4.4. Visualization Plotly

4.4. Visualization Plotly — Python

4.4.1. Installation

$ python -m pip install plotly

4.4.2. Offline usage

# Change from (this will upload chart to plot.ly)
import plotly.plotly as py

# to (this will render chart offline - on your computer)
import  plotly.offline as py

4.4.3. Jupyter Usage

import plotly.offline as py
import plotly.graph_objs as go


x = [1, 2, 3, 4]
y = [4, 3, 2, 1]


# For in script chart rendering
py.plot({
    "data": [go.Scatter(x=x, y=y)],
    "layout": go.Layout(title="hello world")
})

# If you want to use Plotly with Jupyter
# Note the ``i`` before ``plot``
py.iplot({
    "data": [go.Scatter(x=x, y=y)],
    "layout": go.Layout(title="hello world")
})

4.4.4. Plot Controls & IPython widgets

Code 4.30. Plot Controls & IPython widgets

# doctest: +SKIP_FILE

import plotly.offline as py
import numpy as np

data = []
steps = []

for step in np.arange(0, 5, 0.1):
    data.append({
        'visible': False,
        'line': {'color': '00CED1', 'width': 6},
        'name': f'𝜈 = {step}',
        'x': np.arange(0, 10, 0.01),
        'y': np.sin(step * np.arange(0, 10, 0.01)),
    })

data[10]['visible'] = True

for i in range(len(data)):
    step = {
        'method': 'restyle',
        'args': ['visible', [False] * len(data)],
    }

    step['args'][1][i] = True  # Toggle 'i' trace to "visible"
    steps.append(step)

sliders = [{
    'active': 10,
    'currentvalue': {"prefix": "Frequency: "},
    'pad': {"t": 50},
    'steps': steps
}]

py.iplot({
    'data': data,
    'layout': {'sliders': sliders}},
    filename='Sine Wave Slider')

4.4.5. Table

Code 4.31. Plotting Table

# doctest: +SKIP_FILE

import plotly.offline as py
import plotly.figure_factory as ff
import pandas as pd

df = pd.read_csv('https://python3.info/_static/school-earnings.csv')

table = ff.create_table(df)
py.iplot(table, filename='jupyter-table1')

4.4.6. Bars

Simple Bars:

Code 4.32. Simple Bars

# doctest: +SKIP_FILE

import plotly.offline as py
import plotly.graph_objs as go
import pandas as pd

df = pd.read_csv('https://python3.info/_static/school-earnings.csv')

data = [go.Bar(x=df.School, y=df.Gap)]
py.iplot(data, filename='jupyter-basic_bar')

Multi Bars:

Code 4.33. Multi Bars

# doctest: +SKIP_FILE

import plotly.offline as py
import plotly.graph_objs as go
import pandas as pd

df = pd.read_csv('https://python3.info/_static/school-earnings.csv')

data = [go.Bar(x=df.School, y=df.Gap)]
py.iplot(data, filename='jupyter-basic_bar')

4.4.7. Box Plot

Basic Box Plot:

Code 4.34. Basic Box Plot

# doctest: +SKIP_FILE

import plotly.offline as py
import plotly.graph_objs as go
import numpy as np

y0 = np.random.randn(50) - 1
y1 = np.random.randn(50) + 1

py.iplot([
    go.Box(y=y0),
    go.Box(y=y1),
])

Colored Box Plot:

Code 4.35. Colored Box Plot

# doctest: +SKIP_FILE

import plotly.offline as py
import plotly.graph_objs as go

import numpy as np

y0 = np.random.randn(50)
y1 = np.random.randn(50) + 1

trace0 = go.Box(
    y=y0,
    name='Sample A',
    marker=dict(
        color='rgb(214, 12, 140)',
    )
)
trace1 = go.Box(
    y=y1,
    name='Sample B',
    marker=dict(
        color='rgb(0, 128, 128)',
    )
)
data = [trace0, trace1]
py.iplot(data)

Grouped Box Plot:

