Jupyter Coding Console in ATH Precision (AI/ML Platform)
**Analyttica Datalab's AI/ML Platform ATH Precision provides a feature of** [**#Jupyter**](https://www.linkedin.com/feed/hashtag/?highlightedUpdateUrns=urn%3Ali%3Aactivity%3A6641233793892085760&keywords=%23Jupyter&originTrackingId=jMi4N7BF8PzzsWq4%2FCle2w%3D%3D) Coding Console
With the coding console, you get the power to [**#code**](https://www.linkedin.com/feed/hashtag/?highlightedUpdateUrns=urn%3Ali%3Aactivity%3A6641233793892085760&keywords=%23code&originTrackingId=jMi4N7BF8PzzsWq4%2FCle2w%3D%3D) and [**#create**](https://www.linkedin.com/feed/hashtag/?highlightedUpdateUrns=urn%3Ali%3Aactivity%3A6641233793892085760&keywords=%23create&originTrackingId=jMi4N7BF8PzzsWq4%2FCle2w%3D%3D) your own function.
Check out the platform here - [https://www.analyttica.com/precision/](https://www.analyttica.com/precision/)
https://preview.redd.it/t70jxjqep0m41.png?width=2208&format=png&auto=webp&s=a987b04f224ab666b742166da30af7db1143bc07
/r/JupyterNotebooks
https://redd.it/fguuyt
**Analyttica Datalab's AI/ML Platform ATH Precision provides a feature of** [**#Jupyter**](https://www.linkedin.com/feed/hashtag/?highlightedUpdateUrns=urn%3Ali%3Aactivity%3A6641233793892085760&keywords=%23Jupyter&originTrackingId=jMi4N7BF8PzzsWq4%2FCle2w%3D%3D) Coding Console
With the coding console, you get the power to [**#code**](https://www.linkedin.com/feed/hashtag/?highlightedUpdateUrns=urn%3Ali%3Aactivity%3A6641233793892085760&keywords=%23code&originTrackingId=jMi4N7BF8PzzsWq4%2FCle2w%3D%3D) and [**#create**](https://www.linkedin.com/feed/hashtag/?highlightedUpdateUrns=urn%3Ali%3Aactivity%3A6641233793892085760&keywords=%23create&originTrackingId=jMi4N7BF8PzzsWq4%2FCle2w%3D%3D) your own function.
Check out the platform here - [https://www.analyttica.com/precision/](https://www.analyttica.com/precision/)
https://preview.redd.it/t70jxjqep0m41.png?width=2208&format=png&auto=webp&s=a987b04f224ab666b742166da30af7db1143bc07
/r/JupyterNotebooks
https://redd.it/fguuyt
Linkedin
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Basic Power Analysis Discrepancy
Hi all,
I'm working on a power analysis to better understand how the process works for linear regression and interactions effects. I'm trying to create a function that simulates a dataset, adds participants to it based on an argument that can be specified (e.g., to see how many more people one would need to have power reach a certain threshold), and then counts a proportion of p-values less than an alpha level. In this case, the model is
dv ~ dx_status + ybocs + dx_status*ybocs
and I'm interested in learning how many participants I'd need to get a statistically significant p-value for the interaction term.
Here is the code:
import pandas as pd
import numpy as np
import statsmodels.api as sm
import statsmodels.formula.api as smf
hyp2_pvalues_list = [] #create an empty list
np.random.seed(4) #sets a seed for the random number generator
def pwrcurve_hypoth2(addtogroup = 0, simulations = 1000, es = 0.5, dv_sd = 3.9, bdi_sd = 5, ybocs_sd = 5,
alpha = .05):
for x in range(simulations):
/r/pystats
https://redd.it/lumrgk
Hi all,
I'm working on a power analysis to better understand how the process works for linear regression and interactions effects. I'm trying to create a function that simulates a dataset, adds participants to it based on an argument that can be specified (e.g., to see how many more people one would need to have power reach a certain threshold), and then counts a proportion of p-values less than an alpha level. In this case, the model is
dv ~ dx_status + ybocs + dx_status*ybocs
and I'm interested in learning how many participants I'd need to get a statistically significant p-value for the interaction term.
