Python Seborn Ridge绘图教程不起作用 [英] Python Seaborn Ridge Plot tutorial not working

问题描述

如果我复制粘贴Seaborn website中给出的示例以生成"；Ridge Plot&Quot；，则代码在两个不同的点上失败：

import numpy as np
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
sns.set_theme(style="white", rc={"axes.facecolor": (0, 0, 0, 0)})

# Create the data
rs = np.random.RandomState(1979)
x = rs.randn(500)
g = np.tile(list("ABCDEFGHIJ"), 50)
df = pd.DataFrame(dict(x=x, g=g))
m = df.g.map(ord)
df["x"] += m

# Initialize the FacetGrid object
pal = sns.cubehelix_palette(10, rot=-.25, light=.7)
g = sns.FacetGrid(df, row="g", hue="g", aspect=15, height=.5, palette=pal)

# Draw the densities in a few steps
g.map(sns.kdeplot, "x",
      bw_adjust=.5, clip_on=False,
      fill=True, alpha=1, linewidth=1.5)
g.map(sns.kdeplot, "x", clip_on=False, color="w", lw=2, bw_adjust=.5)

# passing color=None to refline() uses the hue mapping
g.refline(y=0, linewidth=2, linestyle="-", color=None, clip_on=False)


# Define and use a simple function to label the plot in axes coordinates
def label(x, color, label):
    ax = plt.gca()
    ax.text(0, .2, label, fontweight="bold", color=color,
            ha="left", va="center", transform=ax.transAxes)


g.map(label, "x")

# Set the subplots to overlap
g.figure.subplots_adjust(hspace=-.25)

# Remove axes details that don't play well with overlap
g.set_titles("")
g.set(yticks=[], ylabel="")
g.despine(bottom=True, left=True)

行 g.refline(y=0, linewidth=2, linestyle="-", color=None, clip_on=False) 和线 g.figure.subplots_adjust(hspace=-.25) 失败，出现此错误：

AttributeError: 'FacetGrid' object has no attribute 'figure'

我在 NumPy：1.19.1 pandas ：1.2.4 海运：0.11.1

推荐答案

您可以将g.figure替换为g.fig。g.figure是同一变量的新名称。refline()是海运0.11.2中的新增功能(网站假定您运行的是最新发布的版本)。您可以将对g.refline()的调用替换为g.map(plt.axhline, y=0, linewidth=2, linestyle="-", color=None, clip_on=False)。

import numpy as np
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt

sns.set_theme(style="white", rc={"axes.facecolor": (0, 0, 0, 0)})

# Create the data
rs = np.random.RandomState(2022)
x = rs.randn(500)
g = np.tile(list("ABCDEFGHIJ"), 50)
df = pd.DataFrame(dict(x=x, g=g))
df["x"] += df["g"].map(ord)

# Initialize the FacetGrid object
pal = sns.cubehelix_palette(10, start=1, rot=-.25, light=.7)
g = sns.FacetGrid(df, row="g", hue="g", aspect=15, height=.5, palette=pal)

# Draw the densities in a few steps
g.map(sns.kdeplot, "x",
      bw_adjust=.5, clip_on=False,
      fill=True, alpha=1, linewidth=1.5)
g.map(sns.kdeplot, "x", clip_on=False, color="w", lw=2, bw_adjust=.5)

# passing color=None to refline() uses the hue mapping
# g.refline(y=0, linewidth=2, linestyle="-", color=None, clip_on=False)
g.map(plt.axhline, y=0, linewidth=2, linestyle="-", color=None, clip_on=False)

# Define and use a simple function to label the plot in axes coordinates
def label(x, color, label):
    ax = plt.gca()
    ax.text(0, .2, label, fontweight="bold", color=color,
            ha="left", va="center", transform=ax.transAxes)

g.map(label, "x")

# Set the subplots to overlap
g.fig.subplots_adjust(hspace=-.25)

# Remove axes details that don't play well with overlap
g.set_titles("")
g.set(yticks=[], xlabel="", ylabel="")
g.despine(bottom=True, left=True)
plt.show()

这里是另一个使用航班数据集的示例：

import numpy as np
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt

sns.set_theme(style="white", rc={"axes.facecolor": (0, 0, 0, 0)})

flights = sns.load_dataset('flights')
pal = sns.cubehelix_palette(len(flights["year"].unique()), start=1.4, rot=-.25, light=.7, dark=.4)
g = sns.FacetGrid(flights, row="year", hue="year", aspect=20, height=.5, palette=pal)

g.map(sns.kdeplot, "passengers", bw_adjust=.6, cut=5, clip_on=False, fill=True, alpha=1, linewidth=1.5)
g.map(sns.kdeplot, "passengers", bw_adjust=.6, cut=5, clip_on=False, color="w", lw=2)
g.map(plt.axhline, y=0, linewidth=2, linestyle="-", color=None, clip_on=False)

def label(x, color, label):
    ax = plt.gca()
    ax.text(0, .1, label, fontweight="bold", color=color,
            ha="left", va="center", transform=ax.transAxes)

g.map(label, "year")
g.fig.subplots_adjust(hspace=-.7)
g.set(yticks=[], xlabel="", ylabel="", xlim=(None, 680), title="")
g.despine(bottom=True, left=True)
plt.show()

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