This is the first in a series of posts examining Tate's excellent collection dataset available at http://www.tate.org.uk/about/our-work/digital/collection-data .
I've processed that dataset using code for Mongo DB and Node.js available at https://github.com/rheaplex/tate-data/ .
The R and R Markdown code for this series is available at https://github.com/rheaplex/tate-data-r/ .
This document has been produced using Knitr. Text in light grey boxes is R code or the output of that code.
Let's get started by loading the data.
source("../r/load_tate_data.r")
That file reads the comma separated value (csv) files containing information about the Tate's collection and generates some useful extra tables of information. Now we have everything in memory we can start examining the collection data.
Artists
What can we find out about artists in general?
summary(artist[c("name", "gender", "dates", "yearOfBirth", "yearOfDeath", "placeOfBirth",
"placeOfDeath")])
name gender dates
Bateman, James : 2 : 112 dates not known: 59
Doyle, John : 2 Female: 521 born 1967 : 42
Hone, Nathaniel: 2 Male :2894 born 1936 : 38
Peri, Peter : 2 born 1930 : 36
Stokes, Adrian : 2 born 1938 : 36
Wilson, Richard: 2 born 1941 : 34
(Other) :3515 (Other) :3282
yearOfBirth yearOfDeath placeOfBirth
Min. :1497 Min. :1543 : 491
1st Qu.:1855 1st Qu.:1874 London, United Kingdom : 446
Median :1910 Median :1944 Paris, France : 57
Mean :1887 Mean :1920 Edinburgh, United Kingdom: 47
3rd Qu.:1941 3rd Qu.:1982 New York, United States : 43
Max. :2004 Max. :2013 Glasgow, United Kingdom : 35
NA's :57 NA's :1309 (Other) :2408
placeOfDeath
:2079
London, United Kingdom : 442
Paris, France : 82
New York, United States : 45
Roma, Italia : 22
Edinburgh, United Kingdom: 18
(Other) : 839
There are more male than female artists, and the yBA and Pop generations lead the births.
Depending on whether we treat place of birth or place of death as more representative, London and Paris are ahead of New York or Edinburgh.
We can smooth out the birth and death dates by grouping them by decade or century.
summary(artist.birth.decade)
Min. 1st Qu. Median Mean 3rd Qu. Max. NA's
1500 1860 1910 1890 1940 2000 57
summary(artist.death.decade)
Min. 1st Qu. Median Mean 3rd Qu. Max. NA's
1540 1870 1940 1920 1980 2010 1309
sort(table(artist.birth.decade), decreasing = TRUE)
artist.birth.decade
1940 1930 1960 1920 1970 1900 1950 1910 1880 1890 1860 1870 1840 1780 1800
363 285 256 255 222 217 197 186 153 151 136 123 77 72 69
1850 1820 1830 1980 1790 1810 1760 1770 1740 1750 1730 1700 1720 1710 1630
69 67 65 58 57 49 45 44 42 38 31 27 15 13 12
1680 1640 1660 1600 1580 1590 1610 1650 1690 1620 1990 2000 1500 1530 1540
10 9 8 6 5 4 4 4 4 3 3 3 2 2 2
1550 1560 1670 1570
2 2 2 1
summary(artist.birth.century)
Min. 1st Qu. Median Mean 3rd Qu. Max. NA's
1500 1900 1900 1890 1900 2000 57
summary(artist.death.century)
Min. 1st Qu. Median Mean 3rd Qu. Max. NA's
1500 1900 1900 1920 2000 2000 1309
sort(table(artist.death.decade), decreasing = TRUE)
artist.death.decade
2000 1980 1960 1990 1970 1940 2010 1920 1930 1950 1900 1910 1840 1860 1880
224 191 172 157 140 131 112 102 92 89 80 69 59 59 54
1850 1870 1890 1820 1830 1800 1810 1780 1790 1700 1760 1770 1750 1720 1730
53 49 49 46 44 42 40 24 23 15 14 12 10 7 7
1740 1680 1710 1640 1690 1620 1650 1660 1570 1670 1600 1630 1540
7 6 6 5 5 4 4 4 3 3 2 2 1
That's quite a different result from that suggested by the yearly results. Decade-wise, birth percentiles are clustered around the turn of the 20th century, deaths around the second world war. But the largest number of births are in the 1930s/1940s with the 1960s coming in second. The deaths look like they reflect the distribution of births, although it would be useful to confirm this statistically.
