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How to adjust axes properties in Python - axes titles, styling and coloring axes and grid lines, ticks, tick labels and more.	file_settings	python	base	Axes	14	python/axes/	thumbnail/axes.png

This tutorial explain how to set the properties of 2-dimensional Cartesian axes, namely go.layout.XAxis and go.layout.YAxis.

Other kinds of subplots and axes are described in other tutorials:

3D axes The axis object is go.layout.Scene
Polar axes. The axis object is go.layout.Polar
Ternary axes. The axis object is go.layout.Ternary
Geo axes. The axis object is go.layout.Geo
Mapbox axes. The axis object is go.layout.Mapbox
Color axes. The axis object is go.layout.Coloraxis.

See also the tutorials on facet plots, subplots and multiple axes.

2-D Cartesian Axis Types and Auto-Detection

The different types of Cartesian axes are configured via the xaxis.type or yaxis.type attribute, which can take on the following values:

'linear' as described in this page
'log' (see the log plot tutorial)
'date' (see the tutorial on timeseries)
'category' (see the categorical axes tutorial)
'multicategory' (see the categorical axes tutorial)

The axis type is auto-detected by looking at data from the first trace linked to this axis:

First check for multicategory, then date, then category, else default to linear (log is never automatically selected)
multicategory is just a shape test: is the array nested?
date and category: require more than twice as many distinct date or category strings as distinct numbers in order to choose that axis type.
- Both of these test an evenly-spaced sample of at most 1000 values

Forcing an axis to be categorical

It is possible to force the axis type by setting explicitly xaxis_type. In the example below the automatic X axis type would be linear (because there are not more than twice as many unique strings as unique numbers) but we force it to be category.

import plotly.express as px
fig = px.bar(x=["a", "a", "b", 3], y = [1,2,3,4])
fig.update_xaxes(type='category')
fig.show()

General Axis properties

The different groups of Cartesian axes properties are

title of the axis
tick values (locations of tick marks) and tick labels. Tick labels and grid lines are placed at tick values.
lines: grid lines (passing through tick values), axis lines, zero lines
range of the axis
domain of the axis

The examples on this page apply to axes of any type, but extra attributes are available for axes of type category and axes of type date.

Set and Style Axes Title Labels

Set axis title text with Plotly Express

Axis titles are automatically set to the column names when using Plotly Express with a data frame as input.

import plotly.express as px
df = px.data.tips()
fig = px.scatter(df, x="total_bill", y="tip", color="sex")
fig.show()

Axis titles (and legend titles) can also be overridden using the labels argument of Plotly Express functions:

import plotly.express as px
df = px.data.tips()
fig = px.scatter(df, x="total_bill", y="tip", color="sex",
    labels=dict(total_bill="Total Bill ($)", tip="Tip ($)", sex="Payer Gender")
)
fig.show()

The PX labels argument can also be used without a data frame argument:

import plotly.express as px
fig = px.bar(df, x=["Apples", "Oranges"], y=[10,20], color=["Here", "There"],
    labels=dict(x="Fruit", y="Amount", color="Place")
)
fig.show()

Rotating tick labels in Dash

Dash is the best way to build analytical apps in Python using Plotly figures. To run the app below, run pip install dash, click "Download" to get the code and run python app.py.

Get started with the official Dash docs and learn how to effortlessly style & deploy apps like this with Dash Enterprise.

from IPython.display import IFrame
snippet_url = 'https://dash-gallery.plotly.host/python-docs-dash-snippets/'
IFrame(snippet_url + 'axes', width='100%', height=630)

Moving Tick Labels Inside the Plot

The ticklabelposition attribute moves tick labels inside the plotting area, and modifies the auto-range behaviour to accommodate the labels.

import plotly.express as px

df = px.data.stocks(indexed=True)-1
fig = px.bar(df, x=df.index, y="GOOG")
fig.update_yaxes(ticklabelposition="inside top", title=None)
fig.show()

