Python integration (for use in Jupyter Notebooks)

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")

Load ggplot2 and ComplexUpset

%%R
library(ggplot2)
library(ComplexUpset)

Prepare the datasets

from pydataset import data as load_data
movies = load_data('movies').dropna()
movies.head(3).T
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
genres = list(movies.columns[-7:])
genres
['Action', 'Animation', 'Comedy', 'Drama', 'Documentary', 'Romance', 'Short']

Convert the genre indicator columns to use boolean values:

movies[genres] = movies[genres] == 1
movies[genres].head(3).T
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

Quick notes on rpy2 %%R magic usage

  • use -i switch to import data into R using rpy2 interface
  • -w and -h can be used to adjust the width and height of the plot
  • -r switch can be used to adjust DPI

Import the Python data frame to R

%R -i movies -i genres

0. Basic usage

There are two required arguments:

  • the first argument is expected to be a dataframe with both group indicator variables and covariates,
  • the second argument specifies a list with names of column which indicate the group membership.

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)

0.1 Selecting intersections

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(
    movies, genres, width_ratio=0.1,
    min_degree=3,
)

Or request a constant number of intersections with n_intersections:

%%R -w 800 -h 300
upset(
    movies, genres, width_ratio=0.1,
    n_intersections=15
)

0.2 Region selection modes

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 set
  • inclusive_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
abc_data = create_upset_abc_example()

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(
        abc_data, aes(label=size),
        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:

  • exclusive intersection: \((A \cap B) \setminus C\)
  • inclusive intersection: \(A \cap B\)
  • exclusive union: \((A \cup B) \setminus C\)
  • inclusive union: \(A \cup B\)

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)
)
highlight = function(regions) scale_fill_venn_mix(
    abc_data, guide='none', highlight=regions, inactive_color='NA'
)

(
    (
        simple_venn + highlight(c('A-B')) + labs(title='Exclusive intersection of A and B')
        | simple_venn + highlight(c('A-B', 'A-B-C')) + labs(title='Inclusive intersection of A and B')
    ) /
    (
        simple_venn + highlight(c('A-B', 'A', 'B')) + labs(title='Exclusive union of A and B')
        | 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
abc_upset = function(mode) upset(
    abc_data, c('A', 'B', 'C'), mode=mode, set_sizes=FALSE,
    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'))
)

0.3 Displaying all intersections

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
)

1. Adding components

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
)

1.1. Changing modes in annotations

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
)

2. Running statistical tests

%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:

  • all the variables (test=your.test), or
  • specific variables (using tests=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
chisq_from_formula = function(formula, data) {
    chisq.test(
        ftable(formula, data)
    )
}

anova_single = function(formula, data) {
    result = summary(aov(formula, data))
    list(
        p.value=result[[1]][['Pr(>F)']][[1]],
        method='Analysis of variance Pr(>F)',
        statistic=result[[1]][['F value']][[1]]
    )
}

custom_tests = list(
    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
bartlett_results = suppressWarnings(upset_test(movies, genres, test=bartlett.test, min_size=2))
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

2.1 Ignore specific variables

You may want to exclude variables which are:

  • highly correlated and therefore interfering with the FDR calculation, or
  • simply irrelevant

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"  

3. Adjusting “Intersection size”

3.1 Counts

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
)

3.2 Fill the bars

%%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
)

3.3 Adjusting the height ratio

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
)

3.5 Hiding intersection size

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
)

3.6 Showing intersection size/union size ratio

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(
    movies, genres, name='genre', width_ratio=0.1, min_size=10,
    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).

3.7 Showing percentages

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(
    movies, genres, name='genre', width_ratio=0.1, min_size=10,
    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.

3.8 Further adjustments using ggplot2 functions

%%R  -w 800 -h 300
upset(
    movies, genres, width_ratio=0.1,
    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
)

4. Adjusting “set size”

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)
)

4.1 Rotate labels

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(
    movies, genres, width_ratio=0.3, min_size=100, wrap=TRUE,
    set_sizes=(
        upset_set_size()
        + theme(axis.ticks.x=element_line())
    )
)

4.2 Modify geoms and other layers

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(
        movies, genres, width_ratio=0.5, max_size=100, min_size=15, wrap=TRUE,
        set_sizes=upset_set_size(
            geom=geom_bar(width=0.4)
        )
    )
    +
    upset(
        movies, genres, width_ratio=0.5, max_size=100, min_size=15, wrap=TRUE,
        set_sizes=upset_set_size(
            geom=geom_point(
                stat='count',
                color='blue'
            )
        )
    )
    +
    upset(
        movies, genres, width_ratio=0.5, max_size=100, min_size=15, wrap=TRUE,
        set_sizes=(
            upset_set_size(
                geom=geom_point(stat='count'),
                mapping=aes(y=..count../max(..count..)),
            )
            + ylab('Size relative to the largest')
        )
    )
)

