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Plotly Express is the easy-to-use, high-level interface to Plotly, which operates on "tidy" data. With px.line, each data point is represented as a vertex (which location is given by the x and y columns) of a polyline mark in 2D space.
For more examples of line plots, see the line and scatter notebook.
import plotly.express as px
gapminder = px.data.gapminder().query("country=='Canada'")
fig = px.line(gapminder, x="year", y="lifeExp", title='Life expectancy in Canada')
fig.show()import plotly.express as px
gapminder = px.data.gapminder().query("continent=='Oceania'")
fig = px.line(gapminder, x="year", y="lifeExp", color='country')
fig.show()import plotly.express as px
gapminder = px.data.gapminder().query("continent != 'Asia'") # remove Asia for visibility
fig = px.line(gapminder, x="year", y="lifeExp", color="continent",
line_group="country", hover_name="country")
fig.show()### Line Plot with go.Scatter
If Plotly Express does not provide a good starting point, it is possible to use the more generic go.Scatter function from plotly.graph_objects. Whereas plotly.express has two functions scatter and line, go.Scatter can be used both for plotting points (makers) or lines, depending on the value of mode. The different options of go.Scatter are documented in its reference page.
import plotly.graph_objects as go
import numpy as np
x = np.arange(10)
fig = go.Figure(data=go.Scatter(x=x, y=x**2))
fig.show()import plotly.graph_objects as go
# Create random data with numpy
import numpy as np
np.random.seed(1)
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
fig = go.Figure()
fig.add_trace(go.Scatter(x=random_x, y=random_y0,
mode='lines',
name='lines'))
fig.add_trace(go.Scatter(x=random_x, y=random_y1,
mode='lines+markers',
name='lines+markers'))
fig.add_trace(go.Scatter(x=random_x, y=random_y2,
mode='markers', name='markers'))
fig.show()This example styles the color and dash of the traces, adds trace names, modifies line width, and adds plot and axes titles.
import plotly.graph_objects as go
# Add data
month = ['January', 'February', 'March', 'April', 'May', 'June', 'July',
'August', 'September', 'October', 'November', 'December']
high_2000 = [32.5, 37.6, 49.9, 53.0, 69.1, 75.4, 76.5, 76.6, 70.7, 60.6, 45.1, 29.3]
low_2000 = [13.8, 22.3, 32.5, 37.2, 49.9, 56.1, 57.7, 58.3, 51.2, 42.8, 31.6, 15.9]
high_2007 = [36.5, 26.6, 43.6, 52.3, 71.5, 81.4, 80.5, 82.2, 76.0, 67.3, 46.1, 35.0]
low_2007 = [23.6, 14.0, 27.0, 36.8, 47.6, 57.7, 58.9, 61.2, 53.3, 48.5, 31.0, 23.6]
high_2014 = [28.8, 28.5, 37.0, 56.8, 69.7, 79.7, 78.5, 77.8, 74.1, 62.6, 45.3, 39.9]
low_2014 = [12.7, 14.3, 18.6, 35.5, 49.9, 58.0, 60.0, 58.6, 51.7, 45.2, 32.2, 29.1]
fig = go.Figure()
# Create and style traces
fig.add_trace(go.Scatter(x=month, y=high_2014, name='High 2014',
line=dict(color='firebrick', width=4)))
fig.add_trace(go.Scatter(x=month, y=low_2014, name = 'Low 2014',
line=dict(color='royalblue', width=4)))
fig.add_trace(go.Scatter(x=month, y=high_2007, name='High 2007',
line=dict(color='firebrick', width=4,
dash='dash') # dash options include 'dash', 'dot', and 'dashdot'
))
fig.add_trace(go.Scatter(x=month, y=low_2007, name='Low 2007',
line = dict(color='royalblue', width=4, dash='dash')))
fig.add_trace(go.Scatter(x=month, y=high_2000, name='High 2000',
line = dict(color='firebrick', width=4, dash='dot')))
fig.add_trace(go.Scatter(x=month, y=low_2000, name='Low 2000',
line=dict(color='royalblue', width=4, dash='dot')))
# Edit the layout
fig.update_layout(title='Average High and Low Temperatures in New York',
xaxis_title='Month',
yaxis_title='Temperature (degrees F)')
fig.show()import plotly.graph_objects as go
x = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15]
fig = go.Figure()
fig.add_trace(go.Scatter(
x=x,
y=[10, 20, None, 15, 10, 5, 15, None, 20, 10, 10, 15, 25, 20, 10],