Code 4.36. Grouped Box Plot

# doctest: +SKIP_FILE

import plotly.offline as py
import plotly.graph_objs as go


x = ['day 1', 'day 1', 'day 1', 'day 1', 'day 1', 'day 1',
     'day 2', 'day 2', 'day 2', 'day 2', 'day 2', 'day 2']

trace0 = go.Box(
    y=[0.2, 0.2, 0.6, 1.0, 0.5, 0.4, 0.2, 0.7, 0.9, 0.1, 0.5, 0.3],
    x=x,
    name='kale',
    marker=dict(
        color='#3D9970'
    )
)
trace1 = go.Box(
    y=[0.6, 0.7, 0.3, 0.6, 0.0, 0.5, 0.7, 0.9, 0.5, 0.8, 0.7, 0.2],
    x=x,
    name='radishes',
    marker=dict(
        color='#FF4136'
    )
)
trace2 = go.Box(
    y=[0.1, 0.3, 0.1, 0.9, 0.6, 0.6, 0.9, 1.0, 0.3, 0.6, 0.8, 0.5],
    x=x,
    name='carrots',
    marker=dict(
        color='#FF851B'
    )
)
data = [trace0, trace1, trace2]
layout = go.Layout(
    yaxis=dict(
        title='normalized moisture',
        zeroline=False
    ),
    boxmode='group'
)
fig = go.Figure(data=data, layout=layout)
py.iplot(fig)

Outliers:

Code 4.37. Outliers

# doctest: +SKIP_FILE

import plotly.offline as py
import plotly.graph_objs as go


trace0 = go.Box(
    y = [0.75, 5.25, 5.5, 6, 6.2, 6.6, 6.80, 7.0, 7.2, 7.5, 7.5, 7.75, 8.15,
         8.15, 8.65, 8.93, 9.2, 9.5, 10, 10.25, 11.5, 12, 16, 20.90, 22.3, 23.25],
    name="All Points",
    jitter=0.3,
    pointpos=-1.8,
    boxpoints='all',
    marker=dict(
        color='rgb(7,40,89)'),
    line=dict(
        color='rgb(7,40,89)')
)

trace1 = go.Box(
    y = [0.75, 5.25, 5.5, 6, 6.2, 6.6, 6.80, 7.0, 7.2, 7.5, 7.5, 7.75, 8.15,
         8.15, 8.65, 8.93, 9.2, 9.5, 10, 10.25, 11.5, 12, 16, 20.90, 22.3, 23.25],
    name="Only Whiskers",
    boxpoints=False,
    marker=dict(
        color='rgb(9,56,125)'),
    line=dict(
        color='rgb(9,56,125)')
)

trace2 = go.Box(
    y = [0.75, 5.25, 5.5, 6, 6.2, 6.6, 6.80, 7.0, 7.2, 7.5, 7.5, 7.75, 8.15,
         8.15, 8.65, 8.93, 9.2, 9.5, 10, 10.25, 11.5, 12, 16, 20.90, 22.3, 23.25],
    name="Suspected Outliers",
    boxpoints='suspectedoutliers',
    marker=dict(
        color='rgb(8,81,156)',
        outliercolor='rgba(219, 64, 82, 0.6)',
        line=dict(
            outliercolor='rgba(219, 64, 82, 0.6)',
            outlierwidth=2)),
    line=dict(
        color='rgb(8,81,156)')
)

trace3 = go.Box(
    y = [0.75, 5.25, 5.5, 6, 6.2, 6.6, 6.80, 7.0, 7.2, 7.5, 7.5, 7.75, 8.15,
         8.15, 8.65, 8.93, 9.2, 9.5, 10, 10.25, 11.5, 12, 16, 20.90, 22.3, 23.25],
    name="Whiskers and Outliers",
    boxpoints='outliers',
    marker=dict(
        color='rgb(107,174,214)'),
    line=dict(
        color='rgb(107,174,214)')
)

data = [trace0, trace1, trace2, trace3]

layout = go.Layout(
    title="Box Plot Styling Outliers"
)

fig = go.Figure(data=data, layout=layout)
py.iplot(fig, filename="Box Plot Styling Outliers")

4.4.8. Line Chart

Code 4.38. Line Chart

# doctest: +SKIP_FILE

import plotly.offline as py
import plotly.graph_objs as go
import math
import numpy as np

x = [1, 2, 3, 4]
y = [4, 3, 2, 1]

py.iplot({
    "data": [go.Scatter(x=x, y=y)],
    "layout": go.Layout(title="hello world")
})

x = [x for x in np.arange(0, 10, 0.1)]
y = [math.sin(y) for y in np.arange(0, 5, 0.1)]

py.iplot({
    "data": [go.Scatter(x=x, y=y)],
    "layout": go.Layout(title="Sin(x)")
})

4.4.9. Time Series

Simple Time Series:

Code 4.39. Simple Time Series

# doctest: +SKIP_FILE

import plotly.offline as py
import plotly.graph_objs as go

import pandas as pd

df = pd.read_csv('https://python3.info/_static/finance-charts-apple.csv')

data = [go.Scatter(
    x=df.Date,
    y=df['AAPL.Close'])]

py.iplot(data)

Timeseries Range:

