Is there a maximum amount of ticklabels in a matplotlib axes? - python-3.x

Question

So I have two lists one containing a bunch of years and the other one containing some integers, each list has 17 values.
when I make a simple bar chart
plt.bar(keys,values)
plt.show()
in the X axis of the graph it only contains some of the years in the keys list eg: the graph only has 2000,2002,2005,2007,2010,2012,2015. It has missed 2001,2003,2006,2008,2009 etc.
Is it because there is a maximum amount of keys allowed in the bar chart so it randomly took some keys?
If not how do i fix this?

Answer 1

There is a maximum amount of ticklabels on a matplotlib axes. This limit however lies well above 1000 and you would first run into severe lags when creating the figure.
The usual automatic ticking by matplotlib is that the axes are equipped with just as many labels as needed. I.e. if you plot 50 points on a plot, you would not want to have 50 labels as well. Further if you plot a point at 0.853164 you would not want to have such odd number being displayed as ticklabel on the axes.
Now, I cannot think of any reason matplotlib would produce the labels you report about, 2000,2002,2005,2007,2010,2012,2015, because the automatic locator for the ticks chooses equidistant points on the axes. For any help with this specific problem, a MCVE would be needed.
But in general there are two concepts from which you may choose.
Numerical axes
When plotting numbers, matplotlib will by default choose a linear axes and tick it automatically as described above.
import matplotlib.pyplot as plt
import numpy as np
x = np.arange(2000, 2017)
y = np.random.randint(5,21, size=len(x))
plt.bar(x,y)
plt.show()
In this case an equidistant ticking of 2.5 units is chosen to have 7 nicely spaced ticks on the axes. If instead you would want to have every bar ticked, you could use a custom ticker.
E.g. a MultipleLocator with the interval set to 1,
import matplotlib.ticker as mticker
plt.gca().xaxis.set_major_locator(mticker.MultipleLocator(1))
plt.gca().tick_params(axis="x", rotation=90)
Or, a FixedLocator with the locations set to the x values of the bars,
import matplotlib.ticker as mticker
plt.gca().xaxis.set_major_locator(mticker.FixedLocator(x))
plt.gca().tick_params(axis="x", rotation=90)
Categorical axes
You may also decide that your xaxis shall be categorical. This means that every unique value gets its own tick and those ticks are equally spaced, independent of their value. This is easiest accomplished by converting the numbers to strings.
import matplotlib.pyplot as plt
import numpy as np
x = np.arange(2000, 2017)
y = np.random.randint(5,21, size=len(x))
cats = list(map(str, x))
plt.bar(cats,y)
plt.gca().tick_params(axis="x", rotation=90)
plt.show()
The result is visually the same as above, but this time, the number 2000 is not at location 2000, but at its index 0, 2001 is at 1 and so on.

Answer 2

You can show all the ticks in this way:
plt.xticks(np.arange(min(keys), max(keys)+1, 1.0), rotation=45)
Example:
keys = [2000, 2001,2002,2003,2004,2005,2006,2007,2008,2009,2010,2011,2012,2013,2014,2015,2016]
values = range(1,18)
import matplotlib.pyplot as plt
plt.bar(keys,values)
plt.xticks(np.arange(min(keys), max(keys)+1, 1.0), rotation=45)
plt.show()