# Dual Y axis with Python and Matplotlib

This post describes how to build a dual Y axis chart using matplotlib.

It uses `ax.twinx()` function to create a twin Axes sharing the xaxis and add a second Y axis on this twin. Note that this kind of chart has drawbacks. Use it with care.

## Libraries

Let's load some libraries. The `datetime` module supplies classes for manipulating dates and times and comes with the standard Python library.

``````import matplotlib.pyplot as plt
import numpy as np

from datetime import datetime, timedelta``````

## Dataset

Let's consider a dataset with 3 variables:

• date
• temperature: the first series to display. Ranges from 0 to 10.
• price: the second series to display. Ranges from 20 to 120.
``````# Ensures reproducibility of random numbers
rng = np.random.default_rng(1234)

# timedelta(i) adds "i" days to the 1st of January of 2019
date = [datetime(2019, 1, 1) + timedelta(i) for i in range(100)]
temperature = np.arange(100) ** 2.5 / 10000 + rng.uniform(size=100)
price = np.arange(120, 20, -1) ** 1.5 / 10 + rng.uniform(size=100)``````

## 2 simple line charts

One could easily build 2 line charts to study the evolution of those 2 series using the code below.

``````fig, axes = plt.subplots(2, 1, figsize=(8, 10))

axes[0].plot(date, temperature)
axes[1].plot(date, price);``````

But even if strongly unadvised, one sometimes wants to display both series on the same chart, thus needing a second Y axis.

## Create a new twin Axis sharing the x axis with `ax.twinx()`: the idea

The first axis has a method (or function) that allows to create a new axis sharing the same x axis. This is done by calling `ax.twinx()`.

``````fig, ax1 = plt.subplots(figsize=(8, 6))

# Instantiate a second axes that shares the same x-axis
ax2 = ax1.twinx()
ax2.set_ylim(4, 20)

plt.show()``````

As can be seen above, the Y axis on the left goes from 0 to 1, while the Y axis on the right goes from 4 to 20. These limits are adjusted automatically when we pass data.

Note that since both Y axes are independent, you can easily set any custom limit on the secondary Y axis.

## Show 2 series on the same line chart thanks to `ax.twinx()`

`ax.twinx()` returns an Axis instance that can be used just as any other Matplotlib Axis. The only particularity of this new Axis is that it shares the horizontal axis with the first one.

Keep in mind that this type of chart can be misleading, giving the impressions that both series are on the same scale, which is not the case.

``````fig, ax1 = plt.subplots(figsize=(8, 8))
ax2 = ax1.twinx()

ax1.plot(date, temperature)
ax2.plot(date, price);``````

## Dual Y axis customization with Matplotlib

Let's add some details to make the chart look better:

• Use distinctive colors for lines and labels
• Make lines thicker
• Add axis labels
• Format date labels on the horizontal axis.
``````COLOR_TEMPERATURE = "#69b3a2"
COLOR_PRICE = "#3399e6"

fig, ax1 = plt.subplots(figsize=(8, 8))
ax2 = ax1.twinx()

ax1.plot(date, temperature, color=COLOR_TEMPERATURE, lw=3)
ax2.plot(date, price, color=COLOR_PRICE, lw=4)

ax1.set_xlabel("Date")
ax1.set_ylabel("Temperature (Celsius °)", color=COLOR_TEMPERATURE, fontsize=14)
ax1.tick_params(axis="y", labelcolor=COLOR_TEMPERATURE)

ax2.set_ylabel("Price (\$)", color=COLOR_PRICE, fontsize=14)
ax2.tick_params(axis="y", labelcolor=COLOR_PRICE)

fig.suptitle("Temperature down, price up", fontsize=20)
fig.autofmt_xdate()

plt.show()``````

## Barplot with overlapping line chart

It's also possible to use the same tricks with other types of plots.

Here is an example displaying a line chart on top of a barplot.

``````fig, ax1 = plt.subplots(figsize=(8, 8))
ax2 = ax1.twinx()

ax1.bar(date, temperature, color=COLOR_TEMPERATURE, edgecolor="black", alpha=0.4, width=1.0)
ax2.plot(date, price, color=COLOR_PRICE, lw=4)

ax1.set_xlabel("Date")
ax1.set_ylabel("Temperature (Celsius °)", color=COLOR_TEMPERATURE, fontsize=14)
ax1.tick_params(axis="y", labelcolor=COLOR_TEMPERATURE)

ax2.set_ylabel("Price (\$)", color=COLOR_PRICE, fontsize=14)
ax2.tick_params(axis="y", labelcolor=COLOR_PRICE)

fig.autofmt_xdate()
fig.suptitle("Temperature down, price up", fontsize=20)

plt.show()``````

## Going further

This post explains how to use a dual axis with matplotlib.

You might be interested in how to customize a multiple line charts and how to customize title.

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