用不同的颜色绘制点标记和线条，但与Seaborn的样式相同 [英] Plot point markers and lines in different hues but the same style with seaborn

问题描述

给出以下数据框：

 将熊猫作为pd 
 df = pd.DataFrame（{
 n_index：list（range（5））* 2，
 logic：[True] * 5 + [False] * 5，
 value：list（range（5） ）+ list（range（5，10））
}）
  

我想要使用 color和仅color 来区分线图中的逻辑，并在 value s。具体来说，这是我想要的输出（由R

我尝试执行与

然后我尝试了addi ng style = logic ，现在标记出现了：

  sns.lineplot（x = n_index，y = value，hue = logic，style = logic，markers = True，data = df）
  

我也尝试过强制标记样式相同：

  sns.lineplot（x = n_index，y = value，hue =逻辑，样式=逻辑，标记= [ o， o]，数据= df）
  

似乎我必须指定样式在我有了标记之前。但是，由于我不想在一个数据维度上使用两个美学维度，因此会导致不良的绘图输出。

有什么办法可以用使线条和点具有相同的样式，但是具有不同的颜色？ seaborn 还是Python可视化？ （首选 seaborn -我不喜欢 matplotlib 的循环方式。）

解决方案

您可以直接使用熊猫进行绘图。

通过groupby 熊猫>

  fig，ax = plt.subplots（）
 df.groupby（ logic）。plot（x = n_index，y = value，marker = o，ax = ax）
 ax.legend（[ False， True]）
  

这里的缺点是图例需要手动创建。

通过数据透视的熊猫

  df.pivot_table（ value， n_index， logic）。plot（marker = o）
  

seaborn lineplot

对于seaborn lineplot来说，似乎只有一个标记就足以获得所需的结果。

  sns.lineplot（x = n_index，y = value，hue = logic，data = df，marker = o）
  

Given the data frame below:

import pandas as pd
df = pd.DataFrame({
    "n_index": list(range(5)) * 2,
    "logic": [True] * 5 + [False] * 5,
    "value": list(range(5)) + list(range(5, 10))
})

I'd like to use color and only color to distinguish logic in a line plot, and mark points on values. Specifically, this is my desired output (plotted by R ggplot2):

ggplot(aes(x = n_index, y = value, color = logic), data = df) + geom_line() + geom_point()

I tried to do the same thing with seaborn.lineplot, and I specified markers=True but there was no marker:

import seaborn as sns
sns.set()
sns.lineplot(x="n_index", y="value", hue="logic", markers=True, data=df)

I then tried adding style="logic" in the code, now the markers showed up:

sns.lineplot(x="n_index", y="value", hue="logic", style="logic", markers=True, data=df)

Also I tried forcing the markers to be in the same style:

sns.lineplot(x="n_index", y="value", hue="logic", style="logic", markers=["o", "o"], data=df)

It seems like that I have to specify style before I can have markers. However, that causes undesired plot output since I don't want to use two aesthetic dimensions on one data dimension. That violates the principles of aesthetic mapping.

Is there any way I can have the lines and points all in the same style but in different colors with seaborn or Python visualization? (seaborn is preferred - I don't like the looping way ofmatplotlib.)

解决方案

You can directly use pandas for plotting.

pandas via groupby

fig, ax = plt.subplots()
df.groupby("logic").plot(x="n_index", y="value", marker="o", ax=ax)
ax.legend(["False","True"])

The drawback here would be that the legend needs to be created manually.

pandas via pivot

df.pivot_table("value", "n_index", "logic").plot(marker="o")

seaborn lineplot

For seaborn lineplot it seems a single marker is enough to get the desired result.

sns.lineplot(x="n_index", y="value", hue="logic", data=df, marker="o")

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