I have 4 groups (research, sales, manu, hr) and each group has 2 categories (0 & 1). I am trying to plot the average scores for each group in the features in the list ratings. The code that gives me the means looks like this (with 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])
Which results in this output:
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
My question is how do I plot these group means (research, sales, manu, hr) for each rating ['JobSatisfaction', 'PerformanceRating', 'EnvironmentSatisfaction', 'RelationshipSatisfaction']onto the 4 different bar graphs so I can visualize and compare the differences between each group?
My data is from the IBM HR dataset: https://www.kaggle.com/pavansubhasht/ibm-hr-analytics-attrition-dataset
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Answer
You can use sns.barplot from seaborn, and since your y variable is comparable, separating by color and same y-axis is ok:
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)