The maximim birth being in the 2000s doesn't mean that the Tate is collecting child artists, the birth data also includes the years that artist groups were started.
How well is gender represented in the collection?
table(artist.birth.decade, artist$gender)
artist.birth.decade Female Male
1500 1 0 1
1530 1 0 1
1540 0 0 2
1550 0 0 2
1560 0 0 2
1570 0 0 1
1580 0 0 5
1590 1 0 3
1600 3 0 3
1610 1 0 3
1620 0 0 3
1630 0 1 11
1640 0 0 9
1650 0 0 4
1660 0 0 8
1670 1 0 1
1680 0 0 10
1690 0 0 4
1700 4 1 22
1710 0 0 13
1720 0 1 14
1730 0 0 31
1740 1 1 40
1750 0 3 35
1760 0 1 44
1770 0 1 43
1780 1 5 66
1790 1 0 56
1800 10 0 59
1810 0 2 47
1820 0 1 66
1830 1 6 58
1840 0 5 72
1850 0 2 67
1860 1 10 125
1870 0 15 108
1880 4 23 126
1890 4 18 129
1900 8 38 171
1910 3 37 146
1920 2 33 220
1930 4 38 243
1940 12 62 289
1950 2 40 155
1960 6 77 173
1970 8 70 144
1980 3 21 34
1990 2 0 1
2000 2 0 1
table(artist.birth.century, artist$gender)
artist.birth.century Female Male
1500 2 0 5
1600 5 1 44
1700 6 4 157
1800 13 24 576
1900 39 293 1667
2000 22 190 422
The first, unlabelled, column is for artists whose gender is not currently recorded in the data.
As we saw in the summary, there are more male artists than female artists in the Tate's collection. There is no decade or century in which this trend is reversed. The story is slightly different when we look at artistic movements.
Movements
The data for artists includes information on
Error in movements$movement.name :
$ operator is invalid for atomic vectors
artists movements. If we looked at the artwork data there might be more, but we'll stick with the artists for now.
summary(artist.movements[c("artist.fc", "artist.gender", "movement.era.name",
"movement.name")])
artist.fc artist.gender
Ben Nicholson OM : 6 : 5
Dame Barbara Hepworth : 5 Female: 27
Gilbert Soest : 5 Male :324
Joseph Beuys : 5
Sir Peter Lely : 5
British School 17th century: 4
(Other) :326
movement.era.name
16th and 17th century : 47
18th century : 27
19th century : 63
20th century 1900-1945: 95
20th century post-1945:124
movement.name
Performance Art : 14
Conceptual Art : 10
Netherlands-trained, working in Britain: 10
Constructivism : 9
Body Art : 8
British Surrealism : 8
(Other) :297
summary(artist.movements$movement.era.name)
16th and 17th century 18th century 19th century
47 27 63
20th century 1900-1945 20th century post-1945
95 124
summary(artist.movements$movement.name)
Performance Art
14
Conceptual Art
10
Netherlands-trained, working in Britain
10
Constructivism
9
Body Art
8
British Surrealism
8
St Ives School
8
Victorian/Genre
8
Abstraction-Création
7
British War Art
7
Court
7
Environmental Art
7
Later Stuart
7
Picturesque
7
Surrealism
7
Symbolism
7
Abject art
6
Baroque
6
British Constructivism
6
British Impressionism
6
Decadence
6
Pre-Raphaelite
6
Unit One
6
Grand Manner
5
Kinetic Art
5
Land Art
5
Minimalism
5
Neo-Romanticism
5
Tachisme
5
Vorticism
5
Aesthetic Movement
4
Camden Town Group
4
Conversation Piece
4
Cubism
4
Feminist Art
4
Geometry of Fear
4
Neo-Expressionism
4
Restoration
4
Return to Order
4
Seven and Five
4
Sublime
4
British Pop
3
Civil War and Commonwealth
3
Dada
3
Fancy Picture
3
Fin de Siècle
3
Impressionism
3
London Group
3
New English Art Club
3
Post-Impressionism
3
Tudor
3
Young British Artists (YBA)
3
Art Informel
2
Art Nouveau
2
Auto-Destructive art
2
Direct Carving
2
Euston Road School
2
Neo-Classicism
2
Neo-Plasticism
2
Newlyn School
2
New Sculpture
2
Optical Art
2
Pop Art
2
Post Painterly Abstraction
2
Regional
2
Situation
2
Situationist International
2
Abstract Expressionism
1
Actionism
1
Arte Nucleare
1
Artist Placement Group
1
Artists International Association
1
Bauhaus
1
Cobra
1
Der Blaue Reiter
1
De Stijl
1
Early Stuart
1
English-born, working in the Netherlands
1
Expressionism
1
Fauvism
1
Fluxus
1
French-trained, working in Britain
1
Futurism
1
German Expressionism
1
Grand Tour
1
Independent Group
1
Italian-trained, working in Britain
1
Merz
1
Metaphysical Art
1
Modern Moral Subject
1
Modern Realism
1
Neo-Impressionism
1
Neue Wilden
1
New British Sculpture
1
Norwich School
1
Nouveau Réalisme
1
Orientalist
1
Origine group
1
Post-Reformation
1
(Other)
9
The artists included in the most movements are some of the grand elders of British 20th Century art. Being in an art movement doesn't improve gender representation.
