MoMA Tour
By Ajinkya Shinde in R
June 16, 2018
Foreward
MoMA(Mueseum of Modern Art’s) is just not any other art museum but one of the most influential mueseums of modern art in the world. Most of the artwork collections comprise of the modern and contemporary arts discussing the mere essence of social, political and several other issues. The MoMA dataset hosts the collection: 123,919 pieces, including 1,656 sculptures, 28,411 photographs, 11,420 drawings, 1,936 films and — most important for our tour today — 2,229 paintings.
This collection has been further cleansed and an aggregated version “artworks-cleansed.csv” has been formed to perform further analysis.
1. Relevant R Code
2. Description of the TYPE of graph.
The graph is a bar chart with the geom_smooth line showing the trend line.
3. Description of the DATA you used
The data refers to the moma dataset. In this graph, the final data frame is f_moma2(final moma). The quantitative variable is the count of number of paintings created.The qualitative variable is the year during which the paintings were created
4. Description of the AUDIENCE you are aiming for
The audience over here is someone who wants to see the paintings done by women over the years
5. Representation Description:
This graph shows the count of number of paintings done by women across the years.
6. How to read it & What to look for
For year-gap on x-axis, read the number of paintings created during that period.
Major Highlights It seems that Women actually painted more paintings during the year 1960-2000. Also,the highest number of paintings(15) around 1985-1990.
7. Presentation tips
Using scale_x_continuous and scale_y_continuous, the padding at the starting and ending of the x-axis has been removed. The color scheme used is in relation to the artist-gender(female). The trend line has been added to get the sense of overall increase/decrease using geom_smooth
8. Variations and alternatives
This plot can be improved by including the Male gender to see how the Female’s performed wrt Male artists.
9. How I created it
I formulated the question of what exactly I want: I have to see the diversity in the paintings created as per artist’s gender. First, I filtered the data-set on Male and Female. But due to large number of overlapping points , the stacked bar chart wasn’t the perfect fit. So, I decided to go with only one gender. Due to uncontinuity in the year column, the geom_line wasn’t the perfect fit, so decided to go with geom_col