from __future__ import print_function
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.mlab as mlab
import matplotlib.cbook as cbook
import matplotlib.ticker as ticker

datafile = cbook.get_sample_data('aapl.csv', asfileobj=False)
print('loading %s' % datafile)
r = mlab.csv2rec(datafile)

r.sort()
r = r[-30
 
:]  # get the last 30 days


# first we'll do it the default way, with gaps on weekends
fig, ax = plt.subplots()
ax.plot(r.date, r.adj_close, 'o-')
fig.autofmt_xdate()

# next we'll write a custom formatter
N = len(r)
ind = np.arange(N)  # the evenly spaced plot indices


def format_date(x, pos=None)
 
:
    thisind = np.clip(int(x + 0.5), 0, N - 1)
    return r.date[thisind].strftime('%Y-%m-%d')

fig, ax = plt.subplots()
ax.plot(ind, r.adj_close, 'o-')
ax.xaxis.set_major_formatter(ticker.FuncFormatter(format_date))
fig.autofmt_xdate()

plt.show()

Julia的程式碼難點在哪裡？

using PyPlot;
clf();
close();
fig =figure();
ax = fig[:add_subplot
 
](111)  # 或 fig, ax = PyPlot.subplots() 
x = [Date(now()) + Dates.Day(i) for i in collect(1:100)] # 日期圖
y = rand(100) 
ax[:plot](x,y, color="red", linewidth=2.0, linestyle="-") 

fig[:autofmt_xdate]()# x軸的日期是預設格式安排

要變成其它的日期格式（2016-05-06）那需要如何處理？

ax.xaxis.set_major_formatter(ticker.FuncFormatter(format_date))

=>???????

ax[:xaxis][:set_major_formatter]