def convert_variable_type(self, variable_id, new_type,
convert_data=True,
**kwargs):
"""Convert variable in dataframe to different type
Args:
variable_id (str) : Id of variable to convert.
new_type (subclass of `Variable`) : Type of variable to convert to.
entityset (:class:`.BaseEntitySet`) : EntitySet associated with this entity.
convert_data (bool) : If True, convert underlying data in the EntitySet.
Raises:
RuntimeError : Raises if it cannot convert the underlying data
Examples:
>>> es["customer"].convert_variable_type("education_level", vtypes.Categorical, EntitySet)
True
"""
if convert_data:
# first, convert the underlying data (or at least try to)
self.df = convert_variable_data(df=self.df,
column_id=variable_id,
new_type=new_type,
**kwargs)
# replace the old variable with the new one, maintaining order
variable = self._get_variable(variable_id)
new_variable = new_type.create_from(variable)
self.variables[self.variables.index(variable)] = new_variable
def test_convert_variable_data():
df = pd.DataFrame({
'id': [0, 1, 2],
'category': ['a', 'b', 'a'],
'ints': ['1', '2', '1'],
'boolean': [True, False, True],
'date': ['3/11/2000', '3/12/2000', '3/13/2000'],
'integers': [1, 2, 1]
})
# Categorical -> Numeric
init_dtype = df['ints'].dtype.name
df = convert_variable_data(df=df,
column_id='ints',
new_type=vtypes.Numeric)
assert init_dtype != df['ints'].dtype.name
assert df['ints'].dtype.name in vtypes.PandasTypes._pandas_numerics
# Numeric -> Boolean
init_dtype = df['ints'].dtype.name
df = convert_variable_data(df=df,
column_id='ints',
new_type=vtypes.Boolean,
true_val=1,
false_val=2)
assert init_dtype != df['ints'].dtype.name
# Categorical -> Datetime
init_dtype = df['date'].dtype.name
df = convert_variable_data(df=df,
column_id='date',
new_type=vtypes.Datetime)
assert init_dtype != df['date'].dtype.name
assert df['date'].dtype.name in vtypes.PandasTypes._pandas_datetimes