4.3 Logarithmic scale

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)')
)

4.4 Display counts

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))
    )
)

4.5 Change position and add fill

%%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'
)

4.6 Hide the set sizes altogether

%%R -w 500 -h 300

upset(
    movies, genres,
    min_size=10,
    set_sizes=FALSE
)

5. Adjusting other aesthetics

5.1 Stripes

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
genre_metadata = data.frame(
    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
    )
)

5.2 Adding title

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')

5.3 Making the plot transparent

You need to set the plot background to transparent and adjust colors of stripes to your liking:

%%R -w 600 -h 400
(
    upset(
        movies, genres, name='genre', width_ratio=0.1, min_size=10,
        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.

5.4 Adjusting the intersection matrix

Use intersection_matrix() to modify the matrix parameters:

%%R -w 800 -h 400
upset(
    movies, genres, name='genre', min_size=10,
    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')
        )
    )
)

6. Themes

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.

6.1 Substituting themes

%%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())
    )
)

6.2 Adjusting the default themes

Modify all the default themes as once with upset_default_themes():

%%R -w 800 -h 400

upset(
    movies, genres, min_size=10, width_ratio=0.1,
    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))
        )
    )
)

7. Highlighting (queries)

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(
    movies, genres, name='genre', width_ratio=0.1, min_size=10,
    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')
        )
    )
)

8. Sorting

8.1 Sorting intersections

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(
    movies, genres, name='genre', width_ratio=0.1, min_size=10,
    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'
    )
)

8.2 Sorting sets

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)

9. Grouping

9.1 Grouping intersections

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(
    movies, c("Action", "Comedy", "Drama"),
    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')
    )
)

10. Display percentages

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
rating_scale = scale_fill_manual(values=c(
    'R'='#E41A1C', 'PG'='#377EB8',
    'PG-13'='#4DAF4A', 'NC-17'='#FF7F00'
))
show_hide_scale = scale_color_manual(values=c('show'='black', 'hide'='transparent'), guide='none')

10.1 Within intersection

%%R -w 800 -h 500

upset(
    movies, genres, name='genre', width_ratio=0.1, min_size=100,
    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
            )
        )
    )
)

10.2 Relative to the group

%%R -w 800 -h 500

upset(
    movies, genres, name='genre', width_ratio=0.1, min_size=100,
    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
            )
        )
    )
)

10.3 Relative to all observed values

%%R -w 800 -h 500

upset(
    movies, genres, name='genre', width_ratio=0.1, min_size=100,
    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
            )
        )
    )
)

11. Advanced usage examples

11.1 Display text on some bars only

%%R -w 800 -h 500

upset(
    movies, genres, name='genre', width_ratio=0.1, min_size=100,
    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
            )
        )
    )
)

11.2 Combine multiple plots together

%%R -w 800 -h 500
library(patchwork)

annotations = list(
    'MPAA Rating'=list(
        aes=aes(x=intersection, fill=mpaa),
        geom=list(
            geom_bar(stat='count', position='fill')
        )
    )
)
set.seed(0)    # for replicable example only

data_1 = movies[sample(nrow(movies), 100), ]
data_2 = movies[sample(nrow(movies), 100), ]

u1 = upset(data_1, genres, min_size=5, base_annotations=annotations)
u2 = upset(data_2, genres, min_size=5, base_annotations=annotations)

(u1 | u2) + plot_layout(guides='collect')

11.3 Change height of the annotations

%%R -w 800 -h 350
upset(
    movies, genres, name='genre', width_ratio=0.1, min_size=100,
    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))

12. Venn diagrams

Simple implementation of Venn diagrams is provided, taking the same input format as upset() but only supporting up to three sets.

%%R
movies_subset = head(movies, 300)
genres_subset = c('Comedy', 'Drama', 'Action')

movies_subset$good_rating = movies_subset$rating > mean(movies_subset$rating)
arranged = arrange_venn(movies_subset, sets=genres_subset)

12.1 Highlight specific elements

%%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)')

)

12.2 Highlight all regions

%%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')
)

12.3 Highlight specific regions

%%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')
)

12.4 Two sets Venn

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
genres_subset = c('Action', 'Drama')
(
    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')
)