• 此答案扩展了以前question中的代码，包括seaborn.barplot和ax.bar的示例。
• 另请参见Different ways of specifying error bars和matplotlib.pyplot.errorbar
• • • 在python 3.11、pandas 1.5.3、matplotlib 3.7.0、seaborn 0.12.2中进行测试**

import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns

# set edgecolor param (this is a global setting, so only set it once)
plt.rcParams["patch.force_edgecolor"] = True

# setup the dataframe
Delay = ['S1', 'S2', 'S3', 'S4']

Time = [87, 66, 90, 55]

df = pd.DataFrame({'Delay':Delay,'Time':Time})

# create a dict for the errors
error = {87: {'max': 90,'min': 60}, 66: {'max': 70,'min': 40}, 90: {'max': 93,'min': 80}, 55: {'max': 60,'min': 23}}

∮ ∮ ∮ ∮ ∮

• seaborn.barplot将自动添加误差线，如链接中的示例所示。但是，这是特定于使用许多数据点的。在这种情况下，将一个值指定为误差，而不是根据数据确定误差。
• 以这种方式添加误差线时，可以指定capsize参数，以便在误差线的顶部和底部添加水平线。

# plot the figure
fig, ax = plt.subplots(figsize=(8, 6))
sns.barplot(x='Delay', y='Time', data=df, ax=ax)

# add the lines for the errors 
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 = error[h]['min']  # use h to get min from dict z
    max_y = error[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gepcel中的answer所示，yerr参数可用于显式地向API提供错误。
• 但是，错误的格式对于参数不正确。yerr要求值与条形的顶部相关
• S1为87，min为60，max为90。因此，ymin为27（87 - 60），ymax为3（90 - 87）。
• seaborn.barplotcapsize参数似乎不适用于yerr，因此必须设置matplotlib'errorbar.capsize'rcParmas。

# set capsize param (this is a global setting, so only set it once)
plt.rcParams['errorbar.capsize'] = 10

# create dataframe as shown by gepcel
Delay = ['S1', 'S2', 'S3', 'S4']

Time = [87, 66, 90, 55]
_min = [60, 40, 80, 23]
_max = [90, 70, 93, 60]
df = pd.DataFrame({'Delay':Delay,'Time':Time, 'Min': _min, 'Max': _max})

# create ymin and ymax
df['ymin'] = df.Time - df.Min
df['ymax'] = df.Max - df.Time

# extract ymin and ymax into a (2, N) array as required by the yerr parameter
yerr = df[['ymin', 'ymax']].T.to_numpy()

# plot with error bars
fig, ax = plt.subplots(figsize=(8, 6))
sns.barplot(x='Delay', y='Time', data=df, yerr=yerr, ax=ax)

∮ ∮ ∮ ∮ ∮

fig, ax = plt.subplots(figsize=(8, 6))

df.plot.bar(x='Delay', y='Time', ax=ax)

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 = error[h]['min']  # use h to get min from dict z
    max_y = error[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

一米二十四分一秒

fig, ax = plt.subplots(figsize=(8, 6))

ax.bar(x='Delay', height='Time', data=df)

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 = error[h]['min']  # use h to get min from dict z
    max_y = error[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

你可以直接使用plt.bar的yerr参数，以@特伦顿McKinney的代码为例：

import pandas as pd
import matplotlib.pyplot as plt

# setup the dataframe
Delay = ['S1', 'S2', 'S3', 'S4']

Time = [87, 66, 90, 55]
_min = [60, 40, 80, 23]
_max = [90, 70, 93, 60]
df = pd.DataFrame({'Delay':Delay,'Time':Time, 'Min': _min, 'Max': _max})
df = (df.assign(yerr_min = df.Time-df.Min)
        .assign(yerr_max=df.Max-df.Time))

plt.figure(figsize=(8, 6))
plt.bar(x='Delay', height='Time', yerr=df[['yerr_min', 'yerr_max']].T.values, capsize=10, data=df)

plt.show()

下面是一个使用yerr和numpy的解决方案，它比@gepcel的样板代码少。

import matplotlib.pyplot as plt
import numpy as np

Delay = ['S1', 'S2', 'S3', 'S4']   # Categories

Time = [87, 66, 90, 55]
_min = [60, 40, 80, 23]
_max = [90, 70, 93, 60]

plt.figure(figsize=(8, 6))

yerr = [np.subtract(Time, _min), np.subtract(_max, Time)]
plt.bar(Delay, Time, yerr=yerr, capsize=10)

plt.show()