Seaborn stacked histogram/barplot

Just stack the total histogram with the survived -0 one. It's hard to give the exact function without the precise form of the dataframe, but here's a basic example with one of seaborn examples dataset.

import matplotlib.pyplot as plt 
import seaborn as sns 
tips = sns.load_dataset("tips") 
sns.distplot(tips.total_bill, color="gold", kde=False, hist_kws={"alpha": 1}) 
sns.distplot(tips[tips.sex == "Female"].total_bill, color="blue", kde=False, hist_kws={"alpha":1}) 
plt.show()

Starting seaborn 0.11.0, you can do this

# stacked histogram
import matplotlib.pyplot as plt
f = plt.figure(figsize=(7,5))
ax = f.add_subplot(1,1,1)

# mock your data frame
import pandas as pd
import numpy as np
_df = pd.DataFrame({
    "age":np.random.normal(30,30,1000),
    "survived":np.random.randint(0,2,1000)
})

# plot
import seaborn as sns
sns.histplot(data=_df, ax=ax, stat="count", multiple="stack",
             x="age", kde=False,
             palette="pastel", hue="survived",
             element="bars", legend=True)
ax.set_title("Seaborn Stacked Histogram")
ax.set_xlabel("Age")
ax.set_ylabel("Count")