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---

permalink: python/dot-plots/

description: How to make dot plots in Python with Plotly.

name: Dot Plots

has_thumbnail: true

thumbnail: thumbnail/dot-plot.jpg

layout: user-guide

language: python

title: Python Dot Plots | plotly

display_as: basic

has_thumbnail: true

ipynb: ~notebook_demo/2

order: 3.1

page_type: u-guide

---

{% raw %}

</div>

<h4 id="New-to-Plotly?">New to Plotly?<a class="anchor-link" href="#New-to-Plotly?">Â¶</a></h4>Plotly's Python library is free and open source! <a href="https://plot.ly/python/getting-started/">Get started</a> by downloading the client and <a href="https://plot.ly/python/getting-started/">reading the primer</a>.

You can set up Plotly to work in <a href="https://plot.ly/python/getting-started/#initialization-for-online-plotting">online</a> or <a href="https://plot.ly/python/getting-started/#initialization-for-offline-plotting">offline</a> mode, or in <a href="https://plot.ly/python/getting-started/#start-plotting-online">jupyter notebooks</a>.

We also have a quick-reference <a href="https://images.plot.ly/plotly-documentation/images/python_cheat_sheet.pdf">cheatsheet</a> (new!) to help you get started!

<h4 id="Version-Check">Version Check<a class="anchor-link" href="#Version-Check">Â¶</a></h4>Plotly's python package is updated frequently. Run <code>pip install plotly --upgrade</code> to use the latest version.

</div>

<div class=" highlight hl-ipython2"><pre>import plotly

plotly.__version__

</pre></div>

</div>

</div>

</div>

<h4 id="Basic-Dot-Plot">Basic Dot Plot<a class="anchor-link" href="#Basic-Dot-Plot">Â¶</a></h4>Dot plots show changes between two points in time or between two conditions.

</div>

<div class=" highlight hl-ipython2"><pre>import plotly.plotly as py

import plotly.graph_objs as go

trace1 = {"x": [72, 67, 73, 80, 76, 79, 84, 78, 86, 93, 94, 90, 92, 96, 94, 112],

"y": ["Brown", "NYU", "Notre Dame", "Cornell", "Tufts", "Yale",

"Dartmouth", "Chicago", "Columbia", "Duke", "Georgetown",

"Princeton", "U.Penn", "Stanford", "MIT", "Harvard"],

"marker": {"color": "pink", "size": 12},

"mode": "markers",

"name": "Women",

"type": "scatter"

}

trace2 = {"x": [92, 94, 100, 107, 112, 114, 114, 118, 119, 124, 131, 137, 141, 151, 152, 165],

"marker": {"color": "blue", "size": 12},

"mode": "markers",

"name": "Men",

"type": "scatter",

}

data = [trace1, trace2]

layout = {"title": "Gender Earnings Disparity",

"xaxis": {"title": "Annual Salary (in thousands)", },

"yaxis": {"title": "School"}}

fig = go.Figure(data=data, layout=layout)

py.iplot(fig, filenmae='basic_dot-plot')

</pre></div>

</div>

</div>

</div>

<h4 id="Styled-Categorical-Dot-Plot">Styled Categorical Dot Plot<a class="anchor-link" href="#Styled-Categorical-Dot-Plot">Â¶</a></h4>

</div>

<div class=" highlight hl-ipython2"><pre>import plotly.plotly as py

import plotly.graph_objs as go

country = ['Switzerland (2011)', 'Chile (2013)', 'Japan (2014)',

'United States (2012)', 'Slovenia (2014)', 'Canada (2011)',

'Poland (2010)', 'Estonia (2015)', 'Luxembourg (2013)', 'Portugal (2011)']

voting_pop = [40, 45.7, 52, 53.6, 54.1, 54.2, 54.5, 54.7, 55.1, 56.6]

reg_voters = [49.1, 42, 52.7, 84.3, 51.7, 61.1, 55.3, 64.2, 91.1, 58.9]

trace0 = go.Scatter(

x=voting_pop,

y=country,

mode='markers',

name='Percent of estimated voting age population',

marker=dict(

color='rgba(156, 165, 196, 0.95)',

line=dict(

color='rgba(156, 165, 196, 1.0)',

width=1,

),

symbol='circle',

size=16,

)

trace1 = go.Scatter(

x=reg_voters,

y=country,

mode='markers',

name='Percent of estimated registered voters',

marker=dict(

color='rgba(204, 204, 204, 0.95)',

line=dict(

color='rgba(217, 217, 217, 1.0)',

width=1,

),

symbol='circle',

size=16,

)

data = [trace0, trace1]

layout = go.Layout(

title="Votes cast for ten lowest voting age population in OECD countries",

xaxis=dict(

showgrid=False,

showline=True,

linecolor='rgb(102, 102, 102)',

titlefont=dict(

color='rgb(204, 204, 204)'

),

tickfont=dict(

color='rgb(102, 102, 102)',

),

showticklabels=True,

dtick=10,

ticks='outside',

tickcolor='rgb(102, 102, 102)',

),

margin=dict(

l=140,

r=40,

b=50,

t=80

),

legend=dict(

font=dict(

size=10,

),

yanchor='middle',

xanchor='right',

),

width=800,

height=600,

paper_bgcolor='rgb(254, 247, 234)',

plot_bgcolor='rgb(254, 247, 234)',

hovermode='closest',

)

py.iplot(fig, filename='lowest-oecd-votes-cast')

</pre></div>

</div>

</div>

</div>

<h3 id="Reference">Reference<a class="anchor-link" href="#Reference">Â¶</a></h3>

</div>

</div>

See <a href="https://plot.ly/python/reference/#scatter">https://plot.ly/python/reference/#scatter</a> for more information and chart attribute options!

</div>

{% endraw %}

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