Code 4.40. Timeseries Range

# doctest: +SKIP_FILE

import plotly.offline as py
import plotly.graph_objs as go

import pandas as pd

df = pd.read_csv('https://python3.info/_static/finance-charts-apple.csv')


# noinspection SpellCheckingInspection
trace_high = go.Scatter(
    x=df.Date,
    y=df['AAPL.High'],
    name="AAPL High",
    line=dict(color='#17BECF'),
    opacity=0.8)

trace_low = go.Scatter(
    x=df.Date,
    y=df['AAPL.Low'],
    name="AAPL Low",
    line=dict(color='#7F7F7F'),
    opacity=0.8)

data = [trace_high, trace_low]

layout = dict(
    title="Manually Set Date Range",
    xaxis=dict(
        range=['2016-07-01', '2016-12-31'])
)

fig = dict(data=data, layout=layout)
py.iplot(fig, filename="Manually Set Range")

Rangeslider:

Code 4.41. Timeseries Range

# doctest: +SKIP_FILE

import plotly.offline as py
import plotly.graph_objs as go

import pandas as pd

df = pd.read_csv('https://python3.info/_static/finance-charts-apple.csv')


# noinspection SpellCheckingInspection
trace_high = go.Scatter(
    x=df.Date,
    y=df['AAPL.High'],
    name="AAPL High",
    line=dict(color='#17BECF'),
    opacity=0.8)

trace_low = go.Scatter(
    x=df.Date,
    y=df['AAPL.Low'],
    name="AAPL Low",
    line=dict(color='#7F7F7F'),
    opacity=0.8)

data = [trace_high, trace_low]

layout = dict(
    title='Time Series with Rangeslider',
    xaxis=dict(
        rangeselector=dict(
            buttons=list([
                dict(count=1,
                     label='1m',
                     step='month',
                     stepmode='backward'),
                dict(count=6,
                     label='6m',
                     step='month',
                     stepmode='backward'),
                dict(step='all')
            ])
        ),
        rangeslider=dict(),
        type='date'
    )
)

fig = dict(data=data, layout=layout)
py.iplot(fig, filename="Time Series with Rangeslider")

4.4.10. Multiple x-axis

Code 4.42. Multiple x-axis

# doctest: +SKIP_FILE

import plotly.offline as py
import plotly.graph_objs as go

trace1 = go.Scatter(
    x=[1, 2, 3],
    y=[40, 50, 60],
    name='yaxis data'
)
trace2 = go.Scatter(
    x=[2, 3, 4],
    y=[4, 5, 6],
    name='yaxis2 data',
    yaxis='y2'
)
data = [trace1, trace2]
layout = go.Layout(
    title='Double Y Axis Example',
    yaxis=dict(
        title='yaxis title'
    ),
    yaxis2=dict(
        title='yaxis2 title',
        titlefont=dict(
            color='rgb(148, 103, 189)'
        ),
        tickfont=dict(
            color='rgb(148, 103, 189)'
        ),
        overlaying='y',
        side='right'
    )
)
fig = go.Figure(data=data, layout=layout)
plot_url = py.iplot(fig, filename='multiple-axes-double')

4.4.11. Multiple y-axis

Code 4.43. Multiple y-axis

# doctest: +SKIP_FILE

import plotly.offline as py
import plotly.graph_objs as go

trace1 = go.Scatter(
    x=[1, 2, 3],
    y=[40, 50, 60],
    name='yaxis data'
)
trace2 = go.Scatter(
    x=[2, 3, 4],
    y=[4, 5, 6],
    name='yaxis2 data',
    yaxis='y2'
)
data = [trace1, trace2]
layout = go.Layout(
    title='Double Y Axis Example',
    yaxis=dict(
        title='yaxis title'
    ),
    yaxis2=dict(
        title='yaxis2 title',
        titlefont=dict(
            color='rgb(148, 103, 189)'
        ),
        tickfont=dict(
            color='rgb(148, 103, 189)'
        ),
        overlaying='y',
        side='right'
    )
)
fig = go.Figure(data=data, layout=layout)
plot_url = py.iplot(fig, filename='multiple-axes-double')

4.4.12. Line Plot Modes

Code 4.44. Line Plot Modes

# doctest: +SKIP_FILE

import plotly.offline as py
import plotly.graph_objs as go

# Create random data with numpy
import numpy as np

N = 100
random_x = np.linspace(0, 1, N)
random_y0 = np.random.randn(N) + 5
random_y1 = np.random.randn(N)
random_y2 = np.random.randn(N) - 5

