I'm practicing my ML Classification skills on The Billionaire Characteristics Database dataset.

I'm using sframe for loading and manipulating the data and seaborn for visualization.

In the process of data analysis, I wanted to draw a box plot grouped by a categorical variable, like this one from seaborn tutorial:

In the dataset, there's a networthusbillion numerical variable and selfmade categorical variable that states whether a billionaire is self-made or (s)he has inherited the bucks.

When I try to draw a similar box plot using sns.boxplot(x='selfmade', y='networthusbillion', data=data), it throws the following error:

---------------------------------------------------------------------
AttributeError                            Traceback (most recent call last)
<ipython-input-17-f4bd651c2ae7> in <module>()
----> 1 sns.boxplot(x='selfmade', y='networthusbillion', data=billionaires)

/home/iulian/.virtualenvs/data-science-python2/lib/python2.7/site-packages/seaborn/categorical.pyc in boxplot(x, y, hue, data, order, hue_order, orient, color, palette, saturation, width, fliersize, linewidth, whis, notch, ax, **kwargs)
   2127     plotter = _BoxPlotter(x, y, hue, data, order, hue_order,
   2128                           orient, color, palette, saturation,
-> 2129                           width, fliersize, linewidth)
   2130 
   2131     if ax is None:

/home/iulian/.virtualenvs/data-science-python2/lib/python2.7/site-packages/seaborn/categorical.pyc in __init__(self, x, y, hue, data, order, hue_order, orient, color, palette, saturation, width, fliersize, linewidth)
    420                  width, fliersize, linewidth):
    421 
--> 422         self.establish_variables(x, y, hue, data, orient, order, hue_order)
    423         self.establish_colors(color, palette, saturation)
    424 

/home/iulian/.virtualenvs/data-science-python2/lib/python2.7/site-packages/seaborn/categorical.pyc in establish_variables(self, x, y, hue, data, orient, order, hue_order, units)
    136             # See if we need to get variables from `data`
    137             if data is not None:
--> 138                 x = data.get(x, x)
    139                 y = data.get(y, y)
    140                 hue = data.get(hue, hue)

AttributeError: 'SFrame' object has no attribute 'get'

I tried the following forms to draw the box plot - none of them achieved the result:

sns.boxplot(x=billionaires['selfmade'], y=billionaires['networthusbillion'])
sns.boxplot(x='selfmade', y='networthusbillion', data=billionaires['selfmade', 'networthusbillion'])

However, I could draw a box plot using sframe, but without grouping by selfmade:

sns.boxplot(x=billionaires['networthusbillion'])

So, my question is: Is there a way to draw a box plot grouped by a categorical variable using an sframe? Maybe I'm doing something wrong?

By the way, I managed to draw it using a pandas.DataFrame using the same syntax (sns.boxplot(x='selfmade', y='networthusbillion', data=data)), so maybe grouping using an sframe with seaborn is just not implemented yet.

TL;DR

Grouping using an sframe with seaborn is just not implemented yet.

---

After digging into the seaborn's source code, I found out that it is designed specifically to work with pandas.DataFrame. Taking the absolutelyNoWarranty's suggestion in their answer, I got the following error:

TypeError: __getitem__() takes exactly 2 arguments (3 given)

Taking a look at the args in the get function on call, there's this data:

('gender', 'gender')

This happens because of this code in the source code for BoxPlot:

# See if we need to get variables from `data`
if data is not None:
    x = data.get(x, x)
    y = data.get(y, y)
    hue = data.get(hue, hue)
    units = data.get(units, units)

It tries to get the value and uses the same value as a fallback in case it doesn't exist. This causes an error in the __getitem__(), because it gets called with (self, 'gender', 'gender') arguments.

I tried to rewrite the get() function as follows:

def get(self, *args):
    return self.__getitem__(args[0]) if args[0] else None  # The `None` is here because the `units` in the source code is `None` for boxplots.

And here I got the error that ended my tries:

TypeError: 'SArray' object is not callable

Taking a look at the source code, it checks whether the y data is a pd.Series and if not, it converts y value into one:

if not isinstance(vals, pd.Series):
    vals = pd.Series(vals)

# Group the val data
grouped_vals = vals.groupby(grouper)

When executing the vals.groupby(grouper) (grouper still being an SArray instance), it goes into pandas core workings where the SArray is called and the error is thrown. End of story.