13 | 124.006043 | Kruskal-Wallis rank sum test | 3.059936e-13 |
r10 | r10 | 1.283470e-11 | 113.381126 | Kruskal-Wallis rank sum test | 1.678384e-11 |
votes | votes | 2.209085e-10 | 105.795879 | Kruskal-Wallis rank sum test | 2.682460e-10 |
r6 | r6 | 3.779129e-05 | 70.809705 | Kruskal-Wallis rank sum test | 4.283013e-05 |
year | year | 2.745818e-02 | 46.559723 | Kruskal-Wallis rank sum test | 2.917431e-02 |
title | title | 2.600003e-01 | 34.533745 | Kruskal-Wallis rank sum test | 2.600003e-01 |
Kruskal-Wallis rank sum test
is not always the best
choice.
You can either change the test for:
test=your.test
), ortests=list(variable=some.test)
argument)The tests are called with
(formula=variable ~ intersection, data)
signature, such as
accepted by kruskal.test
. The result is expected to be a
list with following members:
p.value
statistic
method
It is easy to adapt tests which do not obey this signature/output convention; for example the Chi-squared test and anova can be wrapped with two-line functions as follows:
%%R
= function(formula, data) {
chisq_from_formula chisq.test(
ftable(formula, data)
)
}
= function(formula, data) {
anova_single = summary(aov(formula, data))
result list(
p.value=result[[1]][['Pr(>F)']][[1]],
method='Analysis of variance Pr(>F)',
statistic=result[[1]][['F value']][[1]]
)
}
= list(
custom_tests mpaa=chisq_from_formula,
budget=anova_single
)
%R head(upset_test(movies, genres, tests=custom_tests))
[1] "year, length, budget, rating, votes, r1, r2, r3, r4, r5, r6, r7, r8, r9, r10, mpaa differ significantly between intersections"
variable | p.value | statistic | test | fdr | |
---|---|---|---|---|---|
length | length | 6.511525e-71 | 422.884445 | Kruskal-Wallis rank sum test | 1.106959e-69 |
budget | budget | 1.348209e-60 | 13.663948 | Analysis of variance Pr(>F) | 1.145977e-59 |
rating | rating | 1.209027e-46 | 301.727638 | Kruskal-Wallis rank sum test | 6.851151e-46 |
mpaa | mpaa | 9.799097e-42 | 406.338139 | Pearson’s Chi-squared test | 4.164616e-41 |
r8 | r8 | 9.900004e-39 | 261.288151 | Kruskal-Wallis rank sum test | 3.366002e-38 |
r9 | r9 | 1.433256e-30 | 218.781602 | Kruskal-Wallis rank sum test | 4.060891e-30 |
Many tests will require at least two observations in each group. You
can skip intersections with less than two members with
min_size=2
.
%%R
= suppressWarnings(upset_test(movies, genres, test=bartlett.test, min_size=2))
bartlett_results tail(bartlett_results)
[1] "NA, year, length, budget, rating, votes, r1, r2, r3, r4, r5, r6, r7, r8, r9, r10, NA differ significantly between intersections"
variable p.value statistic
year year 1.041955e-67 386.53699
length length 3.982729e-67 383.70148
budget budget 7.637563e-50 298.89911
rating rating 3.980194e-06 66.63277
title title NA NA
mpaa mpaa NA NA
test fdr
year Bartlett test of homogeneity of variances 1.302444e-67
length Bartlett test of homogeneity of variances 4.595457e-67
budget Bartlett test of homogeneity of variances 8.183103e-50
rating Bartlett test of homogeneity of variances 3.980194e-06
title Bartlett test of homogeneity of variances NA
mpaa Bartlett test of homogeneity of variances NA
You may want to exclude variables which are:
In the movies example, the title variable is not a reasonable thing to compare. We can ignore it using:
%%R
# note: title no longer present
rownames(upset_test(movies, genres, ignore=c('title')))
