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Polar Charts in Python

How to graph polar charts in python. Seven examples of polar line, polar scatter and polar area charts.

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Basic Polar Chart

In [1]:
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')
Out[1]:

Polar Scatter Chart

In [2]:
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)
Out[2]:

Wind Rose Chart

In [3]:
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')
Out[3]:

Reference

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

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