"""Private methods for handling errors throughout imputation analysis."""
from pandas.api.types import is_string_dtype
from pandas.api.types import is_numeric_dtype
# ERROR HANDLING
# --------------
def _not_num_series(m, s):
"""Private method to detect columns of Matrix that are not categorical."""
if not is_numeric_dtype(s):
t = s.dtype
err = f"{m} not appropriate for Series {s.name} of type {t}."
raise TypeError(err)
def _not_num_matrix(m, mat):
"""Private method to detect columns of Matrix that are not numerical."""
try:
for each_col in mat:
c = mat[each_col]
_not_num_series(m, c)
except TypeError as te:
err = f"{m} not appropriate for Matrix with non-numerical columns."
raise TypeError(err) from te
def _not_cat_series(m, s):
"""Private method to detect Series that are not categorical."""
if not is_string_dtype(s):
t = s.dtype
err = f"{m} not appropriate for Series {s.name} of type {t}."
raise TypeError(err)
def _not_cat_matrix(m, mat):
"""Private method to detect columns of Matrix that are not categorical."""
try:
for each_col in mat:
c = mat[each_col]
_not_cat_series(m, c)
except TypeError as te:
err = f"{m} not appropriate for Matrix with non-categorical columns."
raise TypeError(err) from te