Set axis title text with Graph Objects

Axis titles are set using the nested title.text property of the x or y axis. Here is an example of creating a new figure and using update_xaxes and update_yaxes, with magic underscore notation, to set the axis titles.

import plotly.express as px

fig = px.line(y=[1, 0])

fig.update_xaxes(title_text='Time')
fig.update_yaxes(title_text='Value A')

fig.show()

Set axis title position

This example sets standoff attribute to cartesian axes to determine the distance between the tick labels and the axis title. Note that the axis title position is always constrained within the margins, so the actual standoff distance is always less than the set or default value. By default automargin is True in Plotly template for the cartesian axis, so the margins will be pushed to fit the axis title at given standoff distance.

import plotly.graph_objects as go

fig = go.Figure(go.Scatter(
    mode = "lines+markers",
    y = [4, 1, 3],
    x = ["December", "January", "February"]))

fig.update_xaxes(
        tickangle = 90,
        title_text = "Month",
        title_font = {"size": 20},
        title_standoff = 25)

fig.update_yaxes(
        title_text = "Temperature",
        title_standoff = 25)

fig.show()

Set axis title font

Here is an example that configures the font family, size, and color for the axis titles in a figure created using Plotly Express.

import plotly.express as px
df = px.data.iris()

fig = px.scatter(df, x="sepal_width", y="sepal_length", facet_col="species")
fig.update_xaxes(title_font=dict(size=18, family='Courier', color='crimson'))
fig.update_yaxes(title_font=dict(size=18, family='Courier', color='crimson'))

fig.show()

Tick Placement, Color, and Style

Toggling axis tick marks

Axis tick marks are disabled by default for the default plotly theme, but they can easily be turned on by setting the ticks axis property to "inside" (to place ticks inside plotting area) or "outside" (to place ticks outside the plotting area).

Here is an example of turning on inside x-axis and y-axis ticks in a faceted figure created using Plotly Express. Note how the col argument to update_yaxes is used to only turn on the y-axis ticks for the left-most subplot.

import plotly.express as px
df = px.data.iris()

fig = px.scatter(df, x="sepal_width", y="sepal_length", facet_col="species")
fig.update_xaxes(ticks="inside")
fig.update_yaxes(ticks="inside", col=1)

fig.show()

Set number of tick marks (and grid lines)

The approximate number of ticks displayed for an axis can be specified using the nticks axis property.

Here is an example of updating the y-axes of a figure created using Plotly Express to display approximately 20 ticks.

import plotly.express as px
df = px.data.iris()

fig = px.scatter(df, x="sepal_width", y="sepal_length", facet_col="species")
fig.update_yaxes(nticks=20)

fig.show()

Set start position and distance between ticks

The tick0 and dtick axis properties can be used to control to placement of axis ticks as follows: If specified, a tick will fall exactly on the location of tick0 and additional ticks will be added in both directions at intervals of dtick.

Here is an example of updating the y axis of a figure created using Plotly Express to position the ticks at intervals of 0.5, starting at 0.25.

import plotly.express as px
df = px.data.iris()

fig = px.scatter(df, x="sepal_width", y="sepal_length", facet_col="species")
fig.update_yaxes(tick0=0.25, dtick=0.5)

fig.show()

Set exact location of axis ticks

It is possible to configure an axis to display ticks at a set of predefined locations by setting the tickvals property to an array of positions.

Here is an example of setting the exact location of ticks on the y axes of a figure created using Plotly Express.

import plotly.express as px
df = px.data.iris()

fig = px.scatter(df, x="sepal_width", y="sepal_length", facet_col="species")
fig.update_yaxes(tickvals=[5.1, 5.9, 6.3, 7.5])

fig.show()

Style tick marks

As discussed above, tick marks are disabled by default in the default plotly theme, but they can be enabled by setting the ticks axis property to "inside" (to place ticks inside plotting area) or "outside" (to place ticks outside the plotting area).

