Cloudy Mountain Plot
Project description
cmplot.py - Cloudy Mountain Plot in python
An informative RDI categorical distribution plot inspired by Violin, Bean and Pirate Plots.
(RDI = Raw data + Descriptive statistics + Inferential statistics)
-
Like Violin plots, it shows smoothed kernel density curves, revealing information which would be hidden in boxplots, for example presence of multiple "peaks" ("modes") in the distribution "mountain".
-
Like Bean plots, it shows the raw data, drawn as a cloud of points. By default all data points are shown but you can optionally control this and limit the display to a subset of the data.
-
Like Pirate plots, it marks confidence intervals (either from Student's T or as Bayesian Highest Density Intervals or as interquantile ranges) for the probable position of the true population mean.
Since by default it does not symmetrically mirror the density curves, it allows immediate comparisions of distributions side-by-side.
Download and installation
cmplot
is pure python code. It has no platform-specific dependencies and should thus work on all platforms. It requires the packages plotly numpy scipy pandas
. The latest version of cmplot
can be installed by typing:
> pip3 install git+git://github.com/g-insana/cmplot.py.git
There is also a version in Julia.
Documentation
Check the online documentation and jupyter notebook for usage and examples at the github page.
Quickstart
>>> import plotly.graph_objects as go
>>> from cmplot import cmplot
#call the cmplot directly inside a plotly Figure function as:
>>> go.Figure(*cmplot(mydataframe,xcol="xsymbol"))
#alternatively get traces and layout as separate variables, so that you can modify them or combine with others before passing them to Figure() function:
>>> (traces,layout)=(cmplot(mydataframe,xcol="xsymbol"))
#[...] do something with traces/layout
>>> go.Figure(traces,layout) #plot it
Copyright
cmplot
is licensed under the GNU Affero General Public License.
(c) Copyright Giuseppe Insana, 2019-
Project details
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.