Skip to main content
SimilarExport ZIP
100%

Human brain weight dataset

✓ Published3🌍 Public
Llingjizhu@gmail.com
Last edited Jan 23, 2024
Created on Jan 22, 2024

This example visualizes correlations between gender, age range, head size, and brain weight from a Kaggle human brain weight dataset. It parses the CSV data, converting HeadSize and BrainWeight to numeric values, then displays the first data record as formatted JSON in a pre element with large font size. The code uses the imported data array and dynamically updates the container's innerHTML to show the parsed categorical and quantitative attributes.

AI-generated description

The Human Brain Weight Dataset, loaded and parsed as CSV.

Gender and AgeRange are categorical attributes. In Gender: "1" represents male, "2" represents female. In Age Range: "1" represents >=18 years old, "2" represents <18 years old. HeadSize (cm^3) and BrainWeight (gram) are quantitative attributes.

Task

  • Visualize correlation between gender, age range, head size, and brain weight.
MIT Licensed

Similar vizzes

Loading thumbnail…

Human Brain Weight

This scatter plot visualizes the relationship between head size and brain weight for individual data points. Each circle represents one sample, with position determined by head size on the x-axis and brain weight on the y-axis, using a light gray background and semi-transparent points to reveal overlapping data. The visualization is built with D3’s `scaleLinear` for axis scaling and `xAxis`/`yAxis` functions, along with axis labels from the `@curran/axis-labels` library. Data comes from the Human Brain Weight dataset, with filtering applied to remove rows containing missing numeric values.

Llingjizhu@gmail.com
81% match
Loading thumbnail…

Mass/Height

This visualization prints a summary of a dataset containing the mass and height of 500 people, along with their gender, sourced from Kaggle. It loads the CSV file using D3’s `csv` function, then displays the row count, column count, and estimated file size in kilobytes via `csvFormat`. The interface presents the first 100 rows as pre-formatted JSON text on a black background with green terminal-style text. The code relies on D3 v5’s `select`, `append`, and `text` methods to build the output without any graphical chart.

Cceltic660
63% match
Loading thumbnail…

my scatter plot

This scatter plot visualizes the relationship between weight and height for 500 individuals, with points colored by gender (orange for female, teal for male) based on data from a Kaggle CSV file. The visualization uses D3 v5’s `scaleLinear`, `axisLeft`, and `axisBottom` APIs to map the quantitative axes, rendering SVG circles with a radius of 5 pixels. Axis grid lines and text labels are styled via CSS, while the chart displays “PESO (g)” on the x-axis and “ALTURA (cm)” on the y-axis.

JJefferson Abreu
63% match
Loading thumbnail…

Weigh/Height Comparison on Gender

This scatter plot compares weight and height across genders, with each red circle representing an individual’s measurements. The chart uses D3 v5’s `scaleLinear`, `axisBottom`, and `axisLeft` to construct axes and gridlines, while `csv` loads the gender weight and height dataset from VizHub. The SVG rendering emphasizes correlation patterns, though gender differentiation is not visualized despite the title. Data preprocessing converts string values to numbers via unary plus operations before plotting.

Cceltic660
62% match
Loading thumbnail…

Weigh/Height Comparison on Gender

This scatter plot compares weight and height across genders, with each red circle representing an individual’s measurements. The chart uses D3 v5’s `scaleLinear`, `axisBottom`, and `axisLeft` to construct axes and gridlines, while `csv` loads the gender weight and height dataset from VizHub. The SVG rendering emphasizes correlation patterns, though gender differentiation is not visualized despite the title. Data preprocessing converts string values to numbers via unary plus operations before plotting.

Cceltic660
62% match
Loading thumbnail…

Weigh/Height Comparison on Gender

This scatter plot compares height and weight across genders, with each circle representing an individual and color-coded by gender. The visualization uses D3 v5’s `scaleLinear`, `axisBottom`, and `axisLeft` to map data from a CSV file onto an SVG canvas. Points are rendered as semi-transparent red circles, with axes labeled “Height” and “Weight” and a title “Height/Weight.” The code loads data from VizHub, parses numeric fields, and applies margins and tick formatting to create a clean, readable chart.

Cceltic660
61% match
Loading thumbnail…

Weigh/Height Comparison on Gender

This scatter plot visualizes the relationship between height and weight across genders using a dataset from UCI Machine Learning Repository. The visualization displays individual data points as semi-transparent red circles, with height mapped to the x-axis and weight to the y-axis using D3 v5’s `scaleLinear` functions. The code employs D3’s `csv` loader to fetch external data, `axisBottom` and `axisLeft` for tick marks, and SVG circle elements for rendering. Axes labels and a title are added to clarify the quantitative comparisons shown.

Cceltic660
61% match
Loading thumbnail…

Mass/Height

This example prints a summary of a dataset containing the mass and height of 500 people, along with their gender. It displays the row and column counts, the estimated file size in kilobytes, and the first 100 rows as formatted JSON. The code loads the CSV from a Kaggle-sourced URL using `d3.csv`, then uses `select` and `append` to render the text into `<pre>` elements, with `csvFormat` calculating the data size.

Cceltic660
61% match