If you don’t want to change the spacing globally (by editing your rcParams), and want a cleaner approach, try this: ax.tick_params(axis=”both”, which=”major”, pad=15) or for just x axis ax.tick_params(axis=”x”, which=”major”, pad=15) or the y axis ax.tick_params(axis=”y”, which=”major”, pad=15)
Whatever reason it is you are getting 2 ticks only by default, you can fix it (customise it) by changing the ticker locator using a date locator. import matplotlib.pyplot as plt import matplotlib.dates as mdates x = [ datetime.datetime(1900,1,1,0,1,2), datetime.datetime(1900,1,1,0,1,3), … ] # ( more than 1000 elements ) y = [ 34, 33, 23, … Read more
solution for matplotlib >= 2.0.2 Let’s consider the following example which is produced by this code: import matplotlib.pyplot as plt import matplotlib.ticker import numpy as np y = np.arange(12) x = 10.0**y fig, ax=plt.subplots() ax.plot(x,y) ax.set_xscale(“log”) plt.show() The minor ticklabels are indeed gone and usual ways to show them (like plt.tick_params(axis=”x”, which=”minor”)) fail. The first … Read more
IIUC you can format the xticks and set these: In[60]: #generate some psuedo data df = pd.DataFrame({‘num’:[50000, 75000, 100000, 125000], ‘Rent/Sqft’:np.random.randn(4), ‘Region’:list(‘abcd’)}) df Out[60]: num Rent/Sqft Region 0 50000 0.109196 a 1 75000 0.566553 b 2 100000 -0.274064 c 3 125000 -0.636492 d In[61]: import matplotlib.pyplot as plt import matplotlib.ticker as ticker import seaborn as … Read more
There is a simpler way actually. I just found: import matplotlib.pyplot as plt # We prepare the plot fig, ax = plt.subplots() # We change the fontsize of minor ticks label ax.tick_params(axis=”both”, which=”major”, labelsize=10) ax.tick_params(axis=”both”, which=”minor”, labelsize=8) This only answers to the size of label part of your question though.
The labels are centered at the tickmark position. Their bounding boxes are unequal in width and might even overlap, which makes them look unequally spaced. Since you’d always want the ticklabels to link to their tickmarks, changing the spacing is not really an option. However you might want to align them such the the upper … Read more
I had exactly the same problem, and these lines fixed the problem: from matplotlib.ticker import ScalarFormatter y_formatter = ScalarFormatter(useOffset=False) ax.yaxis.set_major_formatter(y_formatter)
There are several problems in your code. First the big ones: You are creating a new figure and a new axes in every iteration of your loop → put fig = plt.figure and ax = fig.add_subplot(1,1,1) outside of the loop. Don’t use the Locators. Call the functions ax.set_xticks() and ax.grid() with the correct keywords. With … Read more
If you prefer a non-object-oriented approach, move plt.xticks(rotation=70) to right before the two avail_plot calls, eg plt.xticks(rotation=70) avail_plot(axs[0], dates, s1, ‘testing’, ‘green’) avail_plot(axs[1], dates, s1, ‘testing2’, ‘red’) This sets the rotation property before setting up the labels. Since you have two axes here, plt.xticks gets confused after you’ve made the two plots. At the point … Read more
The plt.tick_params method is very useful for stuff like this. This code turns off major and minor ticks and removes the labels from the x-axis. Note that there is also ax.tick_params for matplotlib.axes.Axes objects. from matplotlib import pyplot as plt plt.plot(range(10)) plt.tick_params( axis=”x”, # changes apply to the x-axis which=”both”, # both major and minor … Read more