How to Add and Customize the X-Axis Label in Matplotlib

To add an x-axis label in Matplotlib, call plt.xlabel("Label"), or ax.set_xlabel("Label") when you work with an Axes object (for example after plt.subplots()). Both accept text styling such as fontsize, color and fontweight, plus labelpad and loc for its position. This guide covers the matplotlib x-axis label from the basics to changing tick labels, showing every nth label, dates, and labels for subplots.

Tested with Python 3.12.5 and Matplotlib 3.11.2. The charts are real Matplotlib windows. Reference: matplotlib.pyplot.xlabel and Axes.set_xlabel.

Add x-axis and y-axis labels with plt.xlabel()

import matplotlib.pyplot as plt

years = [2019, 2020, 2021, 2022, 2023, 2024]
users = [1.2, 1.8, 2.9, 4.1, 5.0, 6.3]

plt.plot(years, users, marker="o")
plt.xlabel("Year")                      # x-axis label
plt.ylabel("Active users (millions)")   # y-axis label
plt.title("App growth")
plt.show()

plt.xlabel() vs ax.set_xlabel()

pyplot functions work on the current axes; Axes methods work on the axes you name. The names differ, and mixing them up is a common error:

pyplot (current axes)	Axes object
plt.xlabel()	ax.set_xlabel()
plt.ylabel()	ax.set_ylabel()
plt.title()	ax.set_title()
plt.xticks()	ax.set_xticks()

import matplotlib.pyplot as plt

fig, ax = plt.subplots()
ax.plot([1, 2, 3], [4, 5, 6])
ax.xlabel("Time")          # pyplot name used on an Axes object

Result:

Traceback (most recent call last):
  File "C:\pyguides\xlabel_error.py", line 5, in <module>
    ax.xlabel("Time")          # pyplot name used on an Axes object
    ^^^^^^^^^
AttributeError: 'Axes' object has no attribute 'xlabel'. Did you mean: '_label'?

Change the x-axis label font size, color and padding

import matplotlib.pyplot as plt

fig, ax = plt.subplots(figsize=(7, 4))
ax.bar(["North", "South", "East", "West"], [42, 35, 51, 28], color="tab:cyan")

ax.set_xlabel("Sales region", fontsize=14, fontweight="bold", color="darkblue", labelpad=12)
ax.set_ylabel("Orders", fontsize=12, style="italic")
plt.tight_layout()
plt.show()

You can read the label back, and calling set_xlabel() again replaces the text while keeping its style:

import matplotlib.pyplot as plt

fig, ax = plt.subplots()
ax.plot([10, 20, 30], [1, 4, 9])
ax.set_xlabel("Distance (km)", fontsize=13)

label = ax.xaxis.label                       # the Text object behind the label
print("text:     ", ax.get_xlabel())
print("fontsize: ", label.get_fontsize())
print("position: ", ax.xaxis.get_label_position())

ax.set_xlabel("Distance (miles)")            # calling it again replaces the text
print("new text: ", ax.get_xlabel())
print("fontsize: ", ax.xaxis.label.get_fontsize(), "(kept)")

Output:

text:      Distance (km)
fontsize:  13.0
position:  bottom
new text:  Distance (miles)
fontsize:  13.0 (kept)

To change the size of every axis label at once, set plt.rcParams["axes.labelsize"]. More font options are in Matplotlib title font size.

Change the x-axis label position

loc aligns the label to the left, centre or right of the axis. To put it above the plot, move the label position to the top:

import matplotlib.pyplot as plt

fig, axes = plt.subplots(1, 3, figsize=(10, 3.4))
for ax in axes:
    ax.plot([0, 1, 2, 3], [1, 3, 2, 4])

axes[0].set_xlabel("loc='left'", loc="left")          # left / center / right
axes[1].set_xlabel("loc='right'", loc="right")
axes[2].set_xlabel("label on top")
axes[2].xaxis.set_label_position("top")              # move the label above the plot
axes[2].xaxis.tick_top()                             # and the tick labels too
plt.tight_layout()
plt.show()

For exact placement, use axes coordinates: ax.xaxis.set_label_coords(0.5, -0.15).

Change the x-axis tick labels

The label is the axis title; the tick labels are the values along the axis. Replace them with set_xticks() and its labels argument:

import matplotlib.pyplot as plt

quarters = [1, 2, 3, 4]
revenue = [120, 135, 160, 190]

fig, ax = plt.subplots(figsize=(7, 4))
ax.plot(quarters, revenue, marker="o")
ax.set_xticks(quarters, labels=["Q1 2025", "Q2 2025", "Q3 2025", "Q4 2025"])   # custom tick labels
ax.set_xlabel("Quarter")
ax.set_ylabel("Revenue (k$)")
plt.tight_layout()
plt.show()

Long tick labels are easier to read when rotated: see rotate tick labels in Matplotlib.

Show every nth x-axis label

With many points, Matplotlib may crowd the axis or pick awkward steps. MultipleLocator(n) puts a tick and label every n units:

import matplotlib.pyplot as plt
import numpy as np
from matplotlib.ticker import MultipleLocator

days = np.arange(1, 101)
visits = 200 + 40 * np.sin(days / 8) + days

fig, ax = plt.subplots(figsize=(8, 4))
ax.plot(days, visits)
ax.xaxis.set_major_locator(MultipleLocator(10))     # a label every 10 days
ax.set_xlabel("Day")
ax.set_ylabel("Visits")
plt.tight_layout()
plt.show()

For category labels (strings), keep every nth one with ax.set_xticks(x[::10]).

Date labels on the x-axis

import matplotlib.pyplot as plt
import matplotlib.dates as mdates
import pandas as pd

dates = pd.date_range("2025-01-01", periods=12, freq="MS")
sales = [210, 190, 230, 260, 250, 300, 320, 310, 280, 270, 330, 360]

fig, ax = plt.subplots(figsize=(8, 4))
ax.plot(dates, sales, marker="o")
ax.xaxis.set_major_formatter(mdates.DateFormatter("%b %Y"))   # Jan 2025, Feb 2025, ...
ax.set_xlabel("Month")
fig.autofmt_xdate()                                          # slant the date labels so they fit
plt.show()

X-axis labels for subplots

One label for all subplots

With shared axes, repeat labels waste space. fig.supxlabel() (Matplotlib 3.4+) adds one centred label for the whole figure:

import matplotlib.pyplot as plt
import numpy as np

x = np.linspace(0, 10, 100)
fig, axes = plt.subplots(2, 2, figsize=(8, 5.5), sharex=True, sharey=True)
for i, ax in enumerate(axes.flat, start=1):
    ax.plot(x, np.sin(x * i / 2))
    ax.set_title(f"Sensor {i}")

fig.supxlabel("Time (seconds)")        # one x-axis label for the whole figure
fig.supylabel("Amplitude")
plt.tight_layout()
plt.show()

A different label for each subplot

import matplotlib.pyplot as plt

fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(9, 3.6))
ax1.bar(["A", "B", "C"], [5, 3, 7])
ax1.set_xlabel("Product")                     # each subplot has its own label
ax2.plot([1, 2, 3, 4], [10, 12, 9, 14])
ax2.set_xlabel("Week", color="tab:red")
plt.tight_layout()
plt.show()

For more on shared axes, see share axes and axis labels in Matplotlib.

More Matplotlib axis tutorials:

• Rotate tick labels in Matplotlib
• Share axes and axis labels between subplots
• Set the axis range in Matplotlib
• Stop labels overlapping with tight_layout()

Frequently asked questions