The appearance of these tick marks can be customized by setting their length (ticklen), width (tickwidth), and color (tickcolor).

Here is an example of enabling and styling the tick marks of a faceted figure created using Plotly Express. Note how the col argument to update_yaxes is used to only turn on and style the y-axis ticks for the left-most subplot.

import plotly.express as px
df = px.data.iris()

fig = px.scatter(df, x="sepal_width", y="sepal_length", facet_col="species")
fig.update_xaxes(ticks="outside", tickwidth=2, tickcolor='crimson', ticklen=10)
fig.update_yaxes(ticks="outside", tickwidth=2, tickcolor='crimson', ticklen=10, col=1)

fig.show()

Toggling axis labels

The axis tick mark labels can be disabled by setting the showticklabels axis property to False.

Here is an example of disabling tick labels in all subplots for a faceted figure created using Plotly Express.

import plotly.express as px
df = px.data.iris()

fig = px.scatter(df, x="sepal_width", y="sepal_length", facet_col="species")
fig.update_xaxes(showticklabels=False)
fig.update_yaxes(showticklabels=False)

fig.show()

Set axis label rotation and font

The orientation of the axis tick mark labels is configured using the tickangle axis property. The value of tickangle is the angle of rotation, in the clockwise direction, of the labels from vertical in units of degrees. The font family, size, and color for the tick labels are stored under the tickfont axis property.

Here is an example of rotating the x-axis tick labels by 45 degrees, and customizing their font properties, in a faceted histogram figure created using Plotly Express.

import plotly.express as px
df = px.data.tips()

fig = px.histogram(df, x="sex", y="tip", histfunc='sum', facet_col='smoker')
fig.update_xaxes(tickangle=45, tickfont=dict(family='Rockwell', color='crimson', size=14))

fig.show()

Enumerated Ticks with Tickvals and Ticktext

The tickvals and ticktext axis properties can be used together to display custom tick label text at custom locations along an axis. They should be set to lists of the same length where the tickvals list contains positions along the axis, and ticktext contains the strings that should be displayed at the corresponding positions.

Here is an example.

import plotly.graph_objects as go
import pandas as pd

# Load and filter Apple stock data for 2016
apple_df = pd.read_csv(
    "https://raw.githubusercontent.com/plotly/datasets/master/finance-charts-apple.csv",
    parse_dates=["Date"],
    index_col="Date"
)

apple_df_2016 = apple_df["2016"]

# Create figure and add line
fig = go.Figure()
fig.add_trace(go.Scatter(
    x=apple_df_2016.index,
    y=apple_df_2016["AAPL.High"],
    mode="lines"
))

# Set custom x-axis labels
fig.update_xaxes(
    ticktext=["End of Q1", "End of Q2", "End of Q3", "End of Q4"],
    tickvals=["2016-04-01", "2016-07-01", "2016-10-01", apple_df_2016.index.max()],
)

# Prefix y-axis tick labels with dollar sign
fig.update_yaxes(tickprefix="$")

# Set figure title
fig.update_layout(title_text="Apple Stock Price")

fig.show()

Axis lines: grid and zerolines

Toggling Axis grid lines

Axis grid lines can be disabled by setting the showgrid property to False for the x and/or y axis.

Here is an example of setting showgrid to False in the graph object figure constructor.

import plotly.express as px

fig = px.line(y=[1, 0])
fig.update_xaxes(showgrid=False)
fig.update_yaxes(showgrid=False)
fig.show()

Toggling Axis zero lines

The lines passing through zero can be disabled as well by setting the zeroline axis property to False

import plotly.express as px

fig = px.line(y=[1, 0])

fig.update_xaxes(showgrid=False, zeroline=False)
fig.update_yaxes(showgrid=False, zeroline=False)
fig.show()

Styling and Coloring Axes and the Zero-Line

Styling axis lines

The showline axis property controls the visibility of the axis line, and the linecolor and linewidth axis properties control the color and width of the axis line.

