Histogram + rug + kernel density curve
# libraries & dataset
import seaborn as sns
import matplotlib.pyplot as plt
# set a grey background (use sns.set_theme() if seaborn version 0.11.0 or above)
sns.set(style="darkgrid")
df = sns.load_dataset("iris")
sns.distplot(df["sepal_length"], kde=True, rug=True)
# in the next version of the distplot function, one would have to write:
# sns.distplot(data=df, x="sepal_length", kde=True, rug=True) # note that 'kind' is 'hist' by default
plt.show()
Customizing rugs
# libraries & dataset
import seaborn as sns
import matplotlib.pyplot as plt
# set a grey background (use sns.set_theme() if seaborn version 0.11.0 or above)
sns.set(style="darkgrid")
df = sns.load_dataset("iris")
sns.distplot(df["sepal_length"],
kde=True,
rug=True,
rug_kws={"color": "r", "alpha": 0.3, "linewidth": 2, "height":0.2})
# in the next version of the distplot function, one would have to write:
# sns.distplot(data=df, x="sepal_length", kde=True, rug=True, rug_kws={"color": "r", "alpha":0.3, "linewidth": 2, "height":0.2 })
plt.show()
Customizing the density curve
# libraries & dataset
import seaborn as sns
import matplotlib.pyplot as plt
# set a grey background (use sns.set_theme() if seaborn version 0.11.0 or above)
sns.set(style="darkgrid")
df = sns.load_dataset("iris")
sns.distplot(df["sepal_length"],
kde=True,
kde_kws={"color": "g", "alpha": 0.3, "linewidth": 5, "shade": True})
# in the next version of the distplot function, one would have to write:
# sns.distplot(data=df, x="sepal_length", kde=True, kde_kws={"color": "g", "alpha": 0.3, "linewidth": 5, "shade": True})
plt.show()
