问题

我有一个数据框，其中包含要使用seaborn库绘制的x和y值。但问题是，我需要根据已有的数据点来用多种颜色着色背景。例如：

# df - 表示包含x和y数据的数据框
split_points = [20, 40, 60, 80, 100]  # 分割点的列表，该列表也可以更长（与示例保持一致）
sns.scatterplot(...)  # 我需要帮助来获得下面指定的图表

代码片段看起来像上面那样。但通常我希望将split_points列表中提到的所有点的分割显示为不同的背景颜色。希望找到实现此目标的方法。

我打算做类似于这样的事情：

我从这个答案中获取了图像，以便更好地理解。

# df - represents the dataframe in which the x and y data are present
split_points = [20,40,60,80,100] # The list of split point, the list can be bigger as well ( keeping it same with the example)
sns.scatterplot(...) # I need help with this to get the below specified graph

答案1

得分: 1

You can use axvspan() 函数来为每个区域添加背景颜色，同时使用 alpha 控制透明度和 zorder 将有颜色的矩形移到后面，以使线条位于顶部。对于图例，您可以使用 label 在每种情况下提供文本。以下是一个可工作的示例。希望这是您正在寻找的内容...

df = np.random.uniform(low=-10, high=5, size=(100,))  ##线条的数据
split_points = [20, 40, 60, 80, 100]  # 分割点的列表，也可以更大（与示例保持一致）
split_colors = ['red', 'yellow', 'green', 'blue', 'pink']  ##每个区域的颜色
sns.lineplot(data=df, color='black', lw=0.75)  ##绘制所需的线图

labels = [*'abcde']  ##定义图例的标签

## 对于每个条目，绘制带有颜色、透明度、zorder 和图例标签的矩形
for i in range(len(split_points)):
    plt.axvspan(split_points[i] - 20, split_points[i], facecolor=split_colors[i], alpha=0.2, zorder=-10, label=labels[i])

plt.legend()
plt.show()

<details>
<summary>英文:</summary>

You can use `axvspan()` to add the background color for each region, along with `alpha` to control the transparency and `zorder` to move the colored rectangles to the back, so that the lines are on top. For the legend, you can use `label` to provide the text in each case. Below is a working example. Hope this is what you are looking for...

df=np.random.uniform(low=-10, high=5, size=(100,)) ## data for the line
split_points = [20,40,60,80,100] # The list of split point, the list can be bigger as well ( keeping it same with the example)
split_colors = ['red', 'yellow', 'green', 'blue', 'pink'] ## Colors for each region
sns.lineplot(data=df, color='black', lw=0.75) ## Draw the line plot you want

labels=[*'abcde'] ## Define the labels for the legend

For each entry, draw the rectangle along with the color, transparency, zorder and label for the legend

for i in range(len(split_points)):
plt.axvspan(split_points[i]-20, split_points[i], facecolor=split_colors[i], alpha=0.2, zorder=-10, label=labels[i])

plt.legend()
plt.show()

[![enter image description here][1]][1]


  [1]: https://i.stack.imgur.com/yAF1z.png

</details>