我不确定这是你想要的，但你可以尝试以下两种选择：

import pandas as pd
from io import StringIO
import seaborn as sns

data = """category val1 val2 val3
A       2    3     2
A       3    4     1
B       4    5     2
C       3    3     2
B       4    5     2
C       3    3     2"""

df = pd.read_csv(StringIO(data), sep="\s+")

g = sns.barplot(
    data=df.melt(id_vars = ["category"], value_vars=["val1", "val2", "val3"]),
    y="value", x="variable", hue="category", ci=None
)

或

g = sns.catplot(
    data=df.melt(id_vars = ["category"], value_vars=["val1", "val2", "val3"]),
    kind="bar",
    y="value", x="variable", col="category", ci=None
)
g.set_axis_labels("", "")

这些方法的关键是使用melt来取消数据透视。
还要注意的是，上面并没有处理重复的类别。如果你想让你的值是唯一的，你可以在绘图之前将df按category分组并聚合值。

您的类别不是唯一的。您希望在x轴上看到什么？
假设它们是唯一的，那么你可以简单地做：

import pandas as pd
import seaborn as sns
sns.set()

df = pd.DataFrame()
df['category'] = ['A','B','C','D','E','F']
df['val1'] = [2,3,4,3,4,3]
df['val2'] = [3,4,5,3,5,3]
df['val3'] = [2,1,2,2,2,2]

df.set_index('category').plot(kind='bar', stacked=True)

编辑：seaborn本身并不支持堆叠条形图，但如果你需要（或者其他人正在寻找标题中的实际内容），这里有一个黑客方法。

import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
sns.set()

df = pd.DataFrame()
df['category'] = ['A','B','C','D','E','F']
df['val1'] = [2,3,4,3,4,3]
df['val2'] = [3,4,5,3,5,3]
df['val3'] = [2,1,2,2,2,2]

# create total columns
df['v1+v2+v3'] = df.val1 + df.val2 + df.val3
df['v1+v2'] = df.val1 + df.val2

# plot total
g = sns.barplot(x=df['category'], y=df['v1+v2+v3'], color='green', label='val3')

# plot middle values
g = sns.barplot(x=df['category'], y=df['v1+v2'], color='orange', label='val2')

# plot bottom values
g = sns.barplot(x=df['category'], y=df['val1'], color='blue', label='val1')

# rename axes
g.set_ylabel('vals')
g.set_xlabel('categories')

plt.legend()