Python 以不同的色调绘制点标记和线条，但与 seaborn 风格相同
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Plot point markers and lines in different hues but the same style with seaborn
提问by ytu
Given the data frame below:
鉴于以下数据框：
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 colorto distinguish logicin a line plot, and mark points on values. Specifically, this is my desired output (plotted by R ggplot2):
我想在线图中使用颜色和仅颜色来区分logic，并在values上标记点。具体来说，这是我想要的输出（由 R ggplot2绘制）：
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=Truebut there was no marker:
我试图用 做同样的事情seaborn.lineplot，我指定了markers=True但没有标记：
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:
然后我尝试添加style="logic"代码，现在标记出现了：
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:
我还尝试强制标记采用相同的样式：
sns.lineplot(x="n_index", y="value", hue="logic", style="logic", markers=["o", "o"], data=df)
It seems like that I have to specify stylebefore 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.
似乎我必须先指定style才能有标记。但是，这会导致不需要的绘图输出，因为我不想在一个数据维度上使用两个美学维度。这违反了美学映射的原则。
Is there any way I can have the lines and points all in the same style but in different colors with seabornor Python visualization? (seabornis preferred - I don't like the looping way ofmatplotlib.)
有什么方法可以使线条和点都具有相同的样式但颜色不同，并且seaborn可以使用 Python 可视化？（seaborn是首选 - 我不喜欢 . 的循环方式matplotlib。）
采纳答案by ImportanceOfBeingErnest
You can directly use pandas for plotting.
您可以直接使用 Pandas 进行绘图。
pandas via groupby
熊猫通过 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.
这里的缺点是需要手动创建图例。
pandas via pivot
大熊猫通过枢轴
df.pivot_table("value", "n_index", "logic").plot(marker="o")
seaborn lineplot
seaborn 线图
For seaborn lineplot it seems a single marker is enough to get the desired result.
对于seaborn lineplot，似乎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")
回答by Dani Mesejo
You need to set dashesparameter to Falsealso specify the style of the grid to "darkgrid":
您需要设置dashes参数以False还将网格的样式指定为"darkgrid"：
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
df = pd.DataFrame({
"n_index": list(range(5)) * 2,
"logic": [True] * 5 + [False] * 5,
"value": list(range(5)) + list(range(5, 10))
})
sns.set_style("darkgrid")
sns.lineplot(x="n_index", dashes=False, y="value", hue="logic", style="logic", markers=["o", "o"], data=df)
plt.show()
回答by Akshay Jagadeesh
You can set marker='o' in sns.linePlot to draw the marker as a circle for all the different hues, in the appropriate color.
您可以在 sns.linePlot 中设置 marker='o' 以将标记绘制为所有不同色调的圆形，并使用适当的颜色。
sns.lineplot(x="n_index", y="value", hue="logic", marker="o", data=df)
