Options for Color Schema
You can modify the colors in the Evidently Dashboards.
By default, Evidently widgets use the red-grey color scheme.
For example, here is how the Data Drift report looks:
Data Drift
To change the colors in the widgets, you can create an object ColorOptions from the evidently.options.color_scheme, replace the values you need, and use it in the options list when you create a dashboard.
from evidently.options import ColorOptions
from evidently.dashboard import Dashboard
from evidently.dashboard.tabs import DataDriftTab
color_scheme = ColorOptions()
color_scheme.primary_color = "#5a86ad"
color_scheme.fill_color = "#fff4f2"
color_scheme.zero_line_color = "#016795"
color_scheme.current_data_color = "#c292a1"
color_scheme.reference_data_color = "#017b92"
iris_data_drift_dashboard = Dashboard(tabs=[DataDriftTab()], options=[color_scheme])
Here is an example of the report with the modified color schema:
To define values for the colors, you can use CSS and Plotly compatible strings. For example:
  • colors names: "blue", "orange", "green"
  • RGB values: #fff4f2, #ee00aa and so on.

Available Options

Here is the list of all color scheme options with the type and meaning of each:
A Variable in the ColorOptions object
Option type
Option description
primary_color
string
A basic color for data visualization. Used by default for all bars and lines in widgets with one dataset. Used as the default for the current data in widgets with two datasets.
secondary_color
string
A basic color to visualize the second dataset in the widgets with two datasets. For example, the reference data.
current_data_color
string
A color for the current data. By default, the primary color is used.
reference_data_color
string
A color for the reference data. By default, the secondary color is used.
color_sequence
array of strings
A set of colors to draw a number of lines in one graph. For example, in the Data Quality dashboard.
fill_color
string
A fill color for areas in line graphs.
zero_line_color
string
A color for the base, zero line in line graphs.
non_visible_color
string
A color for technical, not visible dots or points for better scalability.
underestimation_color
string
A color for the "underestimation" line in the Regression Performance dashboard.
overestimation_color
string
A color for the "overestimation" line in the Regression Performance dashboard.
majority_color
string
A color for the majority line in the Regression Performance dashboard.
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Evidently also provides some sensible alternative default schemas that have been pre-selected for your convenience:
  • 'Solarised'
  • 'Karachi Sunrise'
  • 'Berlin Autumn'
  • 'Nightowl'
To use them, simply import them directly and pass them into your Dashboard options as follows (taking the Berlin Autumn scheme as an example):
from evidently.options import BERLIN_AUTUMN_COLOR_OPTIONS
# import the data as usual...
iris_data_drift_report = Dashboard(
tabs=[DataDriftTab()], options=[BERLIN_AUTUMN_COLOR_OPTIONS]
)
iris_data_drift_report.calculate(
iris_frame[:75], iris_frame[75:], column_mapping=None
)
iris_data_drift_report.save("output.html")
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