# Create traces
trace0 = go.Scatter(
    x=random_x,
    y=random_y0,
    mode='lines',
    name='lines'
)
trace1 = go.Scatter(
    x=random_x,
    y=random_y1,
    mode='lines+markers',
    name='lines+markers'
)
trace2 = go.Scatter(
    x=random_x,
    y=random_y2,
    mode='markers',
    name='markers'
)
data = [trace0, trace1, trace2]

py.iplot(data, filename='line-mode')

4.4.13. Labels with annotations

Code 4.45. Labels with annotations

# doctest: +SKIP_FILE

import plotly.offline as py
import plotly.graph_objs as go

title = 'Main Source for News'

labels = ['Television', 'Newspaper', 'Internet', 'Radio']

colors = ['rgba(67,67,67,1)', 'rgba(115,115,115,1)', 'rgba(49,130,189, 1)', 'rgba(189,189,189,1)']

mode_size = [8, 8, 12, 8]

line_size = [2, 2, 4, 2]

x_data = [
    [2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010, 2011, 2013],
    [2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010, 2011, 2013],
    [2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010, 2011, 2013],
    [2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010, 2011, 2013],
]

y_data = [
    [74, 82, 80, 74, 73, 72, 74, 70, 70, 66, 66, 69],
    [45, 42, 50, 46, 36, 36, 34, 35, 32, 31, 31, 28],
    [13, 14, 20, 24, 20, 24, 24, 40, 35, 41, 43, 50],
    [18, 21, 18, 21, 16, 14, 13, 18, 17, 16, 19, 23],
]

traces = []

for i in range(0, 4):
    traces.append(go.Scatter(
        x=x_data[i],
        y=y_data[i],
        mode='lines',
        line=dict(color=colors[i], width=line_size[i]),
        connectgaps=True,
    ))

    traces.append(go.Scatter(
        x=[x_data[i][0], x_data[i][11]],
        y=[y_data[i][0], y_data[i][11]],
        mode='markers',
        marker=dict(color=colors[i], size=mode_size[i])
    ))

layout = go.Layout(
    xaxis=dict(
        showline=True,
        showgrid=False,
        showticklabels=True,
        linecolor='rgb(204, 204, 204)',
        linewidth=2,
        autotick=False,
        ticks='outside',
        tickcolor='rgb(204, 204, 204)',
        tickwidth=2,
        ticklen=5,
        tickfont=dict(
            family='Arial',
            size=12,
            color='rgb(82, 82, 82)',
        ),
    ),
    yaxis=dict(
        showgrid=False,
        zeroline=False,
        showline=False,
        showticklabels=False,
    ),
    autosize=False,
    margin=dict(
        autoexpand=False,
        l=100,
        r=20,
        t=110,
    ),
    showlegend=False,
)

annotations = []

# Adding labels
for y_trace, label, color in zip(y_data, labels, colors):
    # labeling the left_side of the plot
    annotations.append(dict(xref='paper', x=0.05, y=y_trace[0],
                            xanchor='right', yanchor='middle',
                            text=label + ' {}%'.format(y_trace[0]),
                            font=dict(family='Arial',
                                      size=16,
                                      color=colors, ),
                            showarrow=False))
    # labeling the right_side of the plot
    annotations.append(dict(xref='paper', x=0.95, y=y_trace[11],
                            xanchor='left', yanchor='middle',
                            text='{}%'.format(y_trace[11]),
                            font=dict(family='Arial',
                                      size=16,
                                      color=colors, ),
                            showarrow=False))
# Title
annotations.append(dict(xref='paper', yref='paper', x=0.0, y=1.05,
                        xanchor='left', yanchor='bottom',
                        text='Main Source for News',
                        font=dict(family='Arial',
                                  size=30,
                                  color='rgb(37,37,37)'),
                        showarrow=False))
# Source
annotations.append(dict(xref='paper', yref='paper', x=0.5, y=-0.1,
                        xanchor='center', yanchor='top',
                        text='Source: PewResearch Center & ' +
                             'Storytelling with data',
                        font=dict(family='Arial',
                                  size=12,
                                  color='rgb(150,150,150)'),
                        showarrow=False))

layout['annotations'] = annotations

fig = go.Figure(data=traces, layout=layout)
py.iplot(fig, filename='news-source')

4.4.14. Filled Line

Code 4.46. Filled Line

# doctest: +SKIP_FILE

import plotly.offline as py
import plotly.graph_objs as go

x = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
x_rev = x[::-1]

# Line 1
y1 = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
y1_upper = [2, 3, 4, 5, 6, 7, 8, 9, 10, 11]
y1_lower = [0, 1, 2, 3, 4, 5, 6, 7, 8, 9]
y1_lower = y1_lower[::-1]

