hexbin 联合图的 Seaborn 成对矩阵 [英] Seaborn pairwise matrix of hexbin jointplots

问题描述

我正在尝试生成一个比较分布的成对图矩阵(类似这样的事情).由于我有很多点，我想使用 hexbin 图来减少时间和绘图复杂性.

I am trying to produce a matrix of pairwise plots comparing distributions (something like this). Since I have many points I want to use a hexbin plot to reduce time and plot complexity.

import seaborn as sns
import matplotlib.pyplot as plt


tips = sns.load_dataset("tips")

g = sns.FacetGrid(tips, col="time", row="sex")
g.map(sns.jointplot, "total_bill", "tip", kind="hex")
plt.show()

尽管如此，与其创建图表矩阵，不如在各个窗口中独立创建多个图表.

Nevertheless, instead of creating the matrix of plots it creates several plots independently in various windows.

我也想过使用 seaborn.pairplot 来生成这个，但我无法将 "hex" 作为值传递给 kind.

I also thought of using seaborn.pairplot to produce this but I can not pass "hex" as a value to kind.

推荐答案

请参见

See the last example in the tutorial on using custom functions with FacetGrid, which I'll reproduce here:

def hexbin(x, y, color, **kwargs):
    cmap = sns.light_palette(color, as_cmap=True)
    plt.hexbin(x, y, gridsize=15, cmap=cmap, **kwargs)

g = sns.FacetGrid(tips, hue="time", col="time", size=4)
g.map(hexbin, "total_bill", "tip", extent=[0, 50, 0, 10])

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