matplotlib 如何自定义条形图注解以不显示选定值

7kqas0il 于 2023-11-22 发布在其他

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我有以下数据集：

data = [6.92, 1.78, 0.0, 0.0, 3.5, 8.82, 3.06, 0.0, 0.0, 5.54, -10.8, -6.03, 0.0, 0.0, -6.8, 13.69, 8.61, 9.98, 0.0, 9.42, 4.91, 3.54, 2.62, 5.65, 1.95, 8.91, 11.46, 5.31, 6.93, 6.42]

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有没有办法从条形图中删除0.0标签？

的数据
我尝试了df = df.replace(0, "")，但我得到了一个list index out of range错误代码。
我的代码：

import pandas as pd
import matplotlib.pyplot as plt
import numpy as np

data = [6.92, 1.78, 0.0, 0.0, 3.5, 8.82, 3.06, 0.0, 0.0, 5.54, -10.8, -6.03, 0.0, 0.0, -6.8, 13.69, 8.61, 9.98, 0.0, 9.42, 4.91, 3.54, 2.62, 5.65, 1.95, 8.91, 11.46, 5.31, 6.93, 6.42]

df = pd.DataFrame(np.array(data).reshape(6,5), columns=['Bank1', 'Bank2', 'Bank3', 'Bank4', 'Bank5'], index =['2016', '2017', '2018', '2019', '2020', '2021'])

print(df)
ax = df.plot(kind='bar', rot=0, xlabel='Year', ylabel='Total Return %', title='Overall Performance', figsize=(15, 10))

ax.bar_label(ax.containers[0], fmt='%.1f', fontsize=8, padding=3)
ax.bar_label(ax.containers[1], fmt='%.1f', fontsize=8, padding=3)
ax.bar_label(ax.containers[2], fmt='%.1f', fontsize=8, padding=3)
ax.bar_label(ax.containers[3], fmt='%.1f', fontsize=8, padding=3)
ax.bar_label(ax.containers[4], fmt='%.1f', fontsize=8, padding=3)

ax.legend(title='Columns', bbox_to_anchor=(1, 1.02), loc='upper left')
plt.show()

型

matplotlib

来源：https://stackoverflow.com/questions/69933583/how-to-customize-bar-annotations-to-not-show-selected-values

1条答案

按热度按时间

kkih6yb81#

必须自定义传递到matplotlib.pyplot.bar_label的labels
根据需要调整比较（!= 0）值或范围。
labels = [f'{v.get_height():0.0f}' if v.get_height() != 0 else '' for v in c ]不带赋值表达式（:=）。
有关使用.bar_label的其他详细信息和示例，请参见this answer。
*在python v3.12.0，pandas v2.1.2，matplotlib v3.8.1中测试。

import pandas as pd
import matplotlib.pyplot as plt

data = [6.92, 1.78, 0.0, 0.0, 3.5, 8.82, 3.06, 0.0, 0.0, 5.54, -10.8, -6.03, 0.0, 0.0, -6.8, 13.69, 8.61, 9.98, 0.0, 9.42, 4.91, 3.54, 2.62, 5.65, 1.95, 8.91, 11.46, 5.31, 6.93, 6.42]

df = pd.DataFrame(np.array(data).reshape(6,5), columns=['Bank1', 'Bank2', 'Bank3', 'Bank4', 'Bank5'], index =['2016', '2017', '2018', '2019', '2020', '2021'])

ax = df.plot(kind='bar', rot=0, xlabel='Year', ylabel='Total Return %', title='Overall Performance', width=0.9, figsize=(15, 10))

for c in ax.containers:
    
    # customize the label to account for cases when there might not be a bar section
    labels = [f'{h:0.1f}' if (h := v.get_height()) != 0 else '' for v in c ]
    
    # set the bar label
    ax.bar_label(c, labels=labels, fontsize=8, padding=3)

    # from matplotlib 3.7, the following options with fmt also work
    # ax.bar_label(c, fmt=lambda x: np.where(x != 0, x, ''), fontsize=8, padding=3)
    # ax.bar_label(c, fmt=lambda x: f'{x:0.2f}' if x != 0 else '', fontsize=8, padding=3)

ax.legend(title='Banks', bbox_to_anchor=(1, 0.5), loc='center left', frameon=False)
plt.show()

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matplotlib 如何自定义条形图注解以不显示选定值

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