python可视化stackplot函数用法-绘制堆积面积图。
matplotlib.pyplot.stackplot(x, *args, labels=(), colors=None, baseline=’zero’, data=None, **kwargs)
堆栈图的思想是随着时间的推移显示“部分到整体”。它用于表示各种数据集而不会彼此重叠。
Stackplot用于绘制堆积面积图。它显示完整的数据以进行可视化。它显示了每个零件相互堆叠以及每个零件如何构成完整的图形。它显示数据的各种组成部分，其行为类似于饼图。它具有x-label，y-label和标题，其中各个部分可以用不同的颜色表示。
效果如图展示：
源码附上:
import matplotlib.pyplot as plt
# List of Days
days = [1, 2, 3, 4, 5]
# No of Study Hours
Studying = [7, 8, 6, 11, 7]
# No of Playing Hours
playing = [8, 5, 7, 8, 13]
# Stackplot with X, Y, colors value
plt.stackplot( days, Studying, playing,
colors=['r', 'c'] )
# Days
plt.xlabel( 'Days' )
# No of hours
plt.ylabel( 'No of Hours' )
# Title of Graph
plt.title( 'Representation of Study and \
Playing wrt to Days' )
# Displaying Graph
plt.show()
范例＃2：使用Stackplot
源码附上：
import matplotlib.pyplot as plt
# List of 7-days
days = [x for x in range( 0, 7 )]
# List of Suspected cases
Suspected = [12, 18, 35, 50, 72, 90, 100]
# List of Cured Cases
Cured = [4, 8, 15, 22, 41, 55, 62]
# List of Number of deaths
Deaths = [1, 3, 5, 7, 9, 11, 13]
# Plot x-labels, y-label and data
plt.plot( [], [], color='blue',
label='Suspected' )
plt.plot( [], [], color='orange',
label='Cured' )
plt.plot( [], [], color='brown',
label='Deaths' )
# Implementing stackplot on data
plt.stackplot( days, Suspected, Cured,
Deaths, baseline='zero',
colors=['blue', 'orange',
'brown'] )
plt.legend()
plt.title( 'No of Cases' )
plt.xlabel( 'Day of the week' )
plt.ylabel( 'Overall cases' )
plt.show()
输出：
如果基线值设置为零，则下面的图表表示输出
原文链接：https://vimsky.com/examples/usage/matplotlib-pyplot-stackplot-in-python.html