Changing The "tick Frequency" On X Or Y Axis In Matplotlib?

Answer :

You could explicitly set where you want to tick marks with plt.xticks:

plt.xticks(np.arange(min(x), max(x)+1, 1.0)) 

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For example,

import numpy as np import matplotlib.pyplot as plt  x = [0,5,9,10,15] y = [0,1,2,3,4] plt.plot(x,y) plt.xticks(np.arange(min(x), max(x)+1, 1.0)) plt.show() 

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(np.arange was used rather than Python's range function just in case min(x) and max(x) are floats instead of ints.)

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The plt.plot (or ax.plot) function will automatically set default x and y limits. If you wish to keep those limits, and just change the stepsize of the tick marks, then you could use ax.get_xlim() to discover what limits Matplotlib has already set.

start, end = ax.get_xlim() ax.xaxis.set_ticks(np.arange(start, end, stepsize)) 

The default tick formatter should do a decent job rounding the tick values to a sensible number of significant digits. However, if you wish to have more control over the format, you can define your own formatter. For example,

ax.xaxis.set_major_formatter(ticker.FormatStrFormatter('%0.1f')) 

Here's a runnable example:

import numpy as np import matplotlib.pyplot as plt import matplotlib.ticker as ticker  x = [0,5,9,10,15] y = [0,1,2,3,4] fig, ax = plt.subplots() ax.plot(x,y) start, end = ax.get_xlim() ax.xaxis.set_ticks(np.arange(start, end, 0.712123)) ax.xaxis.set_major_formatter(ticker.FormatStrFormatter('%0.1f')) plt.show() 

Another approach is to set the axis locator:

import matplotlib.ticker as plticker  loc = plticker.MultipleLocator(base=1.0) # this locator puts ticks at regular intervals ax.xaxis.set_major_locator(loc) 

There are several different types of locator depending upon your needs.

Here is a full example:

import matplotlib.pyplot as plt import matplotlib.ticker as plticker  x = [0,5,9,10,15] y = [0,1,2,3,4] fig, ax = plt.subplots() ax.plot(x,y) loc = plticker.MultipleLocator(base=1.0) # this locator puts ticks at regular intervals ax.xaxis.set_major_locator(loc) plt.show() 

I like this solution (from the Matplotlib Plotting Cookbook):

import matplotlib.pyplot as plt import matplotlib.ticker as ticker  x = [0,5,9,10,15] y = [0,1,2,3,4]  tick_spacing = 1  fig, ax = plt.subplots(1,1) ax.plot(x,y) ax.xaxis.set_major_locator(ticker.MultipleLocator(tick_spacing)) plt.show() 

This solution give you explicit control of the tick spacing via the number given to ticker.MultipleLocater(), allows automatic limit determination, and is easy to read later.