python数据可视化之matplotlib精进,Python数据可视化之matplotlib实践 源码 第二篇 精进 第五章...

图 5.1

importmatplotlib.pyplot as pltimportnumpy as npfrom matplotlib.ticker importAutoMinorLocator, MultipleLocator, FuncFormatter

x=np.linspace(0.5, 3.5, 100)

y=np.sin(x)

fig=plt.figure(figsize=(8, 8))

ax=fig.add_subplot(111)

ax.xaxis.set_major_locator(MultipleLocator(1.0))

ax.yaxis.set_major_locator(MultipleLocator(1.0))

ax.xaxis.set_minor_locator(AutoMinorLocator(4))

ax.yaxis.set_minor_locator(AutoMinorLocator(4))defminor_tick(x, pos):if not x%1.0:return ""

return "%.2f"%x

ax.xaxis.set_minor_formatter(FuncFormatter(minor_tick))

ax.tick_params("y", which='major',length=15, width=2.0, colors='r')

ax.tick_params(which='minor', length=5, width=1.0, labelsize=10, labelcolor='0.25')

ax.set_xlim(0,4)

ax.set_ylim(0,2)

ax.plot(x, y, c=(0.25, 0.25, 1.00), lw=2, zorder=10)#ax.plot(x, y, c=(0.25, 0.25, 1.00), lw=2, zorder=0)

ax.grid(linestyle='-', linewidth=0.5, color='r', zorder=0)#ax.grid(linestyle='-', linewidth=0.5, color='r', zorder=10)#ax.grid(linestyle='--', linewidth=0.5, color='0.25', zorder=0)

plt.show()

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图 5.2

importmatplotlib.pyplot as pltimportnumpy as np

fig=plt.figure(facecolor=(1.0, 1.0, 0.9412))

ax=fig.add_axes([0.1, 0.4, 0.5, 0.5])for ticklabel inax.xaxis.get_ticklabels():

ticklabel.set_color("slateblue")

ticklabel.set_fontsize(18)

ticklabel.set_rotation(30)for ticklabel inax.yaxis.get_ticklabels():

ticklabel.set_color("lightgreen")

ticklabel.set_fontsize(20)

ticklabel.set_rotation(2)

plt.show()

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图 5.3

importmatplotlib.pyplot as pltimportnumpy as npfrom calendar importmonth_name, day_namefrom matplotlib.ticker importFormatStrFormatter

fig=plt.figure()

ax=fig.add_axes([0.2, 0.2, 0.7, 0.7])

x=np.arange(1, 8, 1)

y=2*x

ax.plot(x, y, ls='-', lw=2, color='orange', marker='o',

ms=20, mfc='c', mec='r')

ax.yaxis.set_major_formatter(FormatStrFormatter(r"$yen%1.1f$"))

plt.xticks(x, day_name[0:7], rotation=20)

ax.set_xlim(0,8)

ax.set_ylim(0,18)

plt.show()

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图 5.4

importmatplotlib.pyplot as pltimportnumpy as np

x=np.linspace(0.5, 3.5, 100)

y=np.sin(x)

fig=plt.figure(figsize=(8, 8))

ax=fig.add_subplot(111)

ax.plot(x, y, c='b', ls='-', lw=2)

ax.annotate("maximum", xy=(np.pi/2, 1.0), xycoords='data',

xytext=((np.pi/2)+0.15, 0.8), textcoords="data",

weight="bold", color='r',

arrowprops=dict(arrowstyle='->', connectionstyle='arc3', color='r'))

ax.text(2.8, 0.4, "$y=sin(x)$", fontsize=20, color='b',

bbox=dict(facecolor='y', alpha=0.5))

plt.show()

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图 5.5

来源：oschina

链接：https://my.oschina.net/u/4389867/blog/4288097