How to know the type of features (numeric, categorial) that Featuretools generates?
In the generated feature definitions, there is a variable_type attribute to see the type of feature.
feature_matrix, feature_defs = ft.dfs(target_entity='customers', entityset=es)
feature_defs[1], feature_defs[1].variable_type
(<Feature: COUNT(sessions)>, featuretools.variable_types.variable.Numeric)
Let me know if that helps.
Related
For POS tagging, I am using spacy. I found pos tags for gerund and infinitives are not given. How can I add these two new tags in spacy? I can change tags within the list but not able to add new tags. Please help. Thank you.
**pattern = [tokens[t].pos_== "VERB" and tokens[t-1].pos_=="ADP" for t in range
(len(tokens)-1)]
spacy.pipeline.tagger.Tagger.add_label(u"GERUND")**
this gives error:
TypeError: add_label() takes exactly 2 positional arguments (1 given)
Rather than modifying the output, it sounds like you should just use the .tag_ attribute, which is more detailed and language specific. In this case the value will be VB for an infinitive and VBG for a gerund. These are Penn Treebank Tags.
The .pos_ values are from Universal Dependencies, and are less detailed but appropriate for multi-lingual applications.
I was looking at typings set up on the web but I was curious if I can have multiple types. Example:
self.test: str or None = None
It shows valid on my intellisense but I wasnt sure if it computed it different.
I was trying to implement something equivalent to typescript.
test: number|null = null;
But I didn't see specific types in this regard. Pretty much all my items have the option of being None/Null.
You should use Union https://docs.python.org/3/library/typing.html#typing.Union
from typing import Union
self.test: Union[str, None]
You can use Optional[X] as a shorthand for Union[X, None].
I am following this tutorial on named tuple with specification of variable types. However, I modified the code (below), and even if I enter values of wrong types, there was no error message or programming break as a result. I understand you can write your own try/except to raise error exception, but is there a readily-available solution/syntax to enforce users entering the right type of variables.
from typing import NamedTuple
class Pet(NamedTuple):
pet_name: str
pet_type: str
def __repr__(self):
return f"{self.pet_name}, {self.pet_type}"
cleons_pet = Pet('Cotton', 'owl')
print('cleons_pet: ', cleons_pet)
cleons_pet_v2 = Pet(222, 1)
print('cleons_pet_v2: ', cleons_pet_v2)
# Output
cleons_pet: Cotton, owl
cleons_pet_v2: 222, 1
[Finished in 0.1s]
The type hints in python will not be evaluated by python itself! See PEP484
While these annotations are available at runtime through the usual annotations attribute, no type checking happens at runtime. Instead, the proposal assumes the existence of a separate off-line type checker which users can run over their source code voluntarily.
There are at least two projects which offer offline type checking (mypy and pyre). You should definitely use them if you are using type hints in your project.
If you want to validate the input while running the application, you have to either convince the offline type checkers by validating the data by yourself or use a third-party library. I know of attrs, where you can use validators or type annotations for online validation.
I have a class in UML that looks like this (it's in German, but I think it doesn't matter):
The first method takes an array of 4 "Rohstoffkarte". That's an abstract class and I have 5 concrete sub-classes for it. Now I want to check (with OCL) that all 4 instances in the array are from the same sub-class.
Any idea how to do this? I'm working with MagicDraw.
Thanks.
you can use
oclIsKindOf, oclIsTypeOf to check type conformance, and use oclType to get the type of an object.
See OMG Object Constraint Language Specification Version 2.3.1, p.22
http://www.omg.org/spec/OCL/2.3.1
it's very common in Ada to create a derived type say a new Float type with the last element being Float'Last. I have not yet seen someone using Float'Safe_Large instead of the attribute Float'Last when defining a new Float type. On my 32-bit machine, both
Put( Float'Image( Float'Last ));
and
Put( Float'Image( Float'Safe_large ));
return me the value 3.402..E38
I would like to know the difference between these two number attributes and perhaps also why 'Safe_Large is not as commonly used as the attribute 'Last.
Thanks a lot...
Presently, the Last attribute is defined for any scalar subtype. Now obsolete, Safe_Large is available in GNAT as an implementation defined attribute for compatibility with Ada 83. The Ada 95 Rationale offers some insights about the change in the discussion on "Safe Range".