[1] "year, length, budget, rating, votes, r1, r2, r3, r4, r5, r6, r7, r8, r9, r10, mpaa differ significantly between intersections"
[1] "length" "rating" "budget" "r8" "mpaa" "r9" "r1" "r4"
[9] "r3" "r5" "r7" "r2" "r10" "votes" "r6" "year"
The counts over the bars can be disabled:
%%R -w 800 -h 300
upset(
movies,
genres,base_annotations=list(
'Intersection size'=intersection_size(counts=FALSE)
),min_size=10,
width_ratio=0.1
)
The colors can be changed, and additional annotations added:
%%R -w 800 -h 300
upset(
movies,
genres,base_annotations=list(
'Intersection size'=intersection_size(
text_colors=c(
on_background='brown', on_bar='yellow'
)
)+ annotate(
geom='text', x=Inf, y=Inf,
label=paste('Total:', nrow(movies)),
vjust=1, hjust=1
)+ ylab('Intersection size')
),min_size=10,
width_ratio=0.1
)
Any parameter supported by geom_text
can be passed in
text
list:
%%R -w 800 -h 300
upset(
movies,
genres,base_annotations=list(
'Intersection size'=intersection_size(
text=list(
vjust=-0.1,
hjust=-0.1,
angle=45
)
)
),min_size=10,
width_ratio=0.1
)
%%R -w 800 -h 300
upset(
movies,
genres,base_annotations=list(
'Intersection size'=intersection_size(
counts=FALSE,
mapping=aes(fill=mpaa)
)
),width_ratio=0.1
)
%%R -w 800 -h 300
upset(
movies,
genres,base_annotations=list(
'Intersection size'=intersection_size(
counts=FALSE,
mapping=aes(fill=mpaa)
+ scale_fill_manual(values=c(
) 'R'='#E41A1C', 'PG'='#377EB8',
'PG-13'='#4DAF4A', 'NC-17'='#FF7F00'
))
),width_ratio=0.1
)
%%R -w 800 -h 300
upset(
movies,
genres,base_annotations=list(
'Intersection size'=intersection_size(
counts=FALSE,
mapping=aes(fill='bars_color')
+ scale_fill_manual(values=c('bars_color'='blue'), guide='none')
)
),width_ratio=0.1
)
Setting height_ratio=1
will cause the intersection
matrix and the intersection size to have an equal height:
%%R -w 800 -h 300
upset(
movies,
genres,height_ratio=1,
width_ratio=0.1
)
You can always disable the intersection size altogether:
%%R -w 800 -h 160
upset(
movies,
genres,base_annotations=list(),
min_size=10,
width_ratio=0.1
)
It can be useful to visualise which intersections are larger than expected by chance (assuming equal probability of belonging to multiple sets); this can be achieved using the intersection size/union size ratio.
%%R -w 800 -h 600
upset(
name='genre', width_ratio=0.1, min_size=10,
movies, genres, base_annotations=list(
'Intersection size'=intersection_size(),
'Intersection ratio'=intersection_ratio()
) )
The plot above tells us that the analysed documentary movies are almost always (in over 60% of cases) documentaries (and nothing more!), while comedies more often include elements of other genres (e.g. drama, romance) rather than being comedies alone (like stand-up shows).
text_mapping
can be used to manipulate the aesthetics of
the labels. Using the intersection_size
and
union_size
one can calculate percentage of items in the
intersection (relative to the potential size of the intersection). A
upset_text_percentage(digits=0, sep='')
shorthand is
provided for convenience:
%%R -w 800 -h 600
upset(
name='genre', width_ratio=0.1, min_size=10,
movies, genres, base_annotations=list(
# with manual aes specification:
'Intersection size'=intersection_size(text_mapping=aes(label=paste0(round(
!!get_size_mode('exclusive_intersection')/!!get_size_mode('inclusive_union') * 100
'%'))),
), # using shorthand:
'Intersection ratio'=intersection_ratio(text_mapping=aes(label=!!upset_text_percentage()))
) )
Also see 10. Display percentages.
