Creating a Dashboard with Custom Plots

Learning Objectives

The learning objectives of this article is to learn how to:

Create a custom plot dashboard
Where to find dashboards in the UI
Basic API usage to register plots

Introduction

Abacus allows you to generate and register plots within our UI. Using this method, you can create a custom dashboard that looks like below:

Custom Dashboard Example

Navigating the UI

Create a project
Navigate to the EDA > Plots tab within the project
Click Create New Dashboard button

Create New Dashboard Button

Provide the dashboard name. Click Add Plot button after creation:

Add Plot Button

Provide the plot's title and function name. Once you click the Create Plot button, you'll be redirected to the embedded notebook to create the plotting function and register it within the dashboard. More details are provided in the API approach.

Create Plot Button

Alternatively, you can select a function created earlier. In that case, you have to provide required arguments to the predefined function.

Select Function

Please note that not all projects allow for a dashboard to be created. “Predictive Modeling” is the essential project type that supports dashboard creation.

Basic API’s required

Create a project:

from abacusai import ApiClient, ApiException
client = ApiClient()
project_name = 'sales_over_time_test_ak'
project = client.create_project(name=project_name, use_case='PREDICTING')

Create a dashboard:

graph_dashboard = client.create_graph_dashboard(project_id=project.id, name=project_name)

Define a plot function. The example function below takes as an input feature group, aggregates sales by the day of week and promo indicator. The column names can be used as the function arguments as well.

function_name = 'sales_over_time'
def sales_over_time(df):
    import plotly.express as px
    # bring data into appropriate format
    df = df.groupby(['DayOfWeek', 'Promo']).agg({'Sales': sum}).reset_index()
    df = df.sort_values(by = ['DayOfWeek', 'Promo'])
    # make a plotly animation plot
    fig = px.scatter(df, x="DayOfWeek", y="Sales", color = "Promo")
    # adjust labels
    fig.update_layout(title='Sales variability by Day of Week & Promo')
    fig.update_xaxes(title_text='DayOfWeek',title_standoff=0)
    return fig

For creating a python function, we need to specify the function variable mappings. They can have literal types and values. FEATURE_GROUP is one of the types and its value points to a table name in the example below.

function_variable_mappings = [{'name': 'df', 'value': 'store_sales_data_test', 'variable_type': 'FEATURE_GROUP', 'is_required': True}]

try:
    python_function = client.create_python_function(
        name=function_name,
        function_name=function_name,
        source_code=sales_over_time,
        function_variable_mappings=function_variable_mappings,
        function_type='plotly_fig')
except ApiException as error:
    if error.exception == 'AlreadyExistsError':
        python_function = client.describe_python_function(name=function_name)
    else:
        raise error

client.add_graph_to_dashboard(python_function_id=python_function.python_function_id, graph_dashboard_id=graph_dashboard.id, function_variable_mappings=function_variable_mappings, name=function_name)