带有连接点的群图
我尝试使用箱线图与群图以及连接数据点的线相结合来跟踪数据帧内的变化。
到目前为止，我只能使用以下代码将箱线图与群图结合起来：
import seaborn as sns
from itertools import cycle
import numpy as np
import pandas as pd
#create random dataframe with 4 conditions
df = pd.DataFrame(data = np.random.random(size=(4,4)), columns = ['A','B','C','D'])
datapoints=pd.melt(df)
#add IDs
ID = cycle(["1","2","3", "4"])
datapoints['ID'] = [next(ID) for IDs in range(len(datapoints))]
#plot values
sns.boxplot(x="variable", y="value", data=datapoints)
sns.swarmplot(x="variable", y="value", data=datapoints, color=".25")
结果是这样的： 
我想要做的是跟踪每个 ID 连接 A、B、C 和 D 上的单个点的变化。
这样我就可以跟踪 ID 1 在 4 个条件下的表现。像这样的东西：
I'm try to keep track of changes within a dataframe using a boxplot combined with a swarmplot, and lines connecting data points.
So far I only managed to combine the boxplot with the swarmplot, using this code:
import seaborn as sns
from itertools import cycle
import numpy as np
import pandas as pd
#create random dataframe with 4 conditions
df = pd.DataFrame(data = np.random.random(size=(4,4)), columns = ['A','B','C','D'])
datapoints=pd.melt(df)
#add IDs
ID = cycle(["1","2","3", "4"])
datapoints['ID'] = [next(ID) for IDs in range(len(datapoints))]
#plot values
sns.boxplot(x="variable", y="value", data=datapoints)
sns.swarmplot(x="variable", y="value", data=datapoints, color=".25")
And the result is this:
Waht I would like to do is to keep track of changes connecting the single dots across A, B, C and D per ID.
This way I could follow the performance of for example ID 1 across the 4 conditions. Something like this:
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不确定我是否理解这个问题，因为箱线图用于聚合信息而不是显示所有值，但如果您想显示所有点：
或：
要具有黑线，使用：
Not sure I understood the question as boxplot are used to aggregate information rather than showing all values, but if you want to show all points:
or:
To have black lines, use: