Aggregations in Python/v3

How to use aggregates in Python with Plotly.

Note: this page is part of the documentation for version 3 of, which is not the most recent version.
See our Version 4 Migration Guide for information about how to upgrade.
The version 4 version of this page is here.

New to Plotly?

Plotly's Python library is free and open source! Get started by downloading the client and reading the primer.
You can set up Plotly to work in online or offline mode, or in jupyter notebooks.
We also have a quick-reference cheatsheet (new!) to help you get started!

Version Check

Plotly's python package is updated frequently. Run pip install plotly --upgrade to use the latest version.

In [1]:
import plotly


Aggregates are a type of transform that can be applied to values in a given expression. Available aggregations are:

Function Description
count Returns the quantity of items for each group.
sum Returns the summation of all numeric values.
avg Returns the average of all numeric values.
median Returns the median of all numeric values.
mode Returns the mode of all numeric values.
rms Returns the rms of all numeric values.
stddev Returns the standard deviation of all numeric values.
min Returns the minimum numeric value for each group.
max Returns the maximum numeric value for each group.
first Returns the first numeric value for each group.
last Returns the last numeric value for each group.

Basic Example

In [2]:
import plotly.offline as off


subject = ['Moe','Larry','Curly','Moe','Larry','Curly','Moe','Larry','Curly','Moe','Larry','Curly']
score = [1,6,2,8,2,9,4,5,1,5,2,8]

data = [dict(
  type = 'scatter',
  x = subject,
  y = score,
  mode = 'markers',
  transforms = [dict(
    type = 'aggregate',
    groups = subject,
    aggregations = [dict(
        target = 'y', func = 'sum', enabled = True),

off.iplot({'data': data}, validate=False)