HawkinsJM

@HawkinsJM·4 public vizzes

Gist 379b1fa0356b03ac6d9319f157a229a8

This example uses pandas and seaborn to explore a dataset of user study schedules and referral scores, first loading the CSV into a DataFrame and previewing its structure. The visualization reveals the relationship between whether users follow a study schedule, their note-taking behavior, and their referral scores. Using matplotlib and seaborn with a white background and deep palette, the code generates statistical plots to compare referral scores across binary study-schedule and note-taking groups, highlighting patterns in user engagement. The analysis relies on the pandas DataFrame operations and seaborn’s plotting functions to summarize the data, though the specific chart type is not shown in the provided cells.

Apr 7, 2018

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Basic Scatter Plot

This scatter plot shows the relationship between average class size and in-district expenditures per pupil for Massachusetts public schools in 2017, using data from the MA_Public_Schools_2017.csv file. Each circle represents a school, with position determined by those two quantitative variables. The chart is rendered in SVG via D3 v4, using scale functions for the axes and a simple circle-based encoding. The visualization highlights the distribution and potential correlation between school spending and class size, with the grid of points making outliers and clusters visible at a glance.

Dec 18, 2017

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Scatter Plot with Menus

This interactive scatter plot, built with D3 v4, Redux, and d3-component, visualizes the classic Auto MPG dataset from the UCI Machine Learning Repository. Users can select which attributes to plot on the X and Y axes, as well as which attribute determines the color of the points, via dropdown menus. The visualization animates transitions smoothly when the selection changes, demonstrating how Redux can manage state changes that drive D3 updates without a React layer.

Dec 17, 2017

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Basic Scatter Plot

This basic scatter plot visualizes the relationship between two variables from the MA_Public_Schools_2017.csv dataset, with each point representing a school. Using D3 v4 with SVG rendering, the plot maps one metric to the x-axis and another to the y-axis, with axes automatically scaled from the data. The chart is intentionally minimal, focusing on showing the distribution and correlation of the selected variables across schools. The code from HawkinsJM loads the CSV and uses D3 scales to position circles, providing a straightforward example of how to construct a basic scatter plot with D3.

Dec 17, 2017