ggplot geom_histogram behaves differently between Python and R

I am trying to do some exploratory data analysis and I have a data frame with an integer age column and a "category" column. Making a histogram of the age is easy enough. What I want to do is maintain this age histogram but color the bars based on the categorical variables.

import numpy as np 
import pandas as pd
ageSeries.hist(bins=np.arange(-0.5, 116.5, 1))

I was able to do what I wanted easily in one line with ggplot2 in R

ggplot(data, aes(x=Age, fill=Category)) + geom_histogram(binwidth = 1)

I wasn't able to find a good solution in Python, but then I realized there was a ggplot2 library for Python and installed it. I tried to do the same ggplot command...

ggplot(data, aes(x="Age", fill="Category")) + geom_histogram(binwidth = 1)

Looking at these results we can see that the different categories are treated as different series and and overlaid rather than stacked. I don't want to mess around with transperancies, and I still want to maintain the overall distribution of the the population.

Is this something I can fix with a parameter in the ggplot call, or is there a straightforward way to do this in Python at all without doing a bunch of extra dataframe manipulations?