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2D Histograms in Python

How to make 2D Histograms in Python with Plotly.

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We also have a quick-reference cheatsheet (new!) to help you get started!

Version Check

Note: 2D Histograms are available in version 1.9.12+
Run pip install plotly --upgrade to update your Plotly version

In [1]:
import plotly
plotly.__version__
Out[1]:
'2.0.2'

2D Histogram with Slider Control

Add slider controls to 2d histograms with the postMessage API.
See the code on JSFiddle.
Watch the 5 second video of how it works.

In [2]:
from IPython.core.display import display,HTML
display(HTML('<iframe height=600 width=950 src="https://jsfiddle.net/plotlygraphs/y9sdy76h/4/embedded/result,js,html/"></iframe>'))

2D Histogram of a Bivariate Normal Distribution

In [3]:
import plotly.plotly as py
import plotly.graph_objs as go

import numpy as np

x = np.random.randn(500)
y = np.random.randn(500)+1

data = [
    go.Histogram2d(
        x=x,
        y=y
    )
]
py.iplot(data)
Out[3]:

2D Histogram Binning and Styling Options

In [4]:
import plotly.plotly as py
import plotly.graph_objs as go

import numpy as np

x = np.random.randn(500)
y = np.random.randn(500)+1

data = [
    go.Histogram2d(x=x, y=y, histnorm='probability',
        autobinx=False,
        xbins=dict(start=-3, end=3, size=0.1),
        autobiny=False,
        ybins=dict(start=-2.5, end=4, size=0.1),
        colorscale=[[0, 'rgb(12,51,131)'], [0.25, 'rgb(10,136,186)'], [0.5, 'rgb(242,211,56)'], [0.75, 'rgb(242,143,56)'], [1, 'rgb(217,30,30)']]
    )
]
py.iplot(data)
Out[4]:

2D Histogram Overlaid with a Scatter Chart

In [5]:
import plotly.plotly as py
import plotly.graph_objs as go

import numpy as np

x0 = np.random.randn(100)/5. + 0.5  # 5. enforces float division
y0 = np.random.randn(100)/5. + 0.5
x1 = np.random.rand(50)
y1 = np.random.rand(50) + 1.0

x = np.concatenate([x0, x1])
y = np.concatenate([y0, y1])

trace1 = go.Scatter(
    x=x0,
    y=y0,
    mode='markers',
    showlegend=False,
    marker=dict(
        symbol='x',
        opacity=0.7,
        color='white',
        size=8,
        line=dict(width=1),
    )
)
trace2 = go.Scatter(
    x=x1,
    y=y1,
    mode='markers',
    showlegend=False,
    marker=dict(
        symbol='circle',
        opacity=0.7,
        color='white',
        size=8,
        line=dict(width=1),
    )
)
trace3 = go.Histogram2d(
    x=x,
    y=y,
    colorscale='YIGnBu',
    zmax=10,
    nbinsx=14,
    nbinsy=14,
    zauto=False,
)

layout = go.Layout(
    xaxis=dict( ticks='', showgrid=False, zeroline=False, nticks=20 ),
    yaxis=dict( ticks='', showgrid=False, zeroline=False, nticks=20 ),
    autosize=False,
    height=550,
    width=550,
    hovermode='closest',

)
data = [trace1, trace2, trace3]
fig = go.Figure(data=data, layout=layout)

py.iplot(fig)
Out[5]:

Reference

See https://plot.ly/python/reference/#histogram2d for more information and chart attribute options!

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