Question

Given this 3D bar graph sample code, how would you convert the numerical data in the x-axis to formatted date/time strings? I ve attempted using the ax.xaxis_date() function without success. I also tried using plot_date(), which doesn t appear to work for 3D bar graphs. Here is a modified version of the sample code to illustrate what I am trying to do:

from mpl_toolkits.mplot3d import Axes3D
import matplotlib.pyplot as plt
import numpy as np
import matplotlib.dates as dates

dates = [dates.date2num(datetime.datetime(2009,3,12)),
         dates.date2num(datetime.datetime(2009,6,9)),
         dates.date2num(datetime.datetime(2010,1,1)),
         #etc...
         ]

fig = plt.figure()
ax = Axes3D(fig)
for c, z in zip([ r ,  g ,  b ,  y ], [30, 20, 10, 0]):
    xs = np.array(dates)
    ys = np.random.rand(20)
    ax.bar(xs, ys, zs=z, zdir= y , color=c, alpha=0.8)

ax.set_xlabel( Date & Time )
ax.set_ylabel( Series )
ax.set_zlabel( Amount )

plt.show()

Answer 1

There might be some confusion here, the Axes3D has the properties w_xaxis, w_yaxis and w_zaxis for the axises instead of the usual x-axis, y-axis, etc.

Tested in python 3.8.11, matplotlib 3.4.3

from mpl_toolkits.mplot3d import Axes3D
import matplotlib.pyplot as plt
import numpy as np
import matplotlib.dates as dates
import datetime, random
import matplotlib.ticker as ticker

def random_date():
    date = datetime.date(2008, 12, 1)
    while 1:
        date += datetime.timedelta(days=30)
        yield (date)

def format_date(x, pos=None):
    return dates.num2date(x).strftime( %Y-%m-%d ) #use FuncFormatter to format dates

r_d = random_date()
some_dates = [dates.date2num(next(r_d)) for i in range(0,20)]

fig = plt.figure(figsize=(10, 10))
ax = fig.add_subplot(projection= 3d )

for c, z in zip([ r ,  g ,  b ,  y ], [30, 20, 10, 0]):
    xs = np.array(some_dates)
    ys = np.random.rand(20)
    ax.bar(xs, ys, zs=z, zdir= y , color=c, alpha=0.8,width=8)

ax.w_xaxis.set_major_locator(ticker.FixedLocator(some_dates)) # I want all the dates on my xaxis
ax.w_xaxis.set_major_formatter(ticker.FuncFormatter(format_date))
for tl in ax.w_xaxis.get_ticklabels(): # re-create what autofmt_xdate but with w_xaxis
    tl.set_ha( right )
    tl.set_rotation(30)     

ax.set_ylabel( Series )
ax.set_zlabel( Amount )

plt.show()

Produces:

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