Python 在4个单独的绘图上，每个评级的绘图组平均值

我有4个小组（研究、销售、制造、人力资源），每个小组有2个类别（0和1）。我试图在列表中的功能中绘制每组的平均分数

评分

。给我提供方法的代码如下所示（使用

depts=['research'、'sales'、'manu'、'hr']

：

ratings = ['JobSatisfaction', 'PerformanceRating', 'EnvironmentSatisfaction', 'RelationshipSatisfaction']


for i in depts:
    for x in ratings:
        print(group_data.groupby([i]).mean()[x])

这将导致此输出：

research
0.0    2.700000
1.0    2.773973
Name: JobSatisfaction, dtype: float64
research
0.0    3.100000
1.0    3.167808
Name: PerformanceRating, dtype: float64
research
0.0    2.500000
1.0    2.726027
Name: EnvironmentSatisfaction, dtype: float64
research
0.0    2.687500
1.0    2.705479
Name: RelationshipSatisfaction, dtype: float64
sales
0.0    2.754601
1.0    2.734940
Name: JobSatisfaction, dtype: float64
sales
0.0    3.125767
1.0    3.144578
Name: PerformanceRating, dtype: float64
sales
0.0    2.671779
1.0    2.734940
Name: EnvironmentSatisfaction, dtype: float64
sales
0.0    2.702454
1.0    2.602410
Name: RelationshipSatisfaction, dtype: float64
manu
0.0    2.682759
1.0    2.723077
Name: JobSatisfaction, dtype: float64
manu
0.0    3.186207
1.0    3.158974
Name: PerformanceRating, dtype: float64
manu
0.0    2.917241
1.0    2.735897
Name: EnvironmentSatisfaction, dtype: float64
manu
0.0    2.724138
1.0    2.689744
Name: RelationshipSatisfaction, dtype: float64
hr
0.0    2.705882
1.0    2.557692
Name: JobSatisfaction, dtype: float64
hr
0.0    3.196078
1.0    3.134615
Name: PerformanceRating, dtype: float64
hr
0.0    2.764706
1.0    2.596154
Name: EnvironmentSatisfaction, dtype: float64
hr
0.0    2.813725
1.0    2.961538
Name: RelationshipSatisfaction, dtype: float64

我的问题是，我如何在4个不同的条形图上绘制每个评级的组平均值（研究、销售、制造、人力资源）[‘工作满意度’、‘绩效经营’、‘环境满意度’、‘关系满意度’]，以便我能直观地看到和比较各组之间的差异

---

我的数据来自IBM HR数据集：

您可以使用seaborn提供的

sns.barplot

，因为您的y变量是可比较的，所以可以按颜色和相同的y轴分隔：

import statsmodels.api as sm
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt

df = pd.read_csv("WA_Fn-UseC_-HR-Employee-Attrition.csv")

ratings = ['JobSatisfaction', 'PerformanceRating', 'EnvironmentSatisfaction', 'RelationshipSatisfaction']

sns.barplot(data = df[['Department'] + ratings].melt(id_vars='Department'),
            x = 'variable',y='value',hue='Department')
plt.xticks(rotation=45)