matplotlib中的图例仅显示列表的第一个条目
matplotlib中的图例仅显示列表的第一个条目
提问于 2021-11-18 20:44:18
我正在尝试显示条形图的自定义图例，但它只显示图例列表中的第一个图例。如何显示图例中的所有值？
df.time_to_travel_grouping.value_counts().plot(kind="bar",
color = ["b","tab:green","tab:red","c","m","y","tab:blue","tab:orange"],
xlabel="TTT", ylabel="Total Counts",
title="Fig4: Total Counts by Time to Travel Category (TTT)", figsize=(20,15))
plt.legend(["a","b","c","d","e","f","g","h"])
plt.subplots_adjust(bottom=0.15)
plt.subplots_adjust(left=0.15)
回答 2
Stack Overflow用户
回答已采纳
发布于 2021-11-18 21:02:03
让我们使用ax.get_legend_handles_labels从轴获取补丁句柄
s = pd.Series(np.arange(100,50,-5), index=[*'abcdefghij'])
ax = s.plot(kind="bar",
color = ["b","tab:green","tab:red","c","m","y","tab:blue","tab:orange"],
xlabel="TTT", ylabel="Total Counts",
title="Fig4: Total Counts by Time to Travel Category (TTT)", figsize=(20,15))
patches, _ = ax.get_legend_handles_labels()
labels = [*'abcdefghij']
ax.legend(*patches, labels, loc='best')
plt.subplots_adjust(bottom=0.15)
plt.subplots_adjust(left=0.15)输出：
Stack Overflow用户
发布于 2021-11-18 21:30:39
要创建自动图例，matplotlib会存储图形元素的标签。在这个柱状图的情况下，完整的“容器”熊猫为完整的“容器”分配了一个标签。
您可以移除容器的标签(指定以_开头的标签)，然后将各个标签指定给条形。可以使用xtick标签，因为它们已经是所需的顺序。
import matplotlib.pyplot as plt
import pandas as pd
import numpy as np
df = pd.DataFrame({'time_to_travel_grouping': np.random.choice([*'abcdefgh'], 200)})
ax = df.time_to_travel_grouping.value_counts().plot(kind="bar",
color=["b", "tab:green", "tab:red", "c", "m", "y", "tab:blue", "tab:orange"],
xlabel="TTT", ylabel="Total Counts",
title="Fig4: Total Counts by Time to Travel Category (TTT)",
figsize=(20, 15))
ax.containers[0].set_label('_nolegend')
for bar, tick_label in zip(ax.containers[0], ax.get_xticklabels()):
bar.set_label(tick_label.get_text())
ax.legend()
plt.tight_layout()
plt.show()
通过更少的内部操作，可以通过seaborn获得类似的结果：
import matplotlib.pyplot as plt
import pandas as pd
import numpy as np
import seaborn as sns
df = pd.DataFrame({'time_to_travel_grouping': np.random.choice([*'abcdefgh'], 200)})
plt.figure(figsize=(20, 15))
ax = sns.countplot(data=df, x='time_to_travel_grouping', hue='time_to_travel_grouping',
palette=["b", "tab:green", "tab:red", "c", "m", "y", "tab:blue", "tab:orange"],
order=df.time_to_travel_grouping.value_counts().index,
dodge=False)
plt.setp(ax, xlabel="TTT", ylabel="Total Counts", title="Fig4: Total Counts by Time to Travel Category (TTT)")
plt.tight_layout()
plt.show()
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原文链接：
https://stackoverflow.com/questions/70026518
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