也许这就是你需要的：

import matplotlib.pyplot as plt

collectn_1 = [0.1,0.3]
collectn_2 = [0.5,0.6]
collectn_3 = [0.6,1]
collectn_4 = [0.6,0.7]

## combine these different collections into a list
data_to_plot = [collectn_1, collectn_2, collectn_3, collectn_4]

# Create a figure instance
fig = plt.figure()

# Create an axes instance
ax = fig.add_axes([0,0,1,1])

# Create the boxplot
bp = ax.violinplot(data_to_plot)
plt.show()

可以使用plt.bar：

fig, ax = plt.subplots()

ax.bar(x=df['title'], 
       bottom=df['value_1'], 
       height=df['value_2'] - df['value_1'])

ax.set_ylim(bottom=0, top=1.2)
new_yticks = list(set(df['value_1']).union(df['value_2']))
plt.yticks(new_yticks)
plt.show()

或者如@LuisAlejandro所建议的，您可以使用ax.violinplot，但您必须首先从嵌套框中提取值：

vals = list(df[['value_1', 'value_2']].T.to_dict('list').values())
# [[0.1, 0.3], [0.5, 0.6], [1.0, 0.6], [0.6, 0.7]]

fig, ax = plt.subplots()

ax.violinplot(vals)

ax.set_ylim(bottom=0, top=1.2)
plt.yticks(new_yticks)
plt.show()