Here is the code:
import pandas as pd
import numpy as np
import statsmodels.api as sm
import statsmodels.formula.api as smf
hyp2_pvalues_list = [] #create an empty list
np.random.seed(4) #sets a seed for the random number generator
def pwrcurve_hypoth2(addtogroup = 0, simulations = 1000, es = 0.5, dv_sd = 3.9, bdi_sd = 5, ybocs_sd = 5,
alpha = .05):
for x in range(simulations):
/r/pystats
https://redd.it/lumrgk
reddit
Basic Power Analysis Discrepancy
Hi all, I'm working on a power analysis to better understand how the process works for linear regression and interactions effects. I'm trying to...
Release: NiceGUI 1.2.7 with ui.download, easier color definitions, "aggrid from pandas dataframe" and much more
With 21 contributors the just released NiceGUI 1.2.7 is again a wonderful demonstration of the strong growing community behind our easy to use web-based GUI library for Python. NiceGUI has a very gentle learning curve while still offering the option for advanced customizations. By following a backend-first philosophy you can focus on writing Python code. All the web development details are handled behind the scenes.
### New features and enhancements
- introduce `ui.download`
- introduce color arguments for elements like
- allow running in Python’s interactive mode by auto-disabling reload
- allow creating
- fix navigation links behind reverse proxy with subpath
- allow sending "leading" and/or "trailing" events when throttling
- raise an exception when hiding internal routes with
- add “dark” color to
### Documentation
- enhance Trello "drag and drop" example to use a ToDo data model
- add workaround to docs for native mode when WebView2Loader.dll fails load
- add documentation and demo about element borders inside a
- add hint about exception when running executable with no console on Windows
Of course the release also includes some bugfixes (see release notes for details). Thanks to everyone who was involved in making this release happen.
/r/Python
https://redd.it/12m03v5
With 21 contributors the just released NiceGUI 1.2.7 is again a wonderful demonstration of the strong growing community behind our easy to use web-based GUI library for Python. NiceGUI has a very gentle learning curve while still offering the option for advanced customizations. By following a backend-first philosophy you can focus on writing Python code. All the web development details are handled behind the scenes.
### New features and enhancements
- introduce `ui.download`
- introduce color arguments for elements like
ui.button that accept Quasar, Tailwind, and CSS colors- allow running in Python’s interactive mode by auto-disabling reload
- allow creating
ui.aggrid from pandas dataframe- fix navigation links behind reverse proxy with subpath
- allow sending "leading" and/or "trailing" events when throttling
- raise an exception when hiding internal routes with
app.add_static_files- add “dark” color to
ui.colors### Documentation
- enhance Trello "drag and drop" example to use a ToDo data model
- add workaround to docs for native mode when WebView2Loader.dll fails load
- add documentation and demo about element borders inside a
ui.card- add hint about exception when running executable with no console on Windows
Of course the release also includes some bugfixes (see release notes for details). Thanks to everyone who was involved in making this release happen.
/r/Python
https://redd.it/12m03v5
GitHub
nicegui/examples/nginx_subpath at main · zauberzeug/nicegui
Create web-based interfaces with Python. The nice way. - nicegui/examples/nginx_subpath at main · zauberzeug/nicegui
Automating the creation of Forms, Views, and Templates
I'm trying to use a couple loops to automatically build from the models each form, view, and url, and have a single template file render each list. I'm newer to python but I do know generating classes and functions like this is not best practice to say the least, however its something I wanted to try for my own project. What I'm interested in is playing with on the front end with my primary fact table and not the two dozen or so dimension tables, which may require frequent field additions or abstractions.
base/app/models.py
from django.db import models
from django.contrib.auth.models import User
#Create your models here.
class UserTypeModel(models.Model):
code = models.CharField(maxlength = 10, primarykey = True)
name = models.CharField(maxlength = 100, blank = False, unique = True)
def str(self):
return self.name
/r/djangolearning
https://redd.it/135v43t
I'm trying to use a couple loops to automatically build from the models each form, view, and url, and have a single template file render each list. I'm newer to python but I do know generating classes and functions like this is not best practice to say the least, however its something I wanted to try for my own project. What I'm interested in is playing with on the front end with my primary fact table and not the two dozen or so dimension tables, which may require frequent field additions or abstractions.
base/app/models.py
from django.db import models
from django.contrib.auth.models import User
#Create your models here.
class UserTypeModel(models.Model):
code = models.CharField(maxlength = 10, primarykey = True)
name = models.CharField(maxlength = 100, blank = False, unique = True)
def str(self):
return self.name
/r/djangolearning
https://redd.it/135v43t
Reddit
r/djangolearning on Reddit: Automating the creation of Forms, Views, and Templates
Posted by u/burmeisterN - 1 vote and 1 comