- 为了在条形图上的正确位置进行绘图,必须提取每个条形的补丁数据。
- 返回一个
ndarray,每列一个matplotlib.axes.Axes。
- 条形图的
height 用于从dict、z 中提取正确的min 和max 值。
- 很遗憾,补丁数据不包含条形标签(例如
Delay & Latency)。
import pandas as pd
import matplotlib.pyplot as plt
# create dataframe
Delay = (53.46, 36.22, 83, 17)
Latency = (38, 44, 53, 10)
index = ['T=0', 'T=26', 'T=50','T=900']
df = pd.DataFrame({'Delay': Delay, 'Latency': Latency}, index=index)
# dicts with errors
Delay_error = {53.46: {'min': 0,'max': 60}, 36.22: {'min': 12,'max': 70}, 83: {'min': 21,'max': 54}, 17: {'min': 12,'max': 70}}
Latency_error = {38: {'min': 2, 'max': 70}, 44: {'min': 12,'max': 87}, 53: {'min': 9,'max': 60}, 10: {'min': 11,'max': 77}}
# combine them; providing all the keys are unique
z = {**Delay_error, **Latency_error}
# plot
ax = df.plot.bar(rot=0)
plt.xlabel('Time')
plt.ylabel('(%)')
plt.ylim(0, 101)
for p in ax.patches:
x = p.get_x() # get the bottom left x corner of the bar
w = p.get_width() # get width of bar
h = p.get_height() # get height of bar
min_y = z[h]['min'] # use h to get min from dict z
max_y = z[h]['max'] # use h to get max from dict z
plt.vlines(x+w/2, min_y, max_y, color='k') # draw a vertical line
- 如果两个
dicts中有非唯一值,无法合并,我们可以根据柱状图顺序选择正确的dict。
- 首先绘制单个标签的所有条形图。
- 在这种情况下,索引 0-3 是
Dalay 柱,索引 4-7 是 Latency 柱
for i, p in enumerate(ax.patches):
print(i, p)
x = p.get_x()
w = p.get_width()
h = p.get_height()
if i < len(ax.patches)/2: # select which dictionary to use
d = Delay_error
else:
d = Latency_error
min_y = d[h]['min']
max_y = d[h]['max']
plt.vlines(x+w/2, min_y, max_y, color='k')