4.5.4 Density plot

Density plots are a commonly used tool to visualize the distribution of a continuous variable.

mpg = sns.load_dataset('mpg')   # load  the  embedded  dataset

1. Simple Density Chart

# Draw Density Plot

sns.kdeplot(mpg.loc[mpg["cylinders"] == 4, "mpg"], shade=True, color="g", label="Cyl=4", alpha=.7)
sns.kdeplot(mpg.loc[mpg["cylinders"] == 5, "mpg"], shade=True, color="deeppink", label= "Cyl=5", alpha=.7)
sns.kdeplot(mpg.loc[mpg["cylinders"] == 6, "mpg"], shade=True, color="dodgerblue", label= "Cyl=6", alpha=.7)
sns.kdeplot(mpg.loc[mpg["cylinders"] == 8, "mpg"], shade=True, color="orange", label= "Cyl=8", alpha=.7)
plt.title("Density Plot of MPG by n_Cylinders")

sns.distplot(mpg.loc[mpg['origin'] == 'usa', 'horsepower'],  color='g', label='USA', hist_kws={'alpha':.6})
sns.distplot(mpg.loc[mpg['origin'] == 'europe', 'horsepower'],  color='deeppink', label='Europe', hist_kws={'alpha':.6})
sns.distplot(mpg.loc[mpg['origin'] == 'japan', 'horsepower'], color='dodgerblue', label='Japan', hist_kws={'alpha':.6})
plt.title('Density Plot of Horsepower by origins')
plt.legend()

2. Density Curves with Histogram

3. Bandwidth Control (Bins)

Just like bins in matplotlib, in seaborn, this is controlled using the bw argument of the kdeplot function.

sns.kdeplot(mpg.loc[mpg["cylinders"] == 6, "mpg"], shade=True, color="g", label="bw: 0.1", alpha=.7,bw=.1)
sns.kdeplot(mpg.loc[mpg["cylinders"] == 6, "mpg"], shade=True, color="b", label="bw: 0.5", bw=.5)
plt.title("With  bandwidth control")