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:
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