What is new in 4.7.0#
Time Series Plotting
Support for Python
time
anddate
objects.Support for timezone-aware
datetime
objects and Pandas/PolarsSeries
.
See example notebook.
Native support for PNG and PDF exports
Exporting to PNG and PDF formats now uses the
ImageMagick
library bundled with Lets-Plot Python wheels and available out-of-the-box.This replaces the previous dependency on the
CairoSVG
library and comes with improved support for LaTeX labels rasterization.geom_sina() Geometry
See example notebook.
geom_text_repel() and geom_label_repel() Geometries
See example notebook.
waterfall_plot() Chart
Annotations support via
relative_labels
andabsolute_labels
parameters.See example notebook.
Support for combining waterfall bars with other geometry layers.
See example notebook.
Continuous Data on Discrete Scales
Continuous data when used with discrete positional scales is no longer transformed to discrete data. Instead, it remains continuous, allowing for precise positioning of continuous elements relative to discrete ones.
See: example notebook.
Tip
New way of handling continuous data on discrete scales could potentially break existing plots. If you want to restore a broken plot to its original form, you can use the as_discrete()
function to annotate continuous data as discrete.
Plot Layout
The default plot layout has been improved to better accommodate axis labels and titles. Also, new
theme()
optionsaxis_text_spacing
,axis_text_spacing_x
, andaxis_text_spacing_y
control spacing between axis ticks and labels.See the plot layout diagram showing various layout options and their effects on plot appearance.
And More
See CHANGELOG.md for a full list of changes.
Recent Updates in the Gallery#

















Change Log#
See CHANGELOG.md for other changes and fixes.