%%R -w 800 -h 300
upset(
name='genre', width_ratio=0.1, min_size=10,
movies, genres, base_annotations=list(
'Intersection size'=intersection_size(
text_mapping=aes(label=paste0(
!!upset_text_percentage(),
'\n',
'(',
!!get_size_mode('exclusive_intersection'),
')'
)),bar_number_threshold=1,
text=list(vjust=1.1)
)
) )
If adjusting bar_number_threshold
is not sufficient, you
can specify custom rules for placement of text on bars/background:
%%R -w 800 -h 300
= get_size_mode('exclusive_intersection')
size upset(
name='genre', width_ratio=0.1, min_size=10,
movies, genres, base_annotations=list(
'Intersection size'=intersection_size(
text_mapping=aes(
label=paste0(
!!upset_text_percentage(),
'\n(', !!size, ')'
),colour=ifelse(!!size > 50, 'on_bar', 'on_background'),
y=ifelse(!!size > 50, !!size - 100, !!size)
)
)
) )
%%R -w 800 -h 300
upset(
width_ratio=0.1,
movies, genres, base_annotations = list(
'Intersection size'=(
intersection_size()
+ ylim(c(0, 700))
+ theme(plot.background=element_rect(fill='#E5D3B3'))
+ ylab('# observations in intersection')
)
),min_size=10
)
When using thresholding or selection criteria (such as
min_size
or n_intersections
) the change in
number of elements in each set size is not reflected in the set sizes
plot by default. You can change this by providing
filter_intersections=TRUE
to
upset_set_size
.
%%R -w 800 -h 250
upset(
movies, genres,min_size=200,
set_sizes=upset_set_size()
| upset(
)
movies, genres,min_size=200,
set_sizes=upset_set_size(filter_intersections=TRUE)
)
To rotate the labels modify corresponding theme:
%%R -w 400 -h 300
upset(
movies, genres,min_size=100,
width_ratio=0.15,
set_sizes=(
upset_set_size()
+ theme(axis.text.x=element_text(angle=90))
) )
To display the ticks:
%%R -w 400 -h 300
upset(
width_ratio=0.3, min_size=100,
movies, genres, set_sizes=(
upset_set_size()
+ theme(axis.ticks.x=element_line())
) )
Arguments of the geom_bar
can be adjusted in
upset_set_size
; it can use a different geom, or be replaced
with a custom list of layers altogether:
%%R -w 800 -h 300
(upset(
width_ratio=0.5, max_size=100, min_size=15, wrap=TRUE,
movies, genres, set_sizes=upset_set_size(
geom=geom_bar(width=0.4)
)
)+
upset(
width_ratio=0.5, max_size=100, min_size=15, wrap=TRUE,
movies, genres, set_sizes=upset_set_size(
geom=geom_point(
stat='count',
color='blue'
)
)
)+
upset(
width_ratio=0.5, max_size=100, min_size=15, wrap=TRUE,
movies, genres, set_sizes=(
upset_set_size(
geom=geom_point(stat='count'),
mapping=aes(y=..count../max(..count..)),
)+ ylab('Size relative to the largest')
)
) )
In order to use a log scale we need to pass additional scale to in
layers
argument. However, as the bars are on flipped
coordinates, we need a reversed log transformation. Appropriate
function, reverse_log_trans()
is provided:
%%R -w 500 -h 300
upset(
movies, genres,width_ratio=0.1,
min_size=10,
set_sizes=(
upset_set_size()
+ theme(axis.text.x=element_text(angle=90))
+ scale_y_continuous(trans=reverse_log_trans())
),queries=list(upset_query(set='Drama', fill='blue'))
)
We can also modify the labels to display the logged values:
%%R -w 500 -h 300
upset(
movies, genres,min_size=10,
width_ratio=0.2,
set_sizes=upset_set_size()
+ scale_y_continuous(
trans=reverse_log_trans(),
labels=log10
)+ ylab('log10(set size)')
)
To display the count add geom_text()
:
%%R -w 500 -h 300
upset(
movies, genres,min_size=10,
width_ratio=0.3,
encode_sets=FALSE, # for annotate() to select the set by name disable encoding
set_sizes=(
upset_set_size()
+ geom_text(aes(label=..count..), hjust=1.1, stat='count')
# you can also add annotations on top of bars:
+ annotate(geom='text', label='@', x='Drama', y=850, color='white', size=3)
+ expand_limits(y=1100)
+ theme(axis.text.x=element_text(angle=90))
) )
%%R -w 500 -h 300
upset(
movies, genres,min_size=10,
width_ratio=0.3,
set_sizes=(
upset_set_size(
geom=geom_bar(
aes(fill=mpaa, x=group),
width=0.8
),position='right'
)
),# moves legends over the set sizes
guides='over'
)
%%R -w 500 -h 300
upset(
movies, genres,min_size=10,
set_sizes=FALSE
)
For compatibility with older ggplot2
versions,
upset_set_size
generates a plot with flipped coordinates
and therefore ylab
needs to be used instead of
xlab
(and aesthetic x
is used in examples
above in place of y
. This wil change it in a future major
release of ComplexUpset
.
%%R -w 400 -h 300
upset(
width_ratio=0.3, min_size=100,
movies, genres, set_sizes=(
upset_set_size()
+ ylab('MY TITLE')
) )
Change the colors:
%%R -w 600 -h 400
upset(
movies,
genres,min_size=10,
width_ratio=0.2,
stripes=c('cornsilk1', 'deepskyblue1')
)
You can use multiple colors:
%%R -w 600 -h 400
upset(
movies,
genres,min_size=10,
width_ratio=0.2,
stripes=c('cornsilk1', 'deepskyblue1', 'grey90')
)
Or, set the color to white to effectively disable the stripes:
%%R -w 600 -h 400
upset(
movies,
genres,min_size=10,
width_ratio=0.2,
stripes='white'
)
Advanced customization using upset_stripes()
:
%%R -w 600 -h 400
upset(
movies,
genres,min_size=10,
width_ratio=0.2,
stripes=upset_stripes(
geom=geom_segment(size=5),
colors=c('cornsilk1', 'deepskyblue1', 'grey90')
) )
Mapping stripes attributes to data using
upset_stripes()
:
%%R -w 600 -h 400
= data.frame(
genre_metadata set=c('Action', 'Animation', 'Comedy', 'Drama', 'Documentary', 'Romance', 'Short'),
shown_in_our_cinema=c('no', 'no', 'on weekends', 'yes', 'yes', 'on weekends', 'no')
)
upset(
movies,
genres,min_size=10,
width_ratio=0.2,
stripes=upset_stripes(
mapping=aes(color=shown_in_our_cinema),
colors=c(
'yes'='green',
'no'='red',
'on weekends'='orange'
),data=genre_metadata
) )
Adding title with ggtitle
with add it to the
intersection matrix:
%%R -w 600 -h 400
upset(movies, genres, min_size=10) + ggtitle('Intersection matrix title')
In order to add a title for the entire plot, you need to wrap the plot:
%%R -w 600 -h 400
upset(movies, genres, min_size=10, wrap=TRUE) + ggtitle('The overlap between genres')
You need to set the plot background to transparent and adjust colors of stripes to your liking:
%%R -w 600 -h 400
(upset(
name='genre', width_ratio=0.1, min_size=10,
movies, genres, stripes=c(alpha('grey90', 0.45), alpha('white', 0.3))
)& theme(plot.background=element_rect(fill='transparent', color=NA))
)
Use ggsave('upset.png', bg="transparent")
when exporting
to PNG.
Use intersection_matrix()
to modify the matrix
parameters:
%%R -w 800 -h 400
upset(
name='genre', min_size=10,
movies, genres, encode_sets=FALSE, # for annotate() to select the set by name disable encoding
matrix=(
intersection_matrix(
geom=geom_point(
shape='square',
size=3.5
),segment=geom_segment(
linetype='dotted'
),outline_color=list(
active='darkorange3',
inactive='grey70'
)
)+ scale_color_manual(
values=c('TRUE'='orange', 'FALSE'='grey'),
labels=c('TRUE'='yes', 'FALSE'='no'),
breaks=c('TRUE', 'FALSE'),
name='Is intersection member?'
)+ scale_y_discrete(
position='right'
)+ annotate(
geom='text',
label='Look here →',
x='Comedy-Drama',
y='Drama',
size=5,
hjust=1
)
),queries=list(
upset_query(
intersect=c('Drama', 'Comedy'),
color='red',
fill='red',
only_components=c('intersections_matrix', 'Intersection size')
)
) )
The themes for specific components are defined in
upset_themes
list, which contains themes for:
%%R
names(upset_themes)
[1] "intersections_matrix" "Intersection size" "overall_sizes"
[4] "default"
You can substitute this list for your own using themes
argument. While you can specify a theme for every component, if you omit
one or more components those will be taken from the element named
default
.