Here is an example of enabling the x and y axis lines, and customizing their width and color, for a faceted histogram created with Plotly Express.

import plotly.express as px
df = px.data.tips()

fig = px.histogram(df, x="sex", y="tip", histfunc='sum', facet_col='smoker')
fig.update_xaxes(showline=True, linewidth=2, linecolor='black')
fig.update_yaxes(showline=True, linewidth=2, linecolor='black')

fig.show()

Mirroring axis lines

Axis lines can be mirrored to the opposite side of the plotting area by setting the mirror axis property to True.

Here is an example of mirroring the x and y axis lines in a faceted histogram created using Plotly Express.

import plotly.express as px
df = px.data.tips()

fig = px.histogram(df, x="sex", y="tip", histfunc='sum', facet_col='smoker')
fig.update_xaxes(showline=True, linewidth=2, linecolor='black', mirror=True)
fig.update_yaxes(showline=True, linewidth=2, linecolor='black', mirror=True)

fig.show()

Styling grid lines

The width and color of axis grid lines are controlled by the gridwidth and gridcolor axis properties.

Here is an example of customizing the grid line width and color for a faceted scatter plot created with Plotly Express

import plotly.express as px
df = px.data.iris()

fig = px.scatter(df, x="sepal_width", y="sepal_length", facet_col="species")
fig.update_xaxes(showgrid=True, gridwidth=1, gridcolor='LightPink')
fig.update_yaxes(showgrid=True, gridwidth=1, gridcolor='LightPink')

fig.show()

Styling zero lines

The width and color of axis zero lines are controlled by the zerolinewidth and zerolinecolor axis properties.

Here is an example of configuring the zero line width and color for a simple figure using the update_xaxes and update_yaxes graph object figure methods.

import plotly.express as px

fig = px.line(y=[1, 0])

fig.update_xaxes(zeroline=True, zerolinewidth=2, zerolinecolor='LightPink')
fig.update_yaxes(zeroline=True, zerolinewidth=2, zerolinecolor='LightPink')

fig.show()

Setting the Range of Axes Manually

The visible x and y axis range can be configured manually by setting the range axis property to a list of two values, the lower and upper boundary.

Here's an example of manually specifying the x and y axis range for a faceted scatter plot created with Plotly Express.

import plotly.express as px
df = px.data.iris()

fig = px.scatter(df, x="sepal_width", y="sepal_length", facet_col="species")
fig.update_xaxes(range=[1.5, 4.5])
fig.update_yaxes(range=[3, 9])

fig.show()

Disabling Pan/Zoom on Axes (Fixed Range)

Pan/Zoom can be disabled for a given axis by setting fixedrange to True.

import plotly.express as px
df = px.data.iris()

fig = px.scatter(df, x="sepal_width", y="sepal_length", facet_col="species")
fig.update_xaxes(fixedrange=True)

fig.show()

Fixed Ratio Axes

The scaleanchor and scaleratio axis properties can be used to force a fixed ratio of pixels per unit between two axes.

Here is an example of anchoring the scale of the x and y axis with a scale ratio of 1. Notice how the zoom box is constrained to prevent the distortion of the shape of the line plot.

import plotly.graph_objects as go

fig = go.Figure()

fig.add_trace(go.Scatter(
    x = [0,1,1,0,0,1,1,2,2,3,3,2,2,3],
    y = [0,0,1,1,3,3,2,2,3,3,1,1,0,0]
))

fig.update_layout(
    width = 800,
    height = 500,
    title = "fixed-ratio axes"
)
fig.update_yaxes(
    scaleanchor = "x",
    scaleratio = 1,
  )

fig.show()

