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first pass at heatmap nb
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‎notebooks/heatmaps.md

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---
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jupyter:
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jupytext:
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notebook_metadata_filter: all
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text_representation:
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extension: .md
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format_name: markdown
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display_name: Python 3
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language: python
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name: python3
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language_info:
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codemirror_mode:
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name: ipython
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version: 3
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file_extension: .py
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mimetype: text/x-python
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name: python
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nbconvert_exporter: python
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pygments_lexer: ipython3
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version: 3.6.7
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plotly:
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description: How to make Heatmaps in Python with Plotly.
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display_as: scientific
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redirect_from: python/heatmap/
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thumbnail: thumbnail/heatmap.jpg
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title: Python Heatmaps | plotly
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v4upgrade: true
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---
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#### New to Plotly?
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Plotly's Python library is free and open source! [Get started](https://plot.ly/python/getting-started/) by downloading the client and [reading the primer](https://plot.ly/python/getting-started/).
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<br>You can set up Plotly to work in [online](https://plot.ly/python/getting-started/#initialization-for-online-plotting) or [offline](https://plot.ly/python/getting-started/#initialization-for-offline-plotting) mode, or in [jupyter notebooks](https://plot.ly/python/getting-started/#start-plotting-online).
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<br>We also have a quick-reference [cheatsheet](https://images.plot.ly/plotly-documentation/images/python_cheat_sheet.pdf) (new!) to help you get started!
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#### Version Check
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Plotly's python package is updated frequently. Run pip install plotly --upgrade to use the latest version.
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```python
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import plotly
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plotly.__version__
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```
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### Basic Heatmap
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```python
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import plotly.plotly as py
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import plotly.graph_objs as go
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import plotly.graph_objects as go
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trace = go.Heatmap(z=[[1, 20, 30],
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fig = go.Figure(data=go.Heatmap(
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z=[[1, 20, 30],
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[20, 1, 60],
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[30, 60, 1]])
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data=[trace]
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py.iplot(data, filename='basic-heatmap')
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[30, 60, 1]]))
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fig.show()
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```
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### Heatmap with Categorical Axis Labels
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```python
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import plotly.plotly as py
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import plotly.graph_objs as go
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import plotly.graph_objects as go
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trace = go.Heatmap(z=[[1, 20, 30, 50, 1], [20, 1, 60, 80, 30], [30, 60, 1, -10, 20]],
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fig = go.Figure(data=go.Heatmap(
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z=[[1, 20, 30, 50, 1], [20, 1, 60, 80, 30], [30, 60, 1, -10, 20]],
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x=['Monday', 'Tuesday', 'Wednesday', 'Thursday', 'Friday'],
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y=['Morning', 'Afternoon', 'Evening'])
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data=[trace]
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py.iplot(data, filename='labelled-heatmap')
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y=['Morning', 'Afternoon', 'Evening']))
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fig.show()
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```
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### Heatmap with Unequal Block Sizes
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```python
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import plotly.graph_objects as go
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import numpy as np
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import plotly.plotly as py
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def spiral(th):
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a = 1.120529
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b = 0.306349
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r = a*np.exp(-b*th)
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return (r*np.cos(th), r*np.sin(th))
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nspiral = 2 # number of spiral loops
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th = np.linspace(-np.pi/13,2*np.pi*nspiral,1000); # angle
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(x,y) = spiral(th)
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# shift the spiral north so that it is centered
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yshift = (1.6 - (max(y)-min(y)))/2
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s = dict(x= -x+x[0], y= y-y[0]+yshift,
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line =dict(color='white',width=3))
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# Build the rectangles as a heatmap
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# specify the edges of the heatmap squares
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phi = ( 1+np.sqrt(5) )/2.
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phi = (1 + np.sqrt(5) )/2. # golden ratio
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xe = [0, 1, 1+(1/(phi**4)), 1+(1/(phi**3)), phi]
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ye = [0, 1/(phi**3),1/phi**3+1/phi**4,1/(phi**2),1]
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ye = [0, 1/(phi**3), 1/phi**3+1/phi**4, 1/(phi**2), 1]
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z = [ [13,3,3,5],
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[13,2,1,5],
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[13,10,11,12],
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[13,8,8,8]
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]
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hm = dict(x = np.sort(xe),
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fig = go.Figure(data=go.Heatmap(
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x = np.sort(xe),
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y = np.sort(ye)+yshift,
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z = z,
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type = 'heatmap',
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colorscale = 'Viridis')
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colorscale = 'Viridis'))
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# Add spiral line plot
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def spiral(th):
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a = 1.120529
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b = 0.306349
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r = a*np.exp(-b*th)
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return (r*np.cos(th), r*np.sin(th))
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theta = np.linspace(-np.pi/13,4*np.pi,1000); # angle
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(x,y) = spiral(theta)
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# shift the spiral north so that it is centered
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yshift = (1.6 - (max(y)-min(y)))/2
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fig.add_trace(go.Scatter(x= -x+x[0], y= y-y[0]+yshift,
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line =dict(color='white',width=3)))
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axis_template = dict(range = [0,1.6], autorange = False,
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showgrid = False, zeroline = False,
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linecolor = 'black', showticklabels = False,
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ticks = '' )
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layout = dict( margin = dict(t=200,r=200,b=200,l=200),
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fig.update_layout(margin = dict(t=200,r=200,b=200,l=200),
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xaxis = axis_template,
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yaxis = axis_template,
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showlegend = False,
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width = 700, height = 700,
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autosize = False )
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figure = dict(data=[s, hm],layout=layout)
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py.iplot(figure, filename='golden spiral', height=750)
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fig.show()
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```
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### Heatmap with Datetime Axis
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```python
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import plotly.graph_objects as go
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import datetime
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import numpy as np
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import plotly.plotly as py
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import plotly.graph_objs as go
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programmers = ['Alex','Nicole','Sara','Etienne','Chelsea','Jody','Marianne']
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base = datetime.datetime.today()
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date_list = [base - datetime.timedelta(days=x) for x in range(0, 180)]
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z = []
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for prgmr in programmers:
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new_row = []
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for date in date_list:
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new_row.append( np.random.poisson() )
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z.append(list(new_row))
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data = [
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go.Heatmap(
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dates = base - np.arange(180) * datetime.timedelta(days=1)
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z = np.random.poisson(size=(len(programmers), len(dates)))
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fig = go.Figure(data=go.Heatmap(
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z=z,
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x=date_list,
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x=dates,
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y=programmers,
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colorscale='Viridis',
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)
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]
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colorscale='Viridis'))
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layout = go.Layout(
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fig.update_layout(
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title='GitHub commits per day',
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xaxis = dict(ticks='', nticks=36),
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yaxis = dict(ticks='' )
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)
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xaxis_nticks=36)
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fig = go.Figure(data=data, layout=layout)
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py.iplot(fig, filename='datetime-heatmap')
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fig.show()
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```
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### Dash Example
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#### Reference
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See https://plot.ly/python/reference/#heatmap for more information and chart attribute options!
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```python
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from IPython.display import display, HTML
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display(HTML('<link href="//fonts.googleapis.com/css?family=Open+Sans:600,400,300,200|Inconsolata|Ubuntu+Mono:400,700rel="stylesheet" type="text/css" />'))
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display(HTML('<link rel="stylesheet" type="text/csshref="http://help.plot.ly/documentation/all_static/css/ipython-notebook-custom.css">'))
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! pip install git+https://github.com/plotly/publisher.git --upgrade
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import publisher
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publisher.publish(
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'heatmaps.ipynb', ' python/heatmaps/', 'Heatmaps | plotly',
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'How to make Heatmaps in Python with Plotly.',
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title = 'Python Heatmaps | plotly',
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name = 'Heatmaps',
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has_thumbnail='true', thumbnail='thumbnail/heatmap.jpg',
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language='python', page_type='example_index',
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display_as='scientific',order=3,
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ipynb= '~notebook_demo/33', redirect_from='python/heatmap/')
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```
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```python
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```

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