name = '<b>No</b> Gaps', # Style name/legend entry with html tags
connectgaps=True # override default to connect the gaps
))
fig.add_trace(go.Scatter(
x=x,
y=[5, 15, None, 10, 5, 0, 10, None, 15, 5, 5, 10, 20, 15, 5],
name='Gaps',
))
fig.show()import plotly.graph_objects as go
import numpy as np
x = np.array([1, 2, 3, 4, 5])
y = np.array([1, 3, 2, 3, 1])
fig = go.Figure()
fig.add_trace(go.Scatter(x=x, y=y, name="linear",
line_shape='linear'))
fig.add_trace(go.Scatter(x=x, y=y + 5, name="spline",
text=["tweak line smoothness<br>with 'smoothing' in line object"],
hoverinfo='text+name',
line_shape='spline'))
fig.add_trace(go.Scatter(x=x, y=y + 10, name="vhv",
line_shape='vhv'))
fig.add_trace(go.Scatter(x=x, y=y + 15, name="hvh",
line_shape='hvh'))
fig.add_trace(go.Scatter(x=x, y=y + 20, name="vh",
line_shape='vh'))
fig.add_trace(go.Scatter(x=x, y=y + 25, name="hv",
line_shape='hv'))
fig.update_traces(hoverinfo='text+name', mode='lines+markers')
fig.update_layout(legend=dict(y=0.5, traceorder='reversed', font_size=16))
fig.show()import plotly.graph_objects as go
import numpy as np
title = 'Main Source for News'
labels = ['Television', 'Newspaper', 'Internet', 'Radio']
colors = ['rgb(67,67,67)', 'rgb(115,115,115)', 'rgb(49,130,189)', 'rgb(189,189,189)']
mode_size = [8, 8, 12, 8]
line_size = [2, 2, 4, 2]
x_data = np.vstack((np.arange(2001, 2014),)*4)
y_data = np.array([
[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],
])
fig = go.Figure()
for i in range(0, 4):
fig.add_trace(go.Scatter(x=x_data[i], y=y_data[i], mode='lines',
name=labels[i],
line=dict(color=colors[i], width=line_size[i]),
connectgaps=True,
))
# endpoints
fig.add_trace(go.Scatter(
x=[x_data[i][0], x_data[i][-1]],
y=[y_data[i][0], y_data[i][-1]],
mode='markers',
marker=dict(color=colors[i], size=mode_size[i])
))
fig.update_layout(
xaxis=dict(
showline=True,
showgrid=False,
showticklabels=True,
linecolor='rgb(204, 204, 204)',
linewidth=2,
ticks='outside',
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,
plot_bgcolor='white'
)
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),
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),
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))
fig.update_layout(annotations=annotations)
fig.show()import plotly.graph_objects as go
import numpy as np
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]
fig = go.Figure()
fig.add_trace(go.Scatter(
x=x+x_rev,
y=y1_upper+y1_lower,
fill='toself',
fillcolor='rgba(0,100,80,0.2)',
line_color='rgba(255,255,255,0)',
showlegend=False,
name='Fair',
))
fig.add_trace(go.Scatter(
x=x+x_rev,
y=y2_upper+y2_lower,
fill='toself',
fillcolor='rgba(0,176,246,0.2)',
line_color='rgba(255,255,255,0)',
name='Premium',
showlegend=False,
))
fig.add_trace(go.Scatter(
x=x+x_rev,
y=y3_upper+y3_lower,
fill='toself',
fillcolor='rgba(231,107,243,0.2)',
line_color='rgba(255,255,255,0)',
showlegend=False,
name='Fair',
))
fig.add_trace(go.Scatter(
x=x, y=y1,
line_color='rgb(0,100,80)',
name='Fair',
))
fig.add_trace(go.Scatter(
x=x, y=y2,
line_color='rgb(0,176,246)',
name='Premium',
))
fig.add_trace(go.Scatter(
x=x, y=y3,
line_color='rgb(231,107,243)',
name='Ideal',
))
fig.update_traces(mode='lines')
fig.show()Dash is an Open Source Python library which can help you convert plotly figures into a reactive, web-based application. Below is a simple example of a dashboard created using Dash. Its source code can easily be deployed to a PaaS.
from IPython.display import IFrame
IFrame(src= "https://dash-simple-apps.plotly.host/dash-lineplot/", width="100%", height="650px", frameBorder="0")from IPython.display import IFrame
IFrame(src= "https://dash-simple-apps.plotly.host/dash-lineplot/code", width="100%", height=500, frameBorder="0")See https://plot.ly/python/reference/#scatter for more information and chart attribute options!