%%R -w 800 -h 400
upset(movies, genres, min_size=10, themes=list(default=theme()))
You can also add themes for your custom panels/annotations:
%%R -w 800 -h 800
upset(
movies,
genres,annotations = list(
'Length'=list(
aes=aes(x=intersection, y=length),
geom=geom_boxplot(na.rm=TRUE)
),'Rating'=list(
aes=aes(x=intersection, y=rating),
geom=list(
geom_jitter(aes(color=log10(votes)), na.rm=TRUE),
geom_violin(alpha=0.5, na.rm=TRUE)
)
)
),min_size=10,
width_ratio=0.1,
themes=modifyList(
upset_themes,list(Rating=theme_void(), Length=theme())
) )
Modify all the default themes as once with
upset_default_themes()
:
%%R -w 800 -h 400
upset(
min_size=10, width_ratio=0.1,
movies, genres, themes=upset_default_themes(text=element_text(color='red'))
)
To modify only a subset of default themes use
upset_modify_themes()
:
%%R -w 800 -h 400
upset(
movies, genres,base_annotations=list('Intersection size'=intersection_size(counts=FALSE)),
min_size=100,
width_ratio=0.1,
themes=upset_modify_themes(
list(
'intersections_matrix'=theme(text=element_text(size=20)),
'overall_sizes'=theme(axis.text.x=element_text(angle=90))
)
) )
Pass a list of lists generated with upset_query()
utility to the optional queries
argument to selectively
modify aesthetics of specific intersections or sets.
Use one of the arguments: set
or intersect
(not both) to specify what to highlight: - set
will
highlight the bar of the set size, - intersect
will
highlight an intersection on all components (by default), or on
components chosen with only_components
- all other
parameters will be used to modify the geoms
%%R -w 800 -h 600
upset(
name='genre', width_ratio=0.1, min_size=10,
movies, genres, annotations = list(
'Length'=list(
aes=aes(x=intersection, y=length),
geom=geom_boxplot(na.rm=TRUE)
)
),queries=list(
upset_query(
intersect=c('Drama', 'Comedy'),
color='red',
fill='red',
only_components=c('intersections_matrix', 'Intersection size')
),upset_query(
set='Drama',
fill='blue'
),upset_query(
intersect=c('Romance', 'Comedy'),
fill='yellow',
only_components=c('Length')
)
) )
By degree:
%%R -w 800 -h 300
upset(movies, genres, width_ratio=0.1, sort_intersections_by='degree')
By ratio:
%%R -w 800 -h 400
upset(
name='genre', width_ratio=0.1, min_size=10,
movies, genres, sort_intersections_by='ratio',
base_annotations=list(
'Intersection size'=intersection_size(text_mapping=aes(label=!!upset_text_percentage())),
'Intersection ratio'=intersection_ratio(text_mapping=aes(label=!!upset_text_percentage()))
) )
The other way around:
%%R -w 800 -h 300
upset(movies, genres, width_ratio=0.1, sort_intersections='ascending')
Without any sorting:
%%R -w 800 -h 300
upset(movies, genres, width_ratio=0.1, sort_intersections=FALSE)
First by degree then by cardinality:
%%R -w 800 -h 300
upset(movies, genres, width_ratio=0.1, sort_intersections_by=c('degree', 'cardinality'))
User-specified order:
%%R -w 600 -h 300
upset(
movies,
genres,width_ratio=0.1,
sort_intersections=FALSE,
intersections=list(
'Comedy',
'Drama',
c('Comedy', 'Romance'),
c('Romance', 'Drama'),
'Outside of known sets',
'Action'
) )
Ascending:
%%R -w 800 -h 300
upset(movies, genres, width_ratio=0.1, sort_sets='ascending')
Without sorting - preserving the order as in genres:
genres
['Action', 'Animation', 'Comedy', 'Drama', 'Documentary', 'Romance', 'Short']
%%R -w 800 -h 300
upset(movies, genres, width_ratio=0.1, sort_sets=FALSE)
Use group_by='sets'
to group intersections by set. If
needed, the intersections will be repeated so that they appear in each
set group. Use upset_query()
with group
argument to color the intersection matrix accordingly.