The most movements are post-1945. Performance art is more popular than Conceptual art, which is interesting given public discussion of state art funding in the UK. “Netherlands-trained, working in Britain” clearly isn't a movement, as with the birth dates the movement name field doesn't always describe a movement per se.
Let's break down gender by movement.
table(artist.movements$movement.era.name, artist.movements$artist.gender)
Female Male
16th and 17th century 5 0 42
18th century 0 0 27
19th century 0 0 63
20th century 1900-1945 0 9 86
20th century post-1945 0 18 106
movement.gender <- table(artist.movements$movement.name, artist.movements$artist.gender)
movement.gender <- movement.gender[order(movement.gender[, 2], decreasing = TRUE),
]
movement.gender[1:20, ]
Female Male
Performance Art 0 5 9
Feminist Art 0 4 0
Abject art 0 3 3
Abstraction-Création 0 2 5
Constructivism 0 2 7
St Ives School 0 2 6
Body Art 0 1 7
Camden Town Group 0 1 3
Kinetic Art 0 1 4
Minimalism 0 1 4
Rayonism 0 1 0
Seven and Five 0 1 3
Surrealism 0 1 6
Unit One 0 1 5
Young British Artists (YBA) 0 1 2
Abstract Expressionism 0 0 1
Actionism 0 0 1
Aesthetic Movement 0 0 4
Arte Nucleare 0 0 1
Art Informel 0 0 2
Representation improves slightly over time. Unsurprisingly, feminist art has more female than male artists represented. Abject art is a tie, and there are more than half as many female performance artists as male ones.
Artworks
There are
Error in eval(expr, envir, enclos) : object 'artwork.title' not found
artworks in the dataset.
summary(artwork[c("artist", "title", "dateText")])
artist title
Turner, Joseph Mallord William:39389 [title not known]: 3659
Jones, George : 1046 [blank] : 3520
Moore, Henry, OM, CH : 623 Blank : 1995
Daniell, William : 612 [no title] : 1883
Beuys, Joseph : 578 Untitled : 627
British (?) School : 388 Mountains : 540
(Other) :26493 (Other) :56905
dateText
date not known: 5993
1819 : 2908
1801 : 1331
c.1830–41 : 1194
1833 : 1171
1831 : 1170
(Other) :55362
summary(artwork$year)
Min. 1st Qu. Median Mean 3rd Qu. Max. NA's
1540 1820 1830 1870 1950 2010 5397
JMW Turner has tens of thousands more works in the collection than the next nearest artist. Is this a glitch? No, it's due to the fact that the Tate holds the Turner Bequest of around 30,000 works on paper.
What are artworks titled? Usually Untitled, or simply no title. “Mountains” appears to be the most popular actual title, although if we stemmed or otherwise abstracted and clustered the titles other popular ones might emerge.
The most popular years for artworks are in the early 1800s. This, and possibly the titles, are again attributable to Turner. It would probably be productive to remove Turner's works on paper (or more simply just remove all Turner's works) from the dataset and try again, as his presence is clearly skewing the analysis.
