Skip to main content
SimilarExport ZIP
100%

Eri Kim - Transforming Data

✓ Published0🌍 Public
EEri Kim
Last edited Mar 17, 2023
Created on Jan 28, 2023
Forked from Transforming Data

This visualization presents a histogram of artworks from the MoMA collection, grouping them by medium and sorting the counts in descending order. It processes the CSV data with `flatGroup` and `map` to aggregate records, then displays the resulting summary as a JSON object. The code uses D3 v7 for data parsing and manipulation, and fetches country codes from the RestCountries API.

AI-generated description

Using the MoMA Dataset, I processed it so that it can be used to implement a visualization that matches one of my sketches (Histogram by Medium). I used flatGroup() and map() functions. After grouping and mapping, I sorted the data by count in descending order.

MIT Licensed

Similar vizzes

Loading thumbnail…

Eri Kim - First Viz Iteration

This streamgraph visualizes how the use of different art mediums changes over time, based on MoMA collection data. The chart displays ten medium categories, such as lithograph, ink, and graphite, as flowing bands across a timeline. The visualization uses D3's `stack` with a silhouette offset, `area` shapes, and `schemeTableau10` colors. The code processes a CSV file using `csvParse` and aggregates data by date and medium, with the state managed through React-style props in a Vue framework.

EEri Kim
78% match
Loading thumbnail…

Eri Kim - First Viz

This stacked bar chart from Eri Kim’s first visualization shows the total number of artworks for the top ten most common mediums, broken down by year across the first 20 years of the collection. Each colored segment represents a specific medium, with a legend identifying each. The chart is built using D3 version 7, leveraging `d3.stack` for stacking, `d3.scaleBand` and `d3.scaleLinear` for axes, and `d3.schemeTableau10` for the categorical color palette. Data is loaded and parsed from a local CSV file.

EEri Kim
75% match
Loading thumbnail…

Bar Graph with Dropdown Menu of Artists

A dropdown menu of artists filters a bar graph showing the number of MoMA artworks per year for the selected artist. Hovering highlights bars in orange with a tooltip. The visualization loads data from a CSV using D3 v7's `csvParse`, builds the menu with D3 selections, and computes annual counts via `d3.rollup`. Additional buttons open a thumbnail gallery or histogram, though the code for the latter is incomplete.

EEri Kim
73% match
Loading thumbnail…

MoMA Streamgraph

This visualization displays the most used mediums in MoMA’s collection over time as a streamgraph, with each colored layer representing a medium like Lithograph or Ink. The chart uses d3.stack with a wiggle offset to create the flowing shapes, applies smoothing via array-blur, and labels areas using the d3-area-label library. Hovering an area highlights it with a white border, and a legend helps identify smaller layers. Data comes from a CSV file of MoMA artworks, parsed and scaled by year.

EEri Kim
72% match
Loading thumbnail…

Loading MoMA Data

This example demonstrates the initial step of loading and parsing the Museum of Modern Art’s collection dataset using d3.csvParse within a Vue-based application. It fetches the CSV file and converts raw text into an array of objects, transforming numeric fields like dimensions and dates (negating BeginDate and EndDate to represent years) and converting zero values to null. The parsed data is then displayed as raw JSON in a pre element using D3’s selection and join methods.

EEri Kim
71% match
Loading thumbnail…

Line Chart

This line chart shows the number of artworks per year in the MoMA collection, with time on the x-axis and artwork count on the y-axis. The chart uses the MoMA dataset, parsing dates with `d3.timeParse` and scaling them with `d3.scaleTime`. Data is aggregated using `flatGroup` and sorted by year before being rendered with a `line` generator. The visualization is built with D3 v7 within a Vue framework.

EEri Kim
71% match
Loading thumbnail…

Tree Map: MoMA Dataset

A treemap visualizes the distribution of artist nationalities in the MoMA dataset, with each rectangle's area proportional to the count of artists from that country. Hovering over a rectangle displays a tooltip showing the nationality and its exact count, while the color scale assigns a distinct hue to each nationality. The visualization uses D3 v7 APIs including `d3.treemap`, `d3.hierarchy`, and `d3.scaleOrdinal` with `schemeTableau10`. The code processes an in-memory array of nationality counts, renders rectangles via SVG, and manages the tooltip through D3's `select` method. The layout is computed using the default treemap algorithm with a padding of 4 pixels.

EEri Kim
71% match
Loading thumbnail…

Fork of Pie Chart with Interactive Color Legend

This pie chart visualizes the distribution of artwork classifications in the MoMA dataset, with each slice sized by the count of works in a department. Hovering over a slice reveals a tooltip showing the department name and count, while hovering over the interactive color legend dims all non-matching slices to highlight the selected category. The visualization uses d3.pie, d3.arc, and d3.scaleOrdinal with schemeTableau10 for coloring, built with Vue and rendered as animated SVG. Data is loaded from a CSV and aggregated using d3.flatGroup.

EEri Kim
70% match