Matplotlib.axis.Axis.set_major_formatter() function in Python

Matplotlib is a library in Python and it is numerical – mathematical extension for NumPy library. It is an amazing visualization library in Python for 2D plots of arrays and used for working with the broader SciPy stack.

matplotlib.axis.Axis.set_major_formatter() Function

The Axis.set_major_formatter() function in axis module of matplotlib library is used to set the formatter of the major ticker.

Syntax: Axis.set_major_formatter(self, formatter)

Parameters: This method accepts the following parameters. 

• formatter: This parameter is the Formatter.

Return value: This method does not returns any value. 

Below examples illustrate the matplotlib.axis.Axis.set_major_formatter() function in matplotlib.axis:
Example 1:

Python3

# Implementation of matplotlib function
import numpy as np
from matplotlib.axis import Axis
import matplotlib.pyplot as plt
import matplotlib.ticker as ticker

np.random.seed(19680801)

fig, ax = plt.subplots()
ax.plot(100*np.random.rand(20))

formatter = ticker.FormatStrFormatter('?%1.2f')
Axis.set_major_formatter(ax.yaxis, formatter)

for tick in ax.yaxis.get_major_ticks():
    tick.label1.set_color('green')

plt.title("Matplotlib.axis.Axis.set_major_formatter()\n\
Function Example", fontsize = 12, fontweight ='bold')

plt.show()

Output:

Example 2:

Python3

# Implementation of matplotlib function
from matplotlib.axis import Axis
import datetime
import matplotlib.pyplot as plt
from matplotlib.dates import DayLocator, HourLocator, DateFormatter, drange
import numpy as np

date1 = datetime.datetime(2020, 4, 2)
date2 = datetime.datetime(2020, 4, 6)
delta = datetime.timedelta(hours = 6)
dates = drange(date1, date2, delta)

y = np.arange(len(dates))

fig, ax = plt.subplots()
ax.plot_date(dates, y ** 2, 'g')

ax.set_xlim(dates[0], dates[-1])

ax.xaxis.set_major_locator(DayLocator())
ax.xaxis.set_minor_locator(HourLocator(range(0, 25, 6)))
ax.xaxis.set_major_formatter(plt.NullFormatter())

ax.fmt_xdata = DateFormatter('% Y-% m-% d % H:% M:% S')
fig.autofmt_xdate()

plt.title("Matplotlib.axis.Axis.set_major_formatter()\n\
Function Example", fontsize = 12, fontweight ='bold')

plt.show()

Output: