Skip to main content
100%

Create beautiful square figures with big labels and the correct number of ticks

✓ Published0🌍 Public
Aabehmiel
Last edited Oct 31, 2017
Created on Oct 31, 2017

This example demonstrates how to create square matplotlib figures with large axis labels and precisely controlled tick counts. The `create_figure` function builds a figure with a fixed square size and uses `MaxNLocator` to set the number of x-axis ticks, while `format_axes` applies custom numeric formatting via `FormatStrFormatter` and independently controls tick counts and label sizes for both axes. The code relies on matplotlib’s `figure`, `add_subplot`, and `tick_params` APIs to produce clean, publication-ready plots.

AI-generated description

Similar vizzes

Loading thumbnail…

Matplotlib subplots with TeX rendering: good figure baseline for publications

This example creates a publication-quality figure with two stacked Matplotlib subplots, each displaying four labeled data series with distinct marker styles. The code enables TeX rendering for bold mathematical text throughout the figure, including axis labels, titles, and annotations, while a shared y-axis label spans both plots. It uses the `subplot` API to add axes, `plot` with custom markers, and `set_position` to adjust subplot extents. The script saves the result as a PNG file using `savefig` and applies a serif font family for a polished academic appearance.

Aabehmiel
64% match
Loading thumbnail…

matplotlib basic

This example shows a nearly empty matplotlib figure with a single axes object, demonstrating the basic setup of a plot canvas. The code creates a 10x10 figure and adds an axes region with specified margins, but does not plot any data or set axis labels, limits, or legends. The `ax.plot()` call is made without arguments, leaving the axes blank. The script uses `matplotlib.pyplot.figure` and `fig.add_axes` to define the layout, with commented-out lines for `set_ylim`, `set_xlim`, and `legend` indicating potential future customization.

Aandyreagan
61% match
Loading thumbnail…

Axis tick marks

This example demonstrates how to control the placement of tick marks on a chart axis using the D3.js library. It shows a single horizontal axis with four specified tick values (0, 50, 60, 100) rendered along a linear scale that maps the domain 0–100 to a pixel range of 0–400. The code constructs the axis using `d3.scale.linear()`, `d3.svg.axis()`, and the `tickValues()` method, then appends it to an SVG element. The axis is positioned via a translate transform, with CSS styling providing black strokes for the axis line and tick marks.

RRobinL
61% match
Loading thumbnail…

Responsive Axes with value labels

This example demonstrates responsive axes that maintain a consistent tick mark density as the visualization is resized. It shows a line chart with labeled X and Y axes inside a grey plotting area, where the number of ticks adjusts dynamically to the chart's dimensions. The code uses D3’s `scaleLinear`, `axisBottom`, and `axisLeft` functions, along with a `ResizeObserver` to track container size changes. Tick count is calculated by dividing the inner axis length by a fixed density value (50 pixels), ensuring readable spacing across varied widths and heights.

MMaarten Snels
60% match
Loading thumbnail…

Fork of D3 Axes - Tick Label Formatting

This example demonstrates how to format tick labels on a D3.js axis using custom tick formatting. A linear scale maps a domain of 0 to 100 to a pixel range, and an axis bottom is configured with increased tick padding and size. The axis is customized by limiting the number of ticks to four and applying a custom `tickFormat` function that appends a percent sign to each value. The resulting SVG renders the axis with labeled ticks showing the original data values with a “%” suffix.

SSubhendu Karmakar
60% match
Loading thumbnail…

Tick Format

This example compares three ways to format tick labels on linear axes, each rendered as an SVG axis via `d3.axisLeft`. The left axis uses `scale.tickFormat` with an SI-prefix type (`"s"`), producing a consistent prefix across all ticks. The middle axis applies `d3.format(".0s")` directly, causing variable precision and prefix per label. The right axis uses `d3.formatPrefix(".1", 1e6)` to enforce a fixed mega-prefix, demonstrating manual control over SI formatting. The three axes share the same domain from -1e6 to 2e6.

Mmbostock
60% match
Loading thumbnail…

Density-based Ticks

This example demonstrates how to set tick marks to a fixed pixel density, so the number of ticks adapts to the chart's changing width. The code uses d3.axisBottom and d3.scaleLinear, with the tick count computed as varyingWidth divided by a constant xPixelsPerTick. A sinusoidal animation continuously adjusts the inner width, and requestAnimationFrame re-renders the axis in an SVG. The visualization shows the axis label and tick marks updating in real time, illustrating a responsive approach for resizable charts.

CCurran Kelleher
59% match
Loading thumbnail…

Fork of Responsive Axes - with large values

This example demonstrates a responsive scatterplot-like visualization with axes that maintain consistent tick mark density when the chart is resized. It shows time-series data on the x-axis and large numeric values on the y-axis, ranging up to 97,582, with axis labels for both dimensions. The implementation uses D3 v7, leveraging `scaleLinear`, `scaleTime`, `axisLeft`, and `axisBottom` to render the axes. A ResizeObserver detects container size changes, and the tick density is dynamically calculated by dividing the inner width and height by user-defined constants. The chart includes a gray inner rectangle as the plotting area.

HHitesh Jangid
58% match