如何绘制和注释分组条

How to plot and annotate grouped bars

我有以下代码

import numpy as np
import matplotlib.pyplot as plt

oct_data = [10, 24, 25, 30]
nov_data = [12, 42, 21, 78]

labels = ['Account_1', 'Account_2', 'Account_3', 'Account_4']
bar_width = 0.4

rect_1 = np.arange(0, len(oct_data)*2 ,2) 
rect_2 = [x + bar_width for x in rect_1]

plt.bar(rect_1, oct_data, color='#7f6d5f', width=bar_width, edgecolor='white', label='Month_1')
plt.bar(rect_2, nov_data, color='#557f2d', width=bar_width, edgecolor='white', label='Month_2')

plt.ylabel('Cost ($)', fontsize=10)

plt.legend()
plt.show()

这给了我下图:

如您所见,我的 xticks (Account_1, Account_2, ...) 没有居中。 据我了解,这个命令应该可以完成这项工作,但它没有。

plt.xticks([r + bar_width for r in range(0, len(oct_data)*2, 2)], labels)

我还想添加栏内的高度值。通常,这就是我使用“单条”图的方式:

  for i in range(len(labels)):
    plt.text(i, oct_data[i]//2, oct_data[i], ha = 'center', color = 'black')

但这在这里不起作用。

如有任何帮助,我们将不胜感激。我是 Matplotlib 的初学者。

您可以使用 align 个选项:

# number of data points
num_data = len(labels)

bars1 = plt.bar(range(num_data), oct_data, color='#7f6d5f', 
                align='edge', width=-bar_width,    # align and negative width for left bars
                edgecolor='white', label='Month_1')
bars1 = plt.bar(range(num_data), nov_data, color='#557f2d', 
                align='edge', width=bar_width,     # align and positive width for right bars
                edgecolor='white', label='Month_2')

# set xticks
plt.xticks(range(num_data), labels)

对于注释,建议有一个轴实例:

fig, ax = plt.subplots()
# other plot commands

for patch in ax.patches:
    ax.text(patch.get_x() + patch.get_width()/2,
            patch.get_height()/2,
            f'{patch.get_height()}',
            verticalalignment='center', horizontalalignment='center')

输出:


更新: 所有代码:

oct_data = [10, 24, 25, 30]
nov_data = [12, 42, 21, 78]

labels = ['Account_1', 'Account_2', 'Account_3', 'Account_4']
bar_width = 0.4

fig, ax = plt.subplots()

# number of data points
num_data = len(labels)

bars1 = plt.bar(range(num_data), oct_data, color='#7f6d5f', 
                align='edge', width=-bar_width,    # align and negative width for left bars
                edgecolor='white', label='Month_1')
bars1 = plt.bar(range(num_data), nov_data, color='#557f2d', 
                align='edge', width=bar_width,     # align and positive width for right bars
                edgecolor='white', label='Month_2')

for patch in ax.patches:
    ax.text(patch.get_x() + patch.get_width()/2,
            patch.get_height()/2,
            f'{patch.get_height()}',
            verticalalignment='center', horizontalalignment='center')

# set xticks
plt.xticks(range(num_data), labels)
plt.ylabel('Cost ($)', fontsize=10)

plt.legend()
plt.show()
  • 最简单的解决方案是使用 pandas。这将数据放在一个对象中,这很容易促进进一步的分析,并且绘图 API 正确地管理了分组条的间距。
    • 与 18 行代码相比,此实现仅使用 6 行代码。
  • 使用pandas.DataFrame.plot,它使用matplotlib作为默认绘图后端。列绘制为条形组,索引为独立轴。
  • matplotlib 3.4.2 开始,.bar_label 应该用于柱上的注释。
  • 有关分组条形图的其他示例,请参阅 Adding value labels on a matplotlib bar chart for addition information and examples about using .bar_label, and
  • 测试于 python 3.9.7pandas 1.3.4matplotlib 3.4.3
import pandas as pd
import matplotlib.pyplot as plt

# create a dict with the data
data = {'October': oct_data, 'November': nov_data}

# create the dataframe with the labels as the index
df = pd.DataFrame(data, index=labels)

# display(df)
           October  November
Account_1       10        12
Account_2       24        42
Account_3       25        21
Account_4       30        78

# plot the dataframe
ax = df.plot(kind='bar', figsize=(10, 6), rot=0, ylabel='Cost ($)', color=['#7f6d5f', '#557f2d'])

# iterate through each group of container (bar) objects
for c in ax.containers:

    # annotate the container group
    ax.bar_label(c, label_type='center')

plt.show()