Setting axis labels for histogram pandas

Labels are properties of axes objects, that needs to be set on each of them. Here's an example that worked for me:

frame = pd.DataFrame([np.random.rand(20), np.sign(np.random.rand(20) - 0.5)]).T
frame.columns = ['Age', 'Survived']

# Note that you can let the hist function do the groupby
# the function hist returns the list of axes created
axarr = frame.hist(column='Age', by = 'Survived', sharex=True, sharey=True, layout = (2, 1))

for ax in axarr.flatten():
    ax.set_xlabel("Age")
    ax.set_ylabel("Individuals")

I came here looking for the same thing, but found it easier to do in plotly

import plotly.express as px

px.histogram(df, x="t_depth", nbins=150).update_layout(
    xaxis = dict(dtick=10), bargap=0.2
)

For those looking for a simple one line solution in matplotlib, just tack on .set_xlabel("your_label") to the end.

df.col_to_graph.plot.hist(bins=10, alpha=0.5, figsize=(16, 12)).set_xlabel("col_to_graph label")