使用seaborn在条形图中垂直更改颜色比例/渐变答案

【问题标题】：Changing color scale/gradient vertically in bar like plot using seaborn使用seaborn在条形图中垂直更改颜色比例/渐变
【发布时间】：2018-09-01 07:57:00
【问题描述】：

我想为 seaborn barplot/countplot 的每个条设置垂直渐变，
_{（来源：pydata.org）}

#to reproduce above plot
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns

sns.set(style="whitegrid", color_codes=True)
np.random.seed(sum(map(ord, "categorical")))
titanic = sns.load_dataset("titanic")
sns.countplot(x="deck", data=titanic, palette="Greens_d")
plt.show()

此图像具有水平渐变，但我希望渐变是垂直的，例如 Excel 中的线性向下或线性向上渐变https://support.office.com/en-us/article/add-a-gradient-color-to-a-shape-11cf6392-723c-4be8-840a-b2dab4b2ba3e

请参阅此处来自https://matplotlib.org/gallery/lines_bars_and_markers/gradient_bar.html 的示例垂直渐变忽略背景，颜色无关紧要。

附言新手到seaborn

【问题讨论】：

标签： python plot seaborn

【解决方案1】：

我基于 ImportanceOfBeingErnest 的回答 using good old fashioned Matplotlib。基本上循环通过 Seaborn 的计数图中的酒吧容器，并使用带有渐变的imshow。希望这会有所帮助！

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

def gradientbars(bars):
    grad = np.atleast_2d(np.linspace(0,1,256)).T # Gradient of your choice

    rectangles = bars.containers[0]
    # ax = bars[0].axes
    fig, ax = plt.subplots()

    xList = []
    yList = []
    for rectangle in rectangles:
        x0 = rectangle._x0
        x1 = rectangle._x1
        y0 = rectangle._y0
        y1 = rectangle._y1

        xList.extend([x0,x1])
        yList.extend([y0,y1])

        ax.imshow(grad, extent=[x0,x1,y0,y1], aspect="auto", zorder=0)

    ax.axis([min(xList), max(xList), min(yList), max(yList)*1.1]) # *1.1 to add some buffer to top of plot

    return fig,ax


sns.set(style="whitegrid", color_codes=True)
np.random.seed(sum(map(ord, "categorical")))

# Load dataset
titanic = sns.load_dataset("titanic")

# Make Seaborn countplot
seabornAxHandle = sns.countplot(x="deck", data=titanic, palette="Greens_d")
plt.show() # Vertical bars with horizontal gradient

# Call gradientbars to make vertical gradient barplot using Seaborn ax
figVerticalGradient, axVerticalGradient = gradientbars(seabornAxHandle)

# Styling using the returned ax
axVerticalGradient.xaxis.grid(False)
axVerticalGradient.yaxis.grid(True)

# Labeling plot to match Seaborn
labels=titanic['deck'].dropna().unique().to_list() # Chaining to get tick labels as a list
labels.sort()
plt.ylabel('count')
plt.xlabel('deck')
plt.xticks(range(0,len(labels)), labels)  # Set locations and labels

plt.show() # Vertical bars with vertical gradient

Seaborn 计数图的输出：

带有垂直渐变条的输出：

【讨论】：