Fixed Ratio Axes with Compressed domain

If an axis needs to be compressed (either due to its own scaleanchor and scaleratio or those of the other axis), constrain determines how that happens: by increasing the "range" (default), or by decreasing the "domain".

import plotly.graph_objects as go
fig = go.Figure()
fig.add_trace(go.Scatter(
    x = [0,1,1,0,0,1,1,2,2,3,3,2,2,3],
    y = [0,0,1,1,3,3,2,2,3,3,1,1,0,0]
))
fig.update_layout(
    width = 800,
    height = 500,
    title = "fixed-ratio axes with compressed axes"
)
fig.update_xaxes(
    range=[-1,4],  # sets the range of xaxis
    constrain="domain",  # meanwhile compresses the xaxis by decreasing its "domain"
)
fig.update_yaxes(
    scaleanchor = "x",
    scaleratio = 1
)
fig.show()

Decreasing the domain spanned by an axis

In the example below, the x and y axis are anchored together, and the range of the xaxis is set manually. By default, plotly extends the range of the axis (overriding the range parameter) to fit in the figure domain. You can restrict the domain to force the axis to span only the set range, by setting constrain='domain' as below.

import plotly.graph_objects as go

fig = go.Figure()

fig.add_trace(go.Scatter(
    x = [0,1,1,0,0,1,1,2,2,3,3,2,2,3],
    y = [0,0,1,1,3,3,2,2,3,3,1,1,0,0]
))

fig.update_layout(
    width = 800,
    height = 500,
    title = "fixed-ratio axes"
)
fig.update_xaxes(
    scaleanchor = "x",
    scaleratio = 1,
)
fig.update_yaxes(
    range=(-0.5, 3.5),
    constrain='domain'
)


fig.show()

Fixed Ratio Axes with Compressed domain

If an axis needs to be compressed (either due to its own scaleanchor and scaleratio or those of the other axis), constrain determines how that happens: by increasing the "range" (default), or by decreasing the "domain".

import plotly.graph_objects as go

fig = go.Figure()

fig.add_trace(go.Scatter(
    x = [0,1,1,0,0,1,1,2,2,3,3,2,2,3],
    y = [0,0,1,1,3,3,2,2,3,3,1,1,0,0]
))

fig.update_layout(
    width = 800,
    height = 500,
    title = "fixed-ratio axes with compressed axes"
)
fig.update_xaxes(
    range=[-1,4],  # sets the range of xaxis
    constrain="domain",  # meanwhile compresses the xaxis by decreasing its "domain"
)
fig.update_yaxes(
    scaleanchor = "x",
    scaleratio = 1,
)

fig.show()

Reversed Axes

You can tell plotly's automatic axis range calculation logic to reverse the direction of an axis by setting the autorange axis property to "reversed".

Here is an example of reversing the direction of the y axes for a faceted scatter plot created using Plotly Express.

import plotly.express as px
df = px.data.iris()

fig = px.scatter(df, x="sepal_width", y="sepal_length", facet_col="species")
fig.update_yaxes(autorange="reversed")

fig.show()

Reversed Axes with Range ( Min/Max ) Specified

The direction of an axis can be reversed when manually setting the range extents by specifying a list containing the upper bound followed by the lower bound (rather that the lower followed by the upper) as the range axis property.

Here is an example of manually setting the reversed range of the y axes in a faceted scatter plot figure created using Plotly Express.

import plotly.express as px
df = px.data.iris()

fig = px.scatter(df, x="sepal_width", y="sepal_length", facet_col="species")
fig.update_yaxes(range=[9, 3])

fig.show()

Axis range for log axis type

If you are using a log type of axis and you want to set the range of the axis, you have to give the log10 value of the bounds when using fig.update_xaxes or fig.update_layout. However, with plotly.express functions you pass directly the values of the range bounds (plotly.express then computes the appropriate values to pass to the figure layout).

import plotly.express as px
import numpy as np

x = np.linspace(1, 200, 30)
fig = px.scatter(x=x, y=x**3, log_x=True, log_y=True, range_x=[0.8, 250])
fig.show()

import plotly.graph_objects as go
import numpy as np

x = np.linspace(1, 200, 30)
fig = go.Figure(go.Scatter(x=x, y=x**3))
fig.update_xaxes(type="log", range=[np.log10(0.8), np.log10(250)])
fig.update_yaxes(type="log")
fig.show()

`nonnegative`, `tozero`, and `normal` Rangemode

The axis auto-range calculation logic can be configured using the rangemode axis parameter.

