Seaborn绘制20个pairplot图

seaborn.pairplot(data,  # 绘图数据
                 hue=None,  # 针对某一字段进行颜色分类
                 hue_order=None,  # 指定分组顺序
                 palette=None,  # 控制色调
                 vars=None,  # 变量
                 x_vars=None,
                 y_vars=None,
                 kind='scatter', # scatter’, ‘kde’, ‘hist’, ‘reg’
                 diag_kind='auto', # ‘auto’, ‘hist’, ‘kde’, None
                 markers=None, # 控制散点的样式  “+” “s” "D"
                 height=2.5,  # 高度
                 aspect=1, # 宽度
                 corner=False,  # 对角线是否显示
                 dropna=False,   # 是否去掉控制
                 plot_kws=None,  # 控制非对角线图例样式
                 diag_kws=None,  # 控制对角线图例样式
                 grid_kws=None,  # 网格设置
                 size=None)  # 默认 6，图的尺度大小（正方形）

import pandas as pd
import numpy as np

import seaborn as sns
import matplotlib.pyplot as plt
%matplotlib inline
sns.set_style('darkgrid',{'font.sans-serif':['simhei','Arial']})

sns.pairplot(df)

plt.show()

sns.pairplot(df, kind="kde")

plt.show()

sns.pairplot(df, kind="hist")

plt.show()

sns.pairplot(df, kind="reg")  # 使用回归

plt.show()

sns.pairplot(df, hue="species")

plt.show()

sns.pairplot(df, hue="sex")
plt.show()

sns.pairplot(df, hue="species", diag_kind="hist")

plt.show()

Accent, Accent_r, Blues, Blues_r, BrBG, BrBG_r, BuGn, BuGn_r, BuPu, BuPu_r, CMRmap, CMRmap_r, Dark2, Dark2_r, GnBu, GnBu_r, Greens, Greens_r, Greys, Greys_r, OrRd, OrRd_r, Oranges, Oranges_r, PRGn, PRGn_r, Paired, Paired_r, Pastel1, Pastel1_r, Pastel2, Pastel2_r, PiYG, PiYG_r, PuBu, PuBuGn, PuBuGn_r, PuBu_r, PuOr, PuOr_r, PuRd, PuRd_r, Purples, Purples_r, RdBu, RdBu_r, RdGy, RdGy_r, RdPu, RdPu_r, RdYlBu, RdYlBu_r, RdYlGn, RdYlGn_r, Reds, Reds_r, Set1, Set1_r, Set2, Set2_r, Set3, Set3_r, Spectral, Spectral_r, Wistia, Wistia_r, YlGn, YlGnBu, YlGnBu_r, YlGn_r, YlOrBr, YlOrBr_r, YlOrRd, YlOrRd_r, afmhot, afmhot_r, autumn, autumn_r, binary, binary_r, bone, bone_r, brg, brg_r, bwr, bwr_r, cividis, cividis_r, cool, cool_r, coolwarm, coolwarm_r, copper, copper_r, crest, crest_r, cubehelix, cubehelix_r, flag, flag_r, flare, flare_r, gist_earth, gist_earth_r, gist_gray, gist_gray_r, gist_heat, gist_heat_r, gist_ncar, gist_ncar_r, gist_rainbow, gist_rainbow_r, gist_stern, gist_stern_r, gist_yarg, gist_yarg_r, gnuplot, gnuplot2, gnuplot2_r, gnuplot_r, gray, gray_r, hot, hot_r, hsv, hsv_r, icefire, icefire_r, inferno, inferno_r, jet, jet_r, magma, magma_r, mako, mako_r, nipy_spectral, nipy_spectral_r, ocean, ocean_r, pink, pink_r, plasma, plasma_r, prism, prism_r, rainbow, rainbow_r, rocket, rocket_r, seismic, seismic_r, spring, spring_r, summer, summer_r, tab10, tab10_r, tab20, tab20_r, tab20b, tab20b_r, tab20c, tab20c_r, terrain, terrain_r, twilight, twilight_r, twilight_shifted, twilight_shifted_r, viridis, viridis_r, vlag, vlag_r, winter, winter_r

sns.pairplot(df,hue="species",palette="husl")

plt.show()

sns.pairplot(df, hue="species", diag_kind="hist", markers=["o", "s", "D"])

plt.show()

sns.pairplot(df, height=1.5)

plt.show()

sns.pairplot(df, height=4)

plt.show()

sns.pairplot(df, hue="species", aspect=3)

plt.show()

sns.pairplot(df, corner=True)

plt.show()

df.columns

Index(['species', 'island', 'bill_length_mm', 'bill_depth_mm',
       'flipper_length_mm', 'body_mass_g', 'sex'],
      dtype='object')

sns.pairplot(df,vars=["island","bill_length_mm","sex"])

plt.show()

sns.pairplot(
    df,
    x_vars=["bill_length_mm", "bill_depth_mm", "flipper_length_mm"],
    y_vars=["bill_length_mm", "bill_depth_mm"],
)

plt.show()

sns.pairplot(
    df,
    plot_kws=dict(marker="+", edgecolor="b",linewidth=1),
    diag_kws=dict(fill=False),
)

plt.show()

sns.pairplot(df,
             diag_kind="kde",
             markers="+",
             plot_kws=dict(s=50, edgecolor="b", linewidth=1),
             diag_kws=dict(shade=True)
            )

plt.show()

sns.pairplot(df, dropna=True)

plt.show()

g = sns.pairplot(df, diag_kind="kde")
g.map_lower(sns.kdeplot, levels=6, color=".4")

plt.show()