我使用以下代码创建了雨云图:
#雨图
dx = 'Time Point'; dy = 'Score'; ort = "v"; pal = "Set2"; sigma = .2;
f, ax = plt.subplots(figsize=(7, 5))
pt.RainCloud(x = dx, y = dy, data = df, palette = pal, bw = sigma,
width_viol = .9, ax= ax, orient = ort, move = .2)
plt.title("")
plt.ylabel('Score', fontsize = 20)
plt.xlabel('', fontsize = 20)
plt.grid(color = 'w')
if savefigs:
plt.savefig('/Users/zeidanlab/Desktop/gv/rainplots/figure_tsc.png', bbox_inches='tight')
我想知道是否有办法让箱线图与分布斑点重叠。
这是一种将半小提琴图与箱线图和条形图结合起来的方法。
半小提琴是通过提取其边界框并使用其中一半来剪辑小提琴来创建的。
带状图的点被移动以免重叠。
from matplotlib import pyplot as plt
import seaborn as sns
import numpy as np
sns.set_style('white')
tips = sns.load_dataset('tips')
palette = sns.cubehelix_palette(start=.5, rot=-.5, dark=0.3, light=0.7)
ax = sns.violinplot(y="day", x="total_bill", data=tips,
palette=palette,
scale="width", inner=None)
xlim = ax.get_xlim()
ylim = ax.get_ylim()
for violin in ax.collections:
bbox = violin.get_paths()[0].get_extents()
x0, y0, width, height = bbox.bounds
violin.set_clip_path(plt.Rectangle((x0, y0), width, height / 2, transform=ax.transData))
sns.boxplot(y="day", x="total_bill", data=tips, saturation=1, showfliers=False,
width=0.3, boxprops={'zorder': 3, 'facecolor': 'none'}, ax=ax)
old_len_collections = len(ax.collections)
sns.stripplot(y="day", x="total_bill", data=tips, color='dodgerblue', ax=ax)
for dots in ax.collections[old_len_collections:]:
dots.set_offsets(dots.get_offsets() + np.array([0, 0.12]))
ax.set_xlim(xlim)
ax.set_ylim(ylim)
plt.show()
这是另一个例子,在垂直方向。
from matplotlib import pyplot as plt
import seaborn as sns
import numpy as np
sns.set_style('white')
iris = sns.load_dataset('iris')
palette = 'Set2'
ax = sns.violinplot(x="species", y="sepal_length", data=iris, hue="species", dodge=False,
palette=palette,
scale="width", inner=None)
xlim = ax.get_xlim()
ylim = ax.get_ylim()
for violin in ax.collections:
bbox = violin.get_paths()[0].get_extents()
x0, y0, width, height = bbox.bounds
violin.set_clip_path(plt.Rectangle((x0, y0), width / 2, height, transform=ax.transData))
sns.boxplot(x="species", y="sepal_length", data=iris, saturation=1, showfliers=False,
width=0.3, boxprops={'zorder': 3, 'facecolor': 'none'}, ax=ax)
old_len_collections = len(ax.collections)
sns.stripplot(x="species", y="sepal_length", data=iris, hue="species", palette=palette, dodge=False, ax=ax)
for dots in ax.collections[old_len_collections:]:
dots.set_offsets(dots.get_offsets() + np.array([0.12, 0]))
ax.set_xlim(xlim)
ax.set_ylim(ylim)
ax.legend_.remove()
plt.show()
2023 年PtitPrince 似乎是一个很有前途的方案