%%R -w 800 -h 300
upset(
c("Action", "Comedy", "Drama"),
movies, width_ratio=0.2,
group_by='sets',
queries=list(
upset_query(
intersect=c('Drama', 'Comedy'),
color='red',
fill='red',
only_components=c('intersections_matrix', 'Intersection size')
),upset_query(group='Drama', color='blue'),
upset_query(group='Comedy', color='orange'),
upset_query(group='Action', color='purple'),
upset_query(set='Drama', fill='blue'),
upset_query(set='Comedy', fill='orange'),
upset_query(set='Action', fill='purple')
) )
Use aes_percentage()
utility preceded with
!!
syntax to easily display percentages. In the examples
below only percentages for the movies with R rating are shown to avoid
visual clutter.
%%R
= scale_fill_manual(values=c(
rating_scale 'R'='#E41A1C', 'PG'='#377EB8',
'PG-13'='#4DAF4A', 'NC-17'='#FF7F00'
))= scale_color_manual(values=c('show'='black', 'hide'='transparent'), guide='none') show_hide_scale
%%R -w 800 -h 500
upset(
name='genre', width_ratio=0.1, min_size=100,
movies, genres, annotations =list(
'MPAA Rating'=list(
aes=aes(x=intersection, fill=mpaa),
geom=list(
geom_bar(stat='count', position='fill', na.rm=TRUE),
geom_text(
aes(
label=!!aes_percentage(relative_to='intersection'),
color=ifelse(mpaa == 'R', 'show', 'hide')
),stat='count',
position=position_fill(vjust = .5)
),scale_y_continuous(labels=scales::percent_format()),
show_hide_scale,
rating_scale
)
)
) )
%%R -w 800 -h 500
upset(
name='genre', width_ratio=0.1, min_size=100,
movies, genres, annotations =list(
'MPAA Rating'=list(
aes=aes(x=intersection, fill=mpaa),
geom=list(
geom_bar(stat='count', position='fill', na.rm=TRUE),
geom_text(
aes(
label=!!aes_percentage(relative_to='group'),
group=mpaa,
color=ifelse(mpaa == 'R', 'show', 'hide')
),stat='count',
position=position_fill(vjust = .5)
),scale_y_continuous(labels=scales::percent_format()),
show_hide_scale,
rating_scale
)
)
) )
%%R -w 800 -h 500
upset(
name='genre', width_ratio=0.1, min_size=100,
movies, genres, annotations =list(
'MPAA Rating'=list(
aes=aes(x=intersection, fill=mpaa),
geom=list(
geom_bar(stat='count', position='fill', na.rm=TRUE),
geom_text(
aes(
label=!!aes_percentage(relative_to='all'),
color=ifelse(mpaa == 'R', 'show', 'hide')
),stat='count',
position=position_fill(vjust = .5)
),scale_y_continuous(labels=scales::percent_format()),
show_hide_scale,
rating_scale
)
)
) )
%%R -w 800 -h 500
upset(
name='genre', width_ratio=0.1, min_size=100,
movies, genres, annotations =list(
'MPAA Rating'=list(
aes=aes(x=intersection, fill=mpaa),
geom=list(
geom_bar(stat='count', position='fill', na.rm=TRUE),
geom_text(
aes(label=ifelse(mpaa == 'R', 'R', NA)),
stat='count',
position=position_fill(vjust = .5),
na.rm=TRUE
),
show_hide_scale,
rating_scale
)
)
) )
%%R -w 800 -h 500
library(patchwork)
= list(
annotations 'MPAA Rating'=list(
aes=aes(x=intersection, fill=mpaa),
geom=list(
geom_bar(stat='count', position='fill')
)
)
)set.seed(0) # for replicable example only
= movies[sample(nrow(movies), 100), ]
data_1 = movies[sample(nrow(movies), 100), ]
data_2
= upset(data_1, genres, min_size=5, base_annotations=annotations)
u1 = upset(data_2, genres, min_size=5, base_annotations=annotations)
u2
| u2) + plot_layout(guides='collect') (u1
%%R -w 800 -h 350
upset(
name='genre', width_ratio=0.1, min_size=100,
movies, genres, annotations =list(
'MPAA Rating'=list(
aes=aes(x=intersection, fill=mpaa),
geom=list(
geom_bar(stat='count', position='fill'),
scale_y_continuous(labels=scales::percent_format())
)
)
)+ patchwork::plot_layout(heights=c(0.5, 1, 0.5)) )
Simple implementation of Venn diagrams is provided, taking the same
input format as upset()
but only supporting up to three
sets.
