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View ridgeplot.py
# Initialize the FacetGrid object
g = sns.FacetGrid(df2, row="gender", hue="gender", aspect=5, height=3)
# # Draw the densities in a few steps
g.map(sns.kdeplot, "age", shade=True, alpha=1, lw=3.5, bw=.2)
g.map(sns.kdeplot, "age", color="w", lw=2, bw=.2)
g.map(plt.axhline, y=0, lw=2)
# # Define and use a simple function to label the plot in axes coordinates
def label(x, color, label):
View boxenplot.py
sns.catplot(x="age", y="avg_training_score", data=df2, kind="boxen",height=4, aspect=2.7, hue = "is_promoted")
View heatmap.py
corrmat = df2.corr()
f, ax = plt.subplots(figsize=(9, 6))
sns.heatmap(corrmat, vmax=.8, square=True)
View kdeplot.py
sns.jointplot(x="age", y="avg_training_score", data=df2, kind="kde");
View hexplot.py
sns.jointplot(x=df2.age, y=df2.avg_training_score, kind="hex", data = df2)
View jointplot.py
sns.jointplot(x="avg_training_score", y="age", data=df2);
View histogram.py
sns.distplot(df2.age, kde=False, rug = True)
View categorical12.py
sns.catplot(x="education", y="avg_training_score", hue="is_promoted",
col="gender", aspect=.9,
kind="swarm", data=df2);
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