如何将一个传奇人物与两个海洋小号相结合？

发布于 2025-01-31 10:41:10 字数 619 浏览 2 评论 0原文

我想拥有一个非常适合两个子图顶部的传奇（不一定需要跨越剧情的整个宽度，而需要在图之外）。我知道您可以使用bbox_to_anchor（），但某种程度上似乎无法正常工作。它总是将一个子图移开。

fig, ax = plt.subplots(1, 2)
sns.barplot(x="day", y="total_bill", hue="sex", data=tips, ax = ax[0])
ax[0].legend_.remove()
sns.barplot(x="day", y="total_bill", hue="sex", data=tips, ax = ax[1])
sns.move_legend(ax[1], loc = "center", bbox_to_anchor=(-0.5, 1.1), ncol=2, title=None, frameon=False)
fig.tight_layout()

原文

I would like to have a single legend that nicely fits on top of both the subplots (doesn't necessarily need to span the entire width of the plots, but needs to be outside the plot). I know you can work with bbox_to_anchor() but somehow this doesn't seem to work nicely. It always moves one subplot away.

fig, ax = plt.subplots(1, 2)
sns.barplot(x="day", y="total_bill", hue="sex", data=tips, ax = ax[0])
ax[0].legend_.remove()
sns.barplot(x="day", y="total_bill", hue="sex", data=tips, ax = ax[1])
sns.move_legend(ax[1], loc = "center", bbox_to_anchor=(-0.5, 1.1), ncol=2, title=None, frameon=False)
fig.tight_layout()

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歌入人心 2025-02-07 10:41:10

有几种方法可以解决差距。

1：使用`sns.catplot`：

这可能需要将数据加倍，尽管如果您要在每个子图中绘制不同的变量，则可以

import pandas as pd
import seaborn as sns

# Load the dataset twice
tips_a = sns.load_dataset("tips")
tips_b = sns.load_dataset("tips")
# Add a dummy facet variable
tips_a["col"] = "A"
tips_b["col"] = "B"

# Concat them
tips = pd.concat([tips_a, tips_b])

# Use the dummy variable for the `col` param
g = sns.catplot(x="day", y="total_bill", hue="sex", data=tips, kind="bar", col="col")
# Remove the titles and move the legend
g.set_titles("")
sns.move_legend(g, loc="upper center", ncol=2, title=None, frameon=False)

。

> AutoScale 轴

仍然需要一点bbox_to_anchor弹奏，您可能想更改正确的y轴标签（以及ticks/ticklabels）。

import matplotlib.pyplot as plt
import seaborn as sns

fig, ax = plt.subplots(1, 2, figsize=(7, 4))
sns.barplot(x="day", y="total_bill", hue="sex", data=tips, ax=ax[0])
ax[0].legend_.remove()
sns.barplot(x="day", y="total_bill", hue="sex", data=tips, ax=ax[1])
sns.move_legend(
    ax[1],
    loc="upper center",
    bbox_to_anchor=(-0.1, 1.1),
    ncol=2,
    title=None,
    frameon=False,
)

ax[0].autoscale()
ax[1].autoscale()

There are a couple of ways that I would approach closing the gap.

1: Use a `sns.catplot`:

This potentially requires doubling your data, though if you're plotting different variables in each subplot you may be able to melt your data

import pandas as pd
import seaborn as sns

# Load the dataset twice
tips_a = sns.load_dataset("tips")
tips_b = sns.load_dataset("tips")
# Add a dummy facet variable
tips_a["col"] = "A"
tips_b["col"] = "B"

# Concat them
tips = pd.concat([tips_a, tips_b])

# Use the dummy variable for the `col` param
g = sns.catplot(x="day", y="total_bill", hue="sex", data=tips, kind="bar", col="col")
# Remove the titles and move the legend
g.set_titles("")
sns.move_legend(g, loc="upper center", ncol=2, title=None, frameon=False)

2: `autoscale` the axes

This still requires a little bit of bbox_to_anchor fiddling and you probably want to change the right y-axis label (and ticks/ticklabels).

import matplotlib.pyplot as plt
import seaborn as sns

fig, ax = plt.subplots(1, 2, figsize=(7, 4))
sns.barplot(x="day", y="total_bill", hue="sex", data=tips, ax=ax[0])
ax[0].legend_.remove()
sns.barplot(x="day", y="total_bill", hue="sex", data=tips, ax=ax[1])
sns.move_legend(
    ax[1],
    loc="upper center",
    bbox_to_anchor=(-0.1, 1.1),
    ncol=2,
    title=None,
    frameon=False,
)

ax[0].autoscale()
ax[1].autoscale()