如何用条形图绘制最小/最大条形

Question

我想调整我的绘图代码以显示最小/最大条形，如下图所示：

我的代码是：

from datetime import datetime, timedelta
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
sns.set_style("white")
sns.set_style('darkgrid',{"axes.facecolor": ".92"}) # (1)
sns.set_context('notebook')

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

Time = [87, 66, 90, 55]

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

display(df) # in jupyter

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

x = Delay
y = Time

plt.xlabel("Delay", size=14)
plt.ylim(-0.3, 100)
width = 0.1

for i, j in zip(x,y): 
    ax.bar(i,j, edgecolor = "black",
        error_kw=dict(lw=1, capsize=1, capthick=1))  
    ax.set(ylabel = 'Accuracy')

from matplotlib import ticker
ax.yaxis.set_major_locator(ticker.MultipleLocator(10)) 
plt.savefig("Try.png", dpi=300, bbox_inches='tight')

代码产生这个图：

我想添加的最小/最大是：

87 (60-90)
66 (40-70)
90 (80-93)
55 (23-60)

预先感谢您的帮助。

Answer 1

• 此答案通过包含 和 的示例扩展了上一个问题的代码。seaborn.barplotax.bar
• 另请参阅指定误差线的不同方法&matplotlib.pyplot.errorbar
• 测试于python 3.11, pandas 1.5.3, matplotlib 3.7.0,seaborn 0.12.2

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

• seaborn.barplot将自动添加误差线，如链接中的示例所示。然而，这是特定于使用许多数据点的。在这种情况下，一个值被指定为错误，但错误不是从数据中确定的。
  • 通过这种方式添加误差线时，capsize可以指定该参数，在误差线的顶部和底部添加水平线。

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}}

• 正如gepcel的答案中所述，该参数可用于显式向 API 提供错误。 yerr
  • 但是，您的错误格式对于参数来说不正确。yerr期望值与条形顶部相关
    • S1是 87，min是 60，max是 90。 因此，ymin是 27， (87-60)，ymax是 3， (90-87)。
• 该seaborn.barplot capsize参数似乎不适用于yerr，因此您必须设置matplotlib 'errorbar.capsize' rcParmas。请参阅Matplotlib 错误栏上限缺失

# 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

pandas.DataFrame.plot.bar

# 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)

ax.bar

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