seaborn distplot two distributions code example

Example 1: seaborn boxplot multiple columns

>>> ax = sns.boxplot(x="day", y="total_bill", hue="smoker",
...                  data=tips, palette="Set3")

Example 2: multiple categories on distplot

import numpy as np
import pandas as pd
from sklearn.datasets import load_iris
import seaborn as sns

iris = load_iris()
iris = pd.DataFrame(data=np.c_[iris['data'], iris['target']],
                    columns=iris['feature_names'] + ['target'])

# Sort the dataframe by target
target_0 = iris.loc[iris['target'] == 0]
target_1 = iris.loc[iris['target'] == 1]
target_2 = iris.loc[iris['target'] == 2]

sns.distplot(target_0[['sepal length (cm)']], hist=False, rug=True)
sns.distplot(target_1[['sepal length (cm)']], hist=False, rug=True)
sns.distplot(target_2[['sepal length (cm)']], hist=False, rug=True)

sns.plt.show()

Example 3: how to overlap two barplots in seaborn

# instead of seaborn use plt.bar 

import matplotlib.pyplot as plt
import seaborn as sns

# Load the example car crash dataset
crashes = sns.load_dataset("car_crashes").sort_values("total", ascending=False)

# states of interest
txcahi = crashes[crashes['abbrev'].isin(['TX','CA','HI'])]

# Plot the total crashes
f, ax = plt.subplots(figsize=(10, 5))
plt.xticks(rotation=90, fontsize=10)

plt.bar(height="total", x="abbrev", data=crashes, label="Total", color="lightgray")
plt.bar(height="total", x="abbrev", data=txcahi, label="Total", color="red")

sns.despine(left=True, bottom=True)

Example 4: multiple categories on distploy

ordered_days = tips.day.value_counts().index
g = sns.FacetGrid(tips, row="day", row_order=ordered_days,
                  height=1.7, aspect=4,)
g.map(sns.distplot, "total_bill", hist=False, rug=True);