如何使用条形图绘制最小/最大条形图

Question

我想修改我的绘图代码，以显示下图所示的最小/最大条形图：

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')

代码生成此图：

我要添加的最小/最大值用于：

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

提前谢谢你的帮助

Answer 1

• 这个答案通过包含seaborn.barplot和ax.bar的示例，扩展了前面question中的代码
• 另见Different ways of specifying error bars&^{}

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将自动添加错误条，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，指定一个值作为错误，而不是根据数据确定错误。
  • 以这种方式添加错误条时，可以指定capsize参数，以便在错误条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answerfrom gepcel中所述，yerr参数可用于显式地向API提供错误。
  • 但是，参数的错误格式不正确yerr期望值与条的顶部相关
    • S1为87，其中{}或60和{}为90。因此，ymin是27，（87-60），而ymax是3，（90-87）
• seaborn.barplotcapsize参数似乎不适用于yerr，因此必须设置matplotlib{}{}。见Matplotlib Errorbar Caps Missing

# 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', 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

ax.bar

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

Answer 2

您可以直接使用plt.bar的yerrarg。以@Trenton 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()

Answer 3

这里有一个使用yerr和numpy的解决方案。它的样板代码比@gepcel的少

import matplotlib.pyplot as plt
import numpy as np

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

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()