我正在嘗試為條形圖顯示自定義圖例，但它僅顯示圖例串列中的第一個圖例。如何顯示圖例中的所有值？
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)
uj5u.com熱心網友回復：
讓我們使用ax.get_legend_handles_labels以下命令從軸獲取補丁句柄：
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)
輸出：
uj5u.com熱心網友回復：
為了創建自動圖例，matplotlib 存盤圖形元素的標簽。在此條形圖中，完整的“容器”熊貓為完整的“容器”分配一個標簽。
您可以洗掉容器的標簽（分配一個以 開頭的標簽_），并為條形分配單獨的標簽。可以使用 xtick 標簽，因為它們已經按所需順序排列。
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()
通過少一點內部操作，可以通過 seaborn 獲得類似的東西：
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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標籤：Python 熊猫 matplotlib
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