Both artists and artworks have movements. Let's look at how artwork movements differ from artists.
summary(artwork.movements)
artwork.id
Min. : 22
1st Qu.: 6050
Median : 11496
Mean : 21962
3rd Qu.: 21954
Max. :114918
artwork.title
[no title] : 674
[title not known] : 169
Untitled : 116
Insertions into Ideological Circuits 2: Banknote Project: 54
Walking the Dog : 39
Exquisite Corpse : 37
(Other) :5894
year artwork.medium movement.era.id
Min. :1545 Screenprint on paper:1301 Min. : 8
1st Qu.:1920 Oil paint on canvas :1113 1st Qu.:290
Median :1963 Lithograph on paper : 527 Median :415
Mean :1936 Etching on paper : 393 Mean :327
3rd Qu.:1973 Graphite on paper : 205 3rd Qu.:415
Max. :2009 Bronze : 113 Max. :415
NA's :303 (Other) :3331
movement.era.name movement.id movement.name
16th and 17th century : 177 Min. : 293 British Pop : 846
18th century : 469 1st Qu.: 363 Conceptual Art : 445
19th century :1004 Median : 433 Pre-Raphaelite : 405
20th century 1900-1945:1156 Mean : 2421 St Ives School : 400
20th century post-1945:4177 3rd Qu.: 1683 School of London: 373
Max. :18626 Neo-Classicism : 310
(Other) :4204
summary(artwork.movements$movement.name)[1:20]
British Pop Conceptual Art
846 445
Pre-Raphaelite St Ives School
405 400
School of London Neo-Classicism
373 310
Pop Art Young British Artists (YBA)
246 226
Independent Group Constructivism
178 147
British War Art Minimalism
141 138
Victorian/Genre Neo-Expressionism
125 111
Neo-Romanticism Abstract Expressionism
107 102
Surrealism Geometry of Fear
96 84
Performance Art British Surrealism
81 75
summary(artwork.movements$movement.era.name)
16th and 17th century 18th century 19th century
177 469 1004
20th century 1900-1945 20th century post-1945
1156 4177
Pop and Pre-Raphaelitism gain in popularity, but Conceptualism and Surrealism are still popular.
Subjects
Each artwork is tagged with descriptions of the subjects that it depicts. Subjects have levels, from general to specific, which I've named the category, subcategory and subject. We can group the subjects of artworks by artists and movements to find out what their characteristic subjects were.
summary(artwork.subjects[c("artwork.title", "artwork.dateText", "category.name",
"subcategory.name", "subject.name")])
artwork.title artwork.dateText category.name
[title not known]: 13992 date not known: 29732 nature :76796
[no title] : 8146 1819 : 12948 places :60314
Untitled : 2148 1833 : 5865 architecture:57507
Mountains : 899 1801 : 5023 people :52820
Shipping : 462 1831 : 4817 objects :22990
Walking the Dog : 412 1840 : 4498 society :20032
(Other) :316957 (Other) :280133 (Other) :52557
subcategory.name subject.name
landscape : 32722 hill : 9737
adults : 22048 wooded : 8223
townscapes, man-made features: 21272 man : 8164
seascapes and coasts : 12202 figure : 8118
water: inland : 11839 townscape, distant: 7916
countries and continents : 11704 England : 7661
(Other) :231229 (Other) :293197
summary(artwork.subjects$category.name)[1:20]
abstraction architecture
13304 57507
emotions, concepts and ideas history
11583 1948
interiors leisure and pastimes
2467 3446
literature and fiction nature
2977 76796
objects people
22990 52820
places religion and belief
60314 4376
society symbols & personifications
20032 6242
work and occupations <NA>
6214 NA
<NA> <NA>
NA NA
<NA> <NA>
NA NA
summary(artwork.subjects$subcategory.name)[1:16]
landscape adults
32722 22048
townscapes, man-made features seascapes and coasts
21272 12202
water: inland countries and continents
11839 11704
UK countries and regions cities, towns, villages (non-UK)
10800 10160
non-representational transport: water
9583 9537
actions: postures and motions UK counties
9055 8867
features military
8694 7091
formal qualities UK cities, towns and villages
6934 6695
summary(artwork.subjects$subject.name)[1:20]
hill wooded man
9737 8223 8164
figure townscape, distant England
8118 7916 7661
river woman mountain
7549 7303 5932
castle bridge rocky
5298 3769 3759
group coast Italy
3694 3545 3509
boat, sailing townscape colour
3381 3157 2859
sea tower
2810 2803
The summary looks like Turner is skewing the results again. The subjects are mostly English landscape of the early 19th Century. But the categories are led by more non-representional subjects, before the subcategories and subjects return to landscape. People (“adults”, “man”, “woman”) emerge as popular subjects as well, indeed they are the second largest subcategory.