# Line 2
y2 = [5, 2.5, 5, 7.5, 5, 2.5, 7.5, 4.5, 5.5, 5]
y2_upper = [5.5, 3, 5.5, 8, 6, 3, 8, 5, 6, 5.5]
y2_lower = [4.5, 2, 4.4, 7, 4, 2, 7, 4, 5, 4.75]
y2_lower = y2_lower[::-1]

# Line 3
y3 = [10, 8, 6, 4, 2, 0, 2, 4, 2, 0]
y3_upper = [11, 9, 7, 5, 3, 1, 3, 5, 3, 1]
y3_lower = [9, 7, 5, 3, 1, -.5, 1, 3, 1, -1]
y3_lower = y3_lower[::-1]

trace1 = go.Scatter(
    x=x + x_rev,
    y=y1_upper + y1_lower,
    fill='tozerox',
    fillcolor='rgba(0,100,80,0.2)',
    line=dict(color='rgba(255,255,255,0)'),
    showlegend=False,
    name='Fair',
)
trace2 = go.Scatter(
    x=x + x_rev,
    y=y2_upper + y2_lower,
    fill='tozerox',
    fillcolor='rgba(0,176,246,0.2)',
    line=dict(color='rgba(255,255,255,0)'),
    name='Premium',
    showlegend=False,
)
trace3 = go.Scatter(
    x=x + x_rev,
    y=y3_upper + y3_lower,
    fill='tozerox',
    fillcolor='rgba(231,107,243,0.2)',
    line=dict(color='rgba(255,255,255,0)'),
    showlegend=False,
    name='Fair',
)
trace4 = go.Scatter(
    x=x,
    y=y1,
    line=dict(color='rgb(0,100,80)'),
    mode='lines',
    name='Fair',
)
trace5 = go.Scatter(
    x=x,
    y=y2,
    line=dict(color='rgb(0,176,246)'),
    mode='lines',
    name='Premium',
)
trace6 = go.Scatter(
    x=x,
    y=y3,
    line=dict(color='rgb(231,107,243)'),
    mode='lines',
    name='Ideal',
)

data = [trace1, trace2, trace3, trace4, trace5, trace6]

layout = go.Layout(
    paper_bgcolor='rgb(255,255,255)',
    plot_bgcolor='rgb(229,229,229)',
    xaxis=dict(
        gridcolor='rgb(255,255,255)',
        range=[1, 10],
        showgrid=True,
        showline=False,
        showticklabels=True,
        tickcolor='rgb(127,127,127)',
        ticks='outside',
        zeroline=False
    ),
    yaxis=dict(
        gridcolor='rgb(255,255,255)',
        showgrid=True,
        showline=False,
        showticklabels=True,
        tickcolor='rgb(127,127,127)',
        ticks='outside',
        zeroline=False
    ),
)
fig = go.Figure(data=data, layout=layout)
py.iplot(fig, filename='shaded_lines')

4.4.15. 3D Plotting

Code 4.47. Simple 3D Plotting

# doctest: +SKIP_FILE

import plotly.offline as py
import plotly.graph_objs as go
import numpy as np

s = np.linspace(0, 2 * np.pi, 240)
t = np.linspace(0, np.pi, 240)
tGrid, sGrid = np.meshgrid(s, t)

r = 2 + np.sin(7 * sGrid + 5 * tGrid)  # r = 2 + sin(7s+5t)
x = r * np.cos(sGrid) * np.sin(tGrid)  # x = r*cos(s)*sin(t)
y = r * np.sin(sGrid) * np.sin(tGrid)  # y = r*sin(s)*sin(t)
z = r * np.cos(tGrid)  # z = r*cos(t)

surface = go.Surface(x=x, y=y, z=z)
data = [surface]

layout = go.Layout(
    title='Parametric Plot',
    scene=dict(
        xaxis=dict(
            gridcolor='rgb(255, 255, 255)',
            zerolinecolor='rgb(255, 255, 255)',
            showbackground=True,
            backgroundcolor='rgb(230, 230,230)'
        ),
        yaxis=dict(
            gridcolor='rgb(255, 255, 255)',
            zerolinecolor='rgb(255, 255, 255)',
            showbackground=True,
            backgroundcolor='rgb(230, 230,230)'
        ),
        zaxis=dict(
            gridcolor='rgb(255, 255, 255)',
            zerolinecolor='rgb(255, 255, 255)',
            showbackground=True,
            backgroundcolor='rgb(230, 230,230)'
        )
    )
)

fig = go.Figure(data=data, layout=layout)
py.iplot(fig, filename='jupyter-parametric_plot')