(Python) Prince MCA transformation error on new data

Question

I am using the newest version of prince (0.7.1), but this seems to be an issue on previous versions as well.

I have a categorical dataframe named 'cat' that I am attempting to find an embedding for.

mca = prince.MCA(n_components=2)
mca.fit(cat)

When I apply the learned embedding to the original dataset, everything works as it should, but when I apply it to a dataset with less data:

x = mca.transform(cat.sample(10))

I get the following error:

ValueError                                Traceback (most recent call last)
<ipython-input-28-faee8865f560> in <module>
----> 1 x = mca.transform(cat.sample(10))
      2 print(x)
      3 plot(np.array(x))

/usr/local/anaconda3/envs/upe-pipeline/lib/python3.8/site-packages/prince/mca.py in transform(self, X)
     48         if self.check_input:
     49             utils.check_array(X, dtype=[str, np.number])
---> 50         return self.row_coordinates(X)
     51 
     52     def plot_coordinates(self, X, ax=None, figsize=(6, 6), x_component=0, y_component=1,

/usr/local/anaconda3/envs/upe-pipeline/lib/python3.8/site-packages/prince/mca.py in row_coordinates(self, X)
     36         if not isinstance(X, pd.DataFrame):
     37             X = pd.DataFrame(X)
---> 38         return super().row_coordinates(pd.get_dummies(X))
     39 
     40     def column_coordinates(self, X):

/usr/local/anaconda3/envs/upe-pipeline/lib/python3.8/site-packages/prince/ca.py in row_coordinates(self, X)
    132 
    133         return pd.DataFrame(
--> 134             data=X @ sparse.diags(self.col_masses_.to_numpy() ** -0.5) @ self.V_.T,
    135             index=row_names
    136         )

/usr/local/anaconda3/envs/upe-pipeline/lib/python3.8/site-packages/scipy/sparse/base.py in __rmatmul__(self, other)
    564             raise ValueError("Scalar operands are not allowed, "
    565                              "use '*' instead")
--> 566         return self.__rmul__(other)
    567 
    568     ####################

/usr/local/anaconda3/envs/upe-pipeline/lib/python3.8/site-packages/scipy/sparse/base.py in __rmul__(self, other)
    548             except AttributeError:
    549                 tr = np.asarray(other).transpose()
--> 550             return (self.transpose() * tr).transpose()
    551 
    552     #######################

/usr/local/anaconda3/envs/upe-pipeline/lib/python3.8/site-packages/scipy/sparse/base.py in __mul__(self, other)
    514 
    515             if other.shape[0] != self.shape[1]:
--> 516                 raise ValueError('dimension mismatch')
    517 
    518             result = self._mul_multivector(np.asarray(other))

ValueError: dimension mismatch