Error Bars in Python

How to add error-bars to charts in Python with Plotly.


New to Plotly?

Plotly is a free and open-source graphing library for Python. We recommend you read our Getting Started guide for the latest installation or upgrade instructions, then move on to our Plotly Fundamentals tutorials or dive straight in to some Basic Charts tutorials.

Error Bars with Plotly Express

Plotly Express is the easy-to-use, high-level interface to Plotly, which operates on "tidy" data and produces easy-to-style figures. For functions representing 2D data points such as px.scatter, px.line, px.bar etc., error bars are given as a column name which is the value of the error_x (for the error on x position) and error_y (for the error on y position).

In [1]:
import plotly.express as px
df = px.data.iris()
df["e"] = df["sepal_width"]/100
fig = px.scatter(df, x="sepal_width", y="sepal_length", color="species",
                 error_x="e", error_y="e")
fig.show()

Asymmetric Error Bars with Plotly Express

In [2]:
import plotly.express as px
df = px.data.iris()
df["e_plus"] = df["sepal_width"]/100
df["e_minus"] = df["sepal_width"]/40
fig = px.scatter(df, x="sepal_width", y="sepal_length", color="species",
                 error_y="e_plus", error_y_minus="e_minus")
fig.show()

Error Bars with graph_objects

Basic Symmetric Error Bars

In [3]:
import plotly.graph_objects as go

fig = go.Figure(data=go.Scatter(
        x=[0, 1, 2],
        y=[6, 10, 2],
        error_y=dict(
            type='data', # value of error bar given in data coordinates
            array=[1, 2, 3],
            visible=True)
    ))
fig.show()

Asymmetric Error Bars

In [4]:
import plotly.graph_objects as go

fig = go.Figure(data=go.Scatter(
        x=[1, 2, 3, 4],
        y=[2, 1, 3, 4],
        error_y=dict(
            type='data',
            symmetric=False,
            array=[0.1, 0.2, 0.1, 0.1],
            arrayminus=[0.2, 0.4, 1, 0.2])
        ))
fig.show()

Error Bars as a Percentage of the y Value

In [5]:
import plotly.graph_objects as go

fig = go.Figure(data=go.Scatter(
        x=[0, 1, 2],
        y=[6, 10, 2],
        error_y=dict(
            type='percent', # value of error bar given as percentage of y value
            value=50,
            visible=True)
    ))
fig.show()

Asymmetric Error Bars with a Constant Offset

In [6]:
import plotly.graph_objects as go

fig = go.Figure(data=go.Scatter(
        x=[1, 2, 3, 4],
        y=[2, 1, 3, 4],
        error_y=dict(
            type='percent',
            symmetric=False,
            value=15,
            valueminus=25)
    ))
fig.show()

Horizontal Error Bars

In [7]:
import plotly.graph_objects as go

fig = go.Figure(data=go.Scatter(
        x=[1, 2, 3, 4],
        y=[2, 1, 3, 4],
        error_x=dict(
            type='percent',
            value=10)
    ))
fig.show()

Bar Chart with Error Bars

In [8]:
import plotly.graph_objects as go

fig = go.Figure()
fig.add_trace(go.Bar(
    name='Control',
    x=['Trial 1', 'Trial 2', 'Trial 3'], y=[3, 6, 4],
    error_y=dict(type='data', array=[1, 0.5, 1.5])
))
fig.add_trace(go.Bar(
    name='Experimental',
    x=['Trial 1', 'Trial 2', 'Trial 3'], y=[4, 7, 3],
    error_y=dict(type='data', array=[0.5, 1, 2])
))
fig.update_layout(barmode='group')
fig.show()

Colored and Styled Error Bars

In [9]:
import plotly.graph_objects as go
import numpy as np

x_theo = np.linspace(-4, 4, 100)
sincx = np.sinc(x_theo)
x = [-3.8, -3.03, -1.91, -1.46, -0.89, -0.24, -0.0, 0.41, 0.89, 1.01, 1.91, 2.28, 2.79, 3.56]
y = [-0.02, 0.04, -0.01, -0.27, 0.36, 0.75, 1.03, 0.65, 0.28, 0.02, -0.11, 0.16, 0.04, -0.15]

fig = go.Figure()
fig.add_trace(go.Scatter(
    x=x_theo, y=sincx,
    name='sinc(x)'
))
fig.add_trace(go.Scatter(
    x=x, y=y,
    mode='markers',
    name='measured',
    error_y=dict(
        type='constant',
        value=0.1,
        color='purple',
        thickness=1.5,
        width=3,
    ),
    error_x=dict(
        type='constant',
        value=0.2,
        color='purple',
        thickness=1.5,
        width=3,
    ),
    marker=dict(color='purple', size=8)
))
fig.show()

Reference

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

What About Dash?

Dash is an open-source framework for building analytical applications, with no Javascript required, and it is tightly integrated with the Plotly graphing library.

Learn about how to install Dash at https://dash.plot.ly/installation.

Everywhere in this page that you see fig.show(), you can display the same figure in a Dash application by passing it to the figure argument of the Graph component from the built-in dash_core_components package like this:

import plotly.graph_objects as go # or plotly.express as px
fig = go.Figure() # or any Plotly Express function e.g. px.bar(...)
# fig.add_trace( ... )
# fig.update_layout( ... )

import dash
import dash_core_components as dcc
import dash_html_components as html

app = dash.Dash()
app.layout = html.Div([
    dcc.Graph(figure=fig)
])

app.run_server(debug=True, use_reloader=False)  # Turn off reloader if inside Jupyter