Legacy polar chart
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Legacy Plot¶
These polar charts are legacy and will likely be deprecated in Plotly 2.0. Please see the new scatterpolar and scatterpolargl trace types for latest and greatest in Plotly polar coordinates.
Basic Polar Chart¶
import plotly.plotly as py
import plotly.graph_objs as go
import pandas as pd
df = pd.read_csv('polar_dataset.csv')
trace1 = go.Scatter(
r=df['x1'],
t=df['y'],
mode='lines',
name='go.Figure8',
marker=dict(
color='none',
line=dict(
color='peru'
)
)
)
trace2 = go.Scatter(
r=df['x2'],
t=df['y'],
mode='lines',
name='Cardioid',
marker=dict(
color='none',
line=dict(
color='darkviolet'
)
)
)
trace3 = go.Scatter(
r=df['x3'],
t=df['y'],
mode='lines',
name='Hypercardioid',
marker=dict(
color='none',
line=dict(
color='deepskyblue'
)
)
)
trace4 = go.Scatter(
r=df['x4'],
t=df['y'],
mode='lines',
name='Subcardioid',
marker=dict(
color='none',
line=dict(
color='orangered'
)
)
)
trace5 = go.Scatter(
r=df['x5'],
t=df['y'],
mode='lines',
name='Supercardioid',
marker=dict(
color='none',
line=dict(
color='green'
)
)
)
data = [trace1, trace2, trace3, trace4, trace5]
layout = go.Layout(
title='Mic Patterns',
font=dict(
family='Arial, sans-serif;',
size=12,
color='#000'
),
orientation=-90
)
fig = go.Figure(data=data, layout=layout)
py.iplot(fig, filename='polar-line')
Polar Scatter Chart¶
import plotly.plotly as py
import plotly.graph_objs as go
import numpy as np
trace1 = go.Scatter(
r = np.random.uniform(1,6,size=62),
t = np.random.uniform(30,5,size=62),
mode='markers',
name='Trial 1',
marker=dict(
color='rgb(27,158,119)',
size=110,
line=dict(
color='white'
),
opacity=0.7
)
)
trace2 = go.Scatter(
r=np.random.uniform(3,8,size=62),
t=np.random.uniform(-14,-76,size=62),
mode='markers',
name='Trial 2',
marker=dict(
color='rgb(217,95,2)',
size=110,
line=dict(
color='white'
),
opacity=0.7
)
)
trace3 = go.Scatter(
r=np.random.uniform(1,7,size=62),
t=np.random.uniform(131,111,size=62),
mode='markers',
name='Trial 3',
marker=dict(
color='rgb(117,112,179)',
size=110,
line=dict(
color='white'
),
opacity=0.7
)
)
trace4 = go.Scatter(
r=np.random.uniform(1,9,size=62),
t=np.random.uniform(-140,-177,size=62),
mode='markers',
name='Trial 4',
marker=dict(
color='rgb(231,41,138)',
size=110,
line=dict(
color='white'
),
opacity=0.7
)
)
trace5 = go.Scatter(
r=np.random.uniform(1,3,size=62),
t=np.random.uniform(-100,-163,size=62),
mode='markers',
name='Trial 5',
marker=dict(
color='rgb(102,166,30)',
size=110,
line=dict(
color='white'
),
opacity=0.7
)
)
trace6 = go.Scatter(
r=np.random.uniform(0,5,size=62),
t=np.random.uniform(66,47,size=62),
mode='markers',
name='Trial 6',
marker=dict(
color='rgb(230,171,2)',
size=110,
line=dict(
color='white'
),
opacity=0.7
)
)
data = [trace1, trace2, trace3, trace4, trace5, trace6]
layout = go.Layout(
title='Hobbs-Pearson Trials',
font=dict(
size=15
),
plot_bgcolor='rgb(223, 223, 223)',
angularaxis=dict(
tickcolor='rgb(253,253,253)'
)
)
fig = go.Figure(data=data, layout=layout)
py.iplot(fig)
Wind Rose Chart¶
import plotly.plotly as py
import plotly.graph_objs as go
trace1 = go.Area(
r=[77.5, 72.5, 70.0, 45.0, 22.5, 42.5, 40.0, 62.5],
t=['North', 'N-E', 'East', 'S-E', 'South', 'S-W', 'West', 'N-W'],
name='11-14 m/s',
marker=dict(
color='rgb(106,81,163)'
)
)
trace2 = go.Area(
r=[57.49999999999999, 50.0, 45.0, 35.0, 20.0, 22.5, 37.5, 55.00000000000001],
t=['North', 'N-E', 'East', 'S-E', 'South', 'S-W', 'West', 'N-W'],
name='8-11 m/s',
marker=dict(
color='rgb(158,154,200)'
)
)
trace3 = go.Area(
r=[40.0, 30.0, 30.0, 35.0, 7.5, 7.5, 32.5, 40.0],
t=['North', 'N-E', 'East', 'S-E', 'South', 'S-W', 'West', 'N-W'],
name='5-8 m/s',
marker=dict(
color='rgb(203,201,226)'
)
)
trace4 = go.Area(
r=[20.0, 7.5, 15.0, 22.5, 2.5, 2.5, 12.5, 22.5],
t=['North', 'N-E', 'East', 'S-E', 'South', 'S-W', 'West', 'N-W'],
name='< 5 m/s',
marker=dict(
color='rgb(242,240,247)'
)
)
data = [trace1, trace2, trace3, trace4]
layout = go.Layout(
title='Wind Speed Distribution in Laurel, NE',
font=dict(
size=16
),
legend=dict(
font=dict(
size=16
)
),
radialaxis=dict(
ticksuffix='%'
),
orientation=270
)
fig = go.Figure(data=data, layout=layout)
py.iplot(fig, filename='polar-area-chart')
Reference¶
See https://plot.ly/python/reference/#area for more information and chart attribute options!
from IPython.display import display, HTML
display(HTML('<link href="//fonts.googleapis.com/css?family=Open+Sans:600,400,300,200|Inconsolata|Ubuntu+Mono:400,700" rel="stylesheet" type="text/css" />'))
display(HTML('<link rel="stylesheet" type="text/css" href="http://help.plot.ly/documentation/all_static/css/ipython-notebook-custom.css">'))
! pip install git+https://github.com/plotly/publisher.git --upgrade
import publisher
publisher.publish(
'polar.ipynb', 'python/legacy-polar-chart/', 'Polar Charts [Legacy]',
'Legacy polar charts in python.',
title = 'Python Polar Charts | plotly',
has_thumbnail='true', thumbnail='thumbnail/polar-scatter.jpg',
language='python',
display_as='legacy_charts', order=1,
ipynb= '~notebook_demo/37')