summary(artist.subjects[c("artist.name", "category.name", "subcategory.name",
"subject.name")])
artist.name category.name
David Lucas :1653 nature :991
Jacques Lipchitz : 301 places :551
Colin Lanceley : 181 people :471
Bernard Leach : 104 architecture:345
Langlands & Bell (Ben Langlands and Nikki Bell): 78 abstraction :275
Linder : 65 objects :256
(Other) :1091 (Other) :584
subcategory.name subject.name
landscape : 287 figure : 157
adults : 250 England : 144
weather : 198 wooded : 138
non-representational : 186 cloud : 99
UK countries and regions: 151 man : 84
animals: mammals : 145 geometric: 74
(Other) :2256 (Other) :2777
summary(artist.subjects$category.name)[1:20]
abstraction architecture
275 345
emotions, concepts and ideas history
132 16
interiors leisure and pastimes
18 36
literature and fiction nature
36 991
objects people
256 471
places religion and belief
551 70
society symbols & personifications
153 51
work and occupations <NA>
72 NA
<NA> <NA>
NA NA
<NA> <NA>
NA NA
summary(artist.subjects$subcategory.name)[1:16]
landscape adults
287 250
weather non-representational
198 186
UK countries and regions animals: mammals
151 145
UK counties townscapes, man-made features
129 118
UK cities, towns and villages water: inland
118 99
formal qualities from recognisable sources
92 89
seascapes and coasts actions: postures and motions
66 62
transport: water residential
57 49
summary(artist.subjects$subject.name)[1:20]
figure England wooded cloud man
157 144 138 99 84
geometric woman Suffolk hill colour
74 62 58 52 47
cow river horse rain ceramics
40 38 37 35 32
monochromatic River Stour Essex sunbeam farmland
29 28 27 27 26
The results from artist subjects don't differ appreciably from the artwork ones. We wouldn't expect any difference, but some artworks have more than one artist or have none, so this introduces variations.
summary(movement.subjects[c("movement.name", "era.name", "artwork.title ", "category.name",
"subcategory.name", "subject.name")])
Error: undefined columns selected
summary(movement.subjects$category.name)[1:20]
abstraction architecture
4977 2831
emotions, concepts and ideas history
4486 578
interiors leisure and pastimes
619 821
literature and fiction nature
858 5634
objects people
7516 11828
places religion and belief
2635 1296
society symbols & personifications
4097 1843
work and occupations <NA>
1568 NA
<NA> <NA>
NA NA
<NA> <NA>
NA NA
summary(movement.subjects$subcategory.name)[1:16]
adults non-representational
4077 3651
formal qualities actions: postures and motions
2500 2138
clothing and personal effects inscriptions
1602 1402
from recognisable sources body
1326 1170
landscape universal concepts
1161 1049
emotions and human qualities social comment
937 913
townscapes, man-made features furnishings
898 868
reading, writing, printed matter features
820 735
summary(movement.subjects$subject.name)[1:20]
woman man figure geometric
1854 1649 1197 1191
colour photographic irregular forms head / face
1111 920 563 531
standing England sitting female
519 503 497 476
printed text text group gestural
443 428 411 389
wooded landscape man-made sea
333 305 276 243
“Insertions into Ideological Circuits 2: Banknote Project” has multiple json records with multiple movements and topics in each, so it's over-represented here. The subjects are still similar, although with more photography.
Conclusions
What can we conclude from this? The collection is dominated by male British pop artists, more from England than from Scotland or the rest of the UK. The subjects of artworks are what one would expect: landscape, human figures, abstracts. The Turner Bequest skews some of the data, and this should be accounted for or addressed in analysis. A few other artworks also skew some results.
Next we'll look more closely at artistic movements with some data visualizations.
