[Python] Seaborn Catplot similar to Pandas groupby

I am working with the Portuguese Bank Marketing dataset http://archive.ics.uci.edu/ml/datasets/Bank Marketing#

I would like to visualise the conversion rate per some categorical feature e.g. occupation or marital status.

Using pandas groupby() as show below

df.groupby(["marital","y"])["y"].count().plot(kind="bar")


I obtain the following graph

However, I would like to create a more readable graph, similar to the ones in seaborn tutorials. Where X is some categorical feature, Y is some value and the Hue groups them per some other metric.

My attempts so far result in the following errors:

sns.catplot(x = df["job"].value_counts().index,
y = df["job"].value_counts().values,
hue="y",
data=df,
kind="bar")

ValueError: Grouper and axis must be same length


Any pointers will be appreciated!

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