If rangemode is "normal" (the default), the range is computed based on the min and max values of the input data. If "tozero", the range will always include zero. If "nonnegative", the range will not extend below zero, regardless of the input data.

Here is an example of configuring a faceted scatter plot created using Plotly Express to always include zero for both the x and y axes.

import plotly.express as px
df = px.data.iris()

fig = px.scatter(df, x="sepal_width", y="sepal_length", facet_col="species")
fig.update_xaxes(rangemode="tozero")
fig.update_yaxes(rangemode="tozero")

fig.show()

Setting the domain of the axis

import plotly.graph_objects as go

fig = go.Figure()

fig.add_trace(go.Scatter(
    x = [0,1,1,0,0,1,1,2,2,3,3,2,2,3],
    y = [0,0,1,1,3,3,2,2,3,3,1,1,0,0]
))
fig.update_xaxes(domain=(0.25, 0.75))
fig.update_yaxes(domain=(0.25, 0.75))
fig.show()

Synchronizing axes in subplots with `matches`

Using facet_col from plotly.express let zoom and pan each facet to the same range implicitly. However, if the subplots are created with make_subplots, the axis needs to be updated with matches parameter to update all the subplots accordingly.

Zoom in one trace below, to see the other subplots zoomed to the same x-axis range. To pan all the subplots, click and drag from the center of x-axis to the side:

import plotly.graph_objects as go
from plotly.subplots import make_subplots
import numpy as np

N = 20
x = np.linspace(0, 1, N)

fig = make_subplots(1, 3)
for i in range(1, 4):
    fig.add_trace(go.Scatter(x=x, y=np.random.random(N)), 1, i)
fig.update_xaxes(matches='x')
fig.show()

Reference

See https://plotly.com/python/reference/layout/xaxis/ and https://plotly.com/python/reference/layout/yaxis/ for more information and chart attribute options!

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2-D Cartesian Axis Types and Auto-Detection

Forcing an axis to be categorical

General Axis properties

Set and Style Axes Title Labels

Set axis title text with Plotly Express

Rotating tick labels in Dash

Moving Tick Labels Inside the Plot

Set axis title text with Graph Objects

Set axis title position

Set axis title font

Tick Placement, Color, and Style

Toggling axis tick marks

Set number of tick marks (and grid lines)

Set start position and distance between ticks

Set exact location of axis ticks

Style tick marks

Toggling axis labels

Set axis label rotation and font

Enumerated Ticks with Tickvals and Ticktext

Axis lines: grid and zerolines

Toggling Axis grid lines

Toggling Axis zero lines

Styling and Coloring Axes and the Zero-Line

Styling axis lines

Mirroring axis lines

Styling grid lines

Styling zero lines

Setting the Range of Axes Manually

Disabling Pan/Zoom on Axes (Fixed Range)

Fixed Ratio Axes

Fixed Ratio Axes with Compressed domain

Decreasing the domain spanned by an axis

Fixed Ratio Axes with Compressed domain

Reversed Axes

Reversed Axes with Range ( Min/Max ) Specified

Axis range for log axis type

nonnegative, tozero, and normal Rangemode

Setting the domain of the axis

Synchronizing axes in subplots with matches

Reference

`nonnegative`, `tozero`, and `normal` Rangemode

Synchronizing axes in subplots with `matches`