[英]Seaborn swarmplot of grouped dataframe
When I have a dataframe likes this here: 当我有一个数据帧时喜欢这里:
import pandas as pd
import seaborn as sns
import random
random.seed(0)
df = pd.DataFrame({"Data":[random.random() for i in range(100)], "Cluster":[random.randint(0,10) for i in range(100)]})
I can easily plot the clusters with seaborn as boxplots: 我可以很容易地用seaborn绘制簇作为箱线图:
sns.boxplot(df["Data"], groupby=df["Cluster"])
Which gives me something like this: 这给了我这样的东西:
Unfortunately seaborn swarmplot does not have a groupby keyword. 不幸的是,seaborn swarmplot没有groupby关键字。 So, how can I convinently plot this dataframe as grouped swarmplots?
那么,我怎样才能将这个数据框架作为分组的swarmplots? I want the same figure as shown only with swarmplots instead of boxplots.
我想要的只是用swarmplots而不是boxplots显示的相同数字。 I played around with the groupby object itself:
我玩了groupby对象本身:
df.groupby(by="Cluster")
So far I could not convince seaborn to accept it. 到目前为止,我无法说服seaborn接受它。
I don't think you need to groupby
- you simply want to specify the cluster as your x value and the data as your y: 我不认为你需要
groupby
- 你只想将集群指定为x值,将数据指定为y:
sns.swarmplot(data=df, x="Cluster", y="Data")
Gives you: 给你:
However, if you had a further category that you wanted to colour by, eg 但是,如果你有另一个类别,你想要着色,例如
df = pd.DataFrame({"Data":[random.random() for _ in range(100)],
"Cluster":[random.randint(0,10) for _ in range(100)],
"Category": [random.choice(("A", "B")) for _ in range(100)]})
You can then use the hue
argument like so: 然后你可以像这样使用
hue
参数:
sns.swarmplot(data=df, x="Cluster", y="Data", hue="Category")
and get: 得到:
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