Visualization methods are located in ./dato/ (the dato.plot module). We also support improved (in our opinion) default styles, specified in ./dato/


We have a single main plotting function, Plot, which loosely follows the pandas.DataFrame.plot() syntactical structure, but adds seaborn-like behavior, while being entirely customizable through matplotlib operations.

df >> Plot('a', 'b', kind='line')

While we originally intended the plotting sub-module to simply wrap matplotlib, pandas, and/or seaborn, we very quickly realized a pain point in doing this is that each of these libraries has vastly different syntactical structures (even internally!). We decided to prioritize simplicity over universal inclusion, and therefore ultimately decided on having a single base plotting function.

kind can take the following arguments:

  • scatter

  • line

  • hist

  • bar

  • barh

  • box

We implement each of these as stand-alone Pipeable objects as well (capitalized) -- Scatter, Hist , Bar, etc (Line doesn't exist, as it's the default functionality of Plot).

Although dato.Plot does borrow most of its base syntactical structure from pandas, it does have some extended functionality inherited from seaborn. For example, facet grids (and so the arguments row, col and hue) are natively supported:

df >> Hist('Age', col='Sex', hue='Survived', alpha=0.5)


We currently support three modes: dark_mode, light_mode, and default (which disables all styling), which can be toggled as follows:

import dato'dato_dark')'dato_light')'default')

The colors specifying these styles are located in the dpipe.plot.STYLES dictionary. These default styles are implemented using the mpl_style_decorator function, which can be applied as a decorator before applying the Pipeable decorator.

By default, the above commands apply dato styles globally, but these can be restricted to dato plots only by using the dato_only keyword argument:'dato_dark', dato_only=True)