%%R
= head(movies, 300)
movies_subset = c('Comedy', 'Drama', 'Action')
genres_subset
$good_rating = movies_subset$rating > mean(movies_subset$rating)
movies_subset= arrange_venn(movies_subset, sets=genres_subset) arranged
%%R -w 800 -h 550
(ggplot(arranged)
+ theme_void()
+ coord_fixed()
+ geom_point(aes(x=x, y=y, color=region, shape=good_rating, fill=length), size=2.7)
+ geom_venn_circle(movies_subset, sets=genres_subset, size=1)
+ geom_venn_label_set(movies_subset, sets=genres_subset, aes(label=region), outwards_adjust=2.6)
+ geom_venn_label_region(movies_subset, sets=genres_subset, aes(label=size), position=position_nudge(y=0.15))
+ geom_curve(
data=arranged[which.min(arranged$length), ],
aes(xend=x+0.01, yend=y+0.01), x=1.5, y=2.5, curvature=.2,
arrow = arrow(length = unit(0.015, "npc"))
)+ annotate(
geom='text', x=1.9, y=2.6, size=6,
label=paste(substr(arranged[which.min(arranged$length), ]$title, 0, 9), 'is the shortest')
)+ scale_color_venn_mix(movies, sets=genres_subset, guide='none')
+ scale_shape_manual(
values=c(
'TRUE'='triangle filled',
'FALSE'='triangle down filled'
),labels=c(
'TRUE'='above average',
'FALSE'='below average'
),name='Rating'
)+ scale_fill_gradient(low='white', high='black', name='Length (minutes)')
)
%%R -w 800 -h 550
(ggplot(arranged)
+ theme_void()
+ coord_fixed()
+ geom_venn_region(movies_subset, sets=genres_subset, alpha=0.1)
+ geom_point(aes(x=x, y=y, color=region), size=2.5)
+ geom_venn_circle(movies_subset, sets=genres_subset, size=1.5)
+ geom_venn_label_set(movies_subset, sets=genres_subset, aes(label=region), outwards_adjust=2.6)
+ geom_venn_label_region(movies_subset, sets=genres_subset, aes(label=size), position=position_nudge(y=0.15))
+ scale_color_venn_mix(movies, sets=genres_subset, guide='none')
+ scale_fill_venn_mix(movies, sets=genres_subset, guide='none')
)
%%R -w 800 -h 550
(ggplot(arranged)
+ theme_void()
+ coord_fixed()
+ geom_venn_region(movies_subset, sets=genres_subset, alpha=0.2)
+ geom_point(aes(x=x, y=y, color=region), size=1.5)
+ geom_venn_circle(movies_subset, sets=genres_subset, size=2)
+ geom_venn_label_set(movies_subset, sets=genres_subset, aes(label=region), outwards_adjust=2.6)
+ scale_color_venn_mix(movies, sets=genres_subset, guide='none')
+ scale_fill_venn_mix(movies, sets=genres_subset, guide='none', highlight=c('Comedy-Action', 'Drama'), inactive_color='white')
)
The density of the points grid is determined in such a way that the all the points from the set with the largest space restrictions are fit into the available area. In case of the diagram below, its the observations that do not belong to any set that define the grid density:
%%R -w 600 -h 450
= c('Action', 'Drama')
genres_subset
(ggplot(arrange_venn(movies_subset, sets=genres_subset))
+ theme_void()
+ coord_fixed()
+ geom_point(aes(x=x, y=y, color=region), size=2)
+ geom_venn_circle(movies_subset, sets=genres_subset, size=2)
+ geom_venn_label_set(movies_subset, sets=genres_subset, aes(label=region), outwards_adjust=2.6)
+ scale_color_venn_mix(movies, sets=genres_subset, guide='none')
)