如何组合线图＆amp; Seaborn/Matplotlib中的传奇

发布于 2025-02-04 18:05:22 字数 1612 浏览 2 评论 0 原文

我会有这样的数据框

import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns

df = pd.DataFrame({'A': [1,2,3,4,5,4,3,2,1],
                   'B': [200,300,400,800,1500,900,450,275,200],
                   'c': ['up','up','down','up','up','down','down','up','down'],
                   'd': ['r','r','r','r','r','r','r','r','r'],
                   })

当我使用代码 sns.lineplot（data = df，x ='a'，y ='b'，ci = none）>时，。我得到了下面的情节。

如您所见，这些要点尚未完全绘制。当我使用下面的代码进行绘图时，

upDF = df.loc[df['c']=='up']
downDF = df.loc[df['c']=='down']
sns.lineplot(data=upDF, x='A', y='B',ci=None, label = 'up');
sns.lineplot(data=downDF, x='A', y='B',ci=None, label = 'down');
plt.legend()

我会得到像下面的图，

在此图中，所有点都绘制了，但它们'已断开连接'。我如何获得下面的绘图，并连接点;只有一个传奇（列'd'或一个常数可以用于图例）

如果我在实际数据上使用 sns.lineplot ，我会在下面获得图形而不是 UP ＆amp; down 单独绘制。

原文

I have a dataframe like this

import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns

df = pd.DataFrame({'A': [1,2,3,4,5,4,3,2,1],
                   'B': [200,300,400,800,1500,900,450,275,200],
                   'c': ['up','up','down','up','up','down','down','up','down'],
                   'd': ['r','r','r','r','r','r','r','r','r'],
                   })

When I do a line plot with seaborn with the code sns.lineplot(data=df, x='A', y='B',ci=None). I get a plot like below.

As you can see, the points have not completely plotted. When I do the plot with the code below

upDF = df.loc[df['c']=='up']
downDF = df.loc[df['c']=='down']
sns.lineplot(data=upDF, x='A', y='B',ci=None, label = 'up');
sns.lineplot(data=downDF, x='A', y='B',ci=None, label = 'down');
plt.legend()

I get a plot like below

In this plot, all points are plotted, but they are 'disconnected'. How can I get a plot like below with the points connected & just only one legend (column 'D' or a constant can be used for legend)

If I use sns.lineplot on my actual data, I get the graph like below instead of up & down plotted separately.

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痴情 2025-02-11 18:05:22

您可以使用纯Matplotlib。作为UP系列的一部分，在UP之后选择行，以确保加入积分。对于传说，添加一个以要跳过的下划线开头的标签：

import matplotlib.pyplot as plt
m = df['c']=='up'
upDF = df.loc[m|m.shift()]
downDF = df.loc[~m]
ax = plt.subplot()
upDF.plot(x='A', y='B', label='r', ax=ax)
downDF.plot(x='A', y='B', label='_skip', ax=ax)
ax.legend()

输出：

You can use pure matplotlib. Select the rows after an up as part of the up Series to ensure joining the points. For the legend, add a label that starts with an underscore to be skipped:

import matplotlib.pyplot as plt
m = df['c']=='up'
upDF = df.loc[m|m.shift()]
downDF = df.loc[~m]
ax = plt.subplot()
upDF.plot(x='A', y='B', label='r', ax=ax)
downDF.plot(x='A', y='B', label='_skip', ax=ax)
ax.legend()

output: