Asutosh989

@Asutosh989·5 public vizzes

Gist a193c0f8df23b74a6ac3ff2ac88e7124

This example displays a pandas DataFrame table listing 14 unique superpowers alongside their corresponding heroes, such as Kool-Aid Man’s Thirstokinesis and Dr. Manhattan’s Molecular Dissipation. The code constructs the table from a Python dictionary using `pd.DataFrame.from_dict`, rendering the data as an HTML table with styled headers and row indices. The output is a static, text-based visualization of the one-to-one mapping between each distinct ability and its associated character, with no charts or graphical elements involved.

Mar 4, 2019

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Gist 0f4f8663651c7090f18281e22b275fd4

This visualization maps crime incidents in Denver to their geographic locations. It shows each offense as a point on a city map, colored by its category and located using the provided latitude and longitude coordinates. The map is rendered using Leaflet, with markers positioned programmatically. Crime classifications are distinguished by color, allowing for a spatial overview of incident types across the city.

Jan 30, 2019

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Gist 670c7537c7467ba60116977d68f891af

This example explores superhero abilities by visualizing the presence or absence of various superpowers using a tabular, boolean matrix representation. Each row corresponds to a specific hero character (e.g., 3-D Man, A-Bomb, Abin Sur), while each column represents a distinct superpower or capability, such as Agility, Flight, or Web Creation. The visualization employs a color-coded table, likely rendered interactively within a Jupyter Notebook using the pandas DataFrame and its built-in styling API to implement conditional formatting. This provides an accessible, grid-based overview of which characters possess which powers, facilitating quick comparisons across the dataset.

Jan 29, 2019

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Gist a25625bb83ff3d640f628b2437480ca3

This example presents a tabular view of superhero character attributes from a dataset, displaying fields such as name, gender, eye color, race, height, publisher, and alignment. The notebook uses Python and the pandas library to load and inspect the data, as evidenced by the DataFrame output and the `superhero_info.head()` call. The rendered HTML table shows the first five records, with entries from Marvel Comics, DC Comics, and Dark Horse Comics, including characters like A-Bomb and Abomination, along with their physical and biographical traits.

Jan 11, 2019

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Vega-lite Visualization Example

This stacked bar chart visualizes barley crop yields across multiple varieties, with each bar segmented by the site where the crop was grown. The visualization uses Vega-Lite’s declarative specification to encode variety on the x-axis, aggregated yield on the y-axis, and site as the color channel. Data is loaded from a local JSON file containing individual yield measurements, and the resulting chart is rendered as an SVG. The stacked segments communicate the total yield per variety while also comparing contributions from different agricultural research sites.

Mar 22, 2018