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# Aggregations in Python

How to use aggregates in Python with Plotly.

#### 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
plotly.__version__
```
Out[1]:
`'2.2.3'`

#### Introduction¶

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

off.init_notebook_mode(connected=False)

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)
```