python matplotlib create 2 subplot sharing axes properties

Question

I am creating a figure with 2 subplots using the following code:

fig, (ax1, ax2) = plt.subplots(2, sharex = True, figsize=(20, 6)) 

mpf.candlestick_ohlc(ax1,quotes, width=0.01)
ax1.xaxis_date()
ax1.xaxis.set_major_locator(mpl.dates.DayLocator(interval=1) )
ax1.xaxis.set_major_formatter(mpl.dates.DateFormatter('%a, %b %d \'%y'))
ax1.xaxis.set_minor_locator(mpl.dates.HourLocator(byhour=range(0,24,4)))
ax1.xaxis.set_minor_formatter(mpl.dates.DateFormatter('%-H'))
ax1.grid(True)
ax1.grid(b=True, which='minor', color='0.7', linestyle='dotted')
ax2.tick_params(direction='out', pad=15)

majors=ax1.xaxis.get_majorticklocs()
chart_start, chart_end = (ax1.xaxis.get_view_interval()[0],ax1.xaxis.get_view_interval()[1])
for major in majors:
    ax1.axvspan(max (chart_start, major-(0.3333)),min(chart_end, major+(0.3333)),color="0.95", zorder=-1 )

plt.bar(quotes[:,0] , quotes[:, 5], width = 0.01)

plt.show()

Here the resulting figure:

I would like the subplot at the bottom to have the same grid, major/ minor ticks and axvspan as the subplot above. I could rewrite all the ax1... lines changing ax1 for ax2 , but i suspect there might be a way to assign the different elements (ie grid, minor/major ticks and axvspan) to both axes in 1 go?

jim jarnac · Accepted Answer · 2016-12-31 03:21:58Z

ok found it:

fig, (axes) = plt.subplots(2, sharex = True, figsize=(20, 6))

mpf.candlestick_ohlc(axes[0],quotes, width=0.01)
plt.bar(quotes[:,0] , quotes[:, 5], width = 0.01)

for i , axes[i] in enumerate(axes):
    axes[i].xaxis_date(tz="Europe/Berlin")
    axes[i].xaxis.set_major_locator(mpl.dates.DayLocator(interval=1) )
    axes[i].xaxis.set_major_formatter(mpl.dates.DateFormatter('%a, %b %d \'%y'))
    axes[i].xaxis.set_minor_locator(mpl.dates.HourLocator(byhour=range(0,24,4)))
    axes[i].xaxis.set_minor_formatter(mpl.dates.DateFormatter('%-H'))
    axes[i].tick_params(direction='out', pad=15)
    axes[i].grid(True)
    axes[i].grid(b=True, which='minor', color='0.7', linestyle='dotted')

    majors=axes[i].xaxis.get_majorticklocs()
    chart_start, chart_end = (axes[i].xaxis.get_view_interval()[0], axes[i].xaxis.get_view_interval()[1])
    for major in majors:
        axes[i].axvspan(max (chart_start, major-(0.3333)),min(chart_end, major+(0.3333)),color="0.95", zorder=-1 )

plt.show()

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