如何自定义条形注释以不显示选定值
How to customize bar annotations to not show selected values
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]
有没有办法从条形图中删除 0.0 标签?
我尝试了 df = df.replace(0, "")
,但后来我收到 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()
labels
传递给 matplotlib.pyplot.bar_label
必须自定义
- 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 ]
没有赋值表达式 (:=
).
- 请参阅此 answer 了解更多详细信息和使用
.bar_label
的示例
- 在
pandas 1.3.4
、python 3.8.12
1. 和 matplotlib 3.4.3
1.[ 中测试=42=]
- 所需的最低版本分别为 3.8 和 3.4.2
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', 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)
ax.legend(title='Columns', bbox_to_anchor=(1, 1.02), loc='upper left')
plt.show()
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]
有没有办法从条形图中删除 0.0 标签?
我尝试了 df = df.replace(0, "")
,但后来我收到 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()
labels
传递给matplotlib.pyplot.bar_label
必须自定义- 根据需要调整比较 (
!= 0
) 值或范围。
- 根据需要调整比较 (
labels = [f'{v.get_height():0.0f}' if v.get_height() != 0 else '' for v in c ]
没有赋值表达式 (:=
).- 请参阅此 answer 了解更多详细信息和使用
.bar_label
的示例
- 在
pandas 1.3.4
、python 3.8.12
1. 和matplotlib 3.4.3
1.[ 中测试=42=]- 所需的最低版本分别为 3.8 和 3.4.2
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', 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)
ax.legend(title='Columns', bbox_to_anchor=(1, 1.02), loc='upper left')
plt.show()