Matplotlib.ticker.MaxNLocator Class in Python

matplotlib.ticker.MaxNLocator

Syntax: class matplotlib.ticker.MaxNLocator(*args, **kwargs) Parameter:

• nbins: It is either an integer or 'auto', where the integer value represents the maximum number of intervals; one less than max number of ticks. The number of bins gets automatically determined on the basis of the length of the axis.It is an optional argument and has a default value of 10.
• steps: It is an optional parameter representing a nice number sequence that starts from 1 and ends with 10.
• integer: It is an optional boolean value. If set True, the ticks accepts only integer values, provided at least min_n_ticks integers are within the view limits.
• symmetric: It is an optional value. If set to True, auto-scaling will result in a range symmetric about zero.
• prune: It is an optional parameter that accepts either of the four values: {'lower', 'upper', 'both', None}. By default it is None.

• set_params(self, **kwargs): It sets parameters for the locator.
• tick_values(self, vmin, vmax): It returns the values of the located ticks given vmin and vmax.
• view_limits(self, dmin, dmax): It is used to select a scale for the range from vmin to vmax.

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


N = 10
x = np.arange(N)
y = np.random.randn(N)

fig = plt.figure()
ax = fig.add_subplot(111)
ax.plot(x, y)

# Create your ticker object with M ticks
M = 3
yticks = ticker.MaxNLocator(M)

# Set the yaxis major locator using
# your ticker object. 
ax.yaxis.set_major_locator(yticks)

plt.show()

import matplotlib.pyplot as plt
from matplotlib.ticker import MaxNLocator, IndexFormatter


ax = df.plot()

ax.xaxis.set_major_locator(MaxNLocator(11))
ax.xaxis.set_major_formatter(IndexFormatter(df.index)) 

ax.grid(which ='minor', alpha = 0.2)
ax.grid(which ='major', alpha = 0.5)

ax.legend().set_visible(False)
plt.xticks(rotation = 75)
plt.tight_layout()

plt.show()