Polar Charts [Legacy] in Python/v3

Legacy polar charts in python.

Note: this page is part of the documentation for version 3 of Plotly.py, which is not the most recent version.
See our Version 4 Migration Guide for information about how to upgrade.

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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¶

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://plotly.com/python/reference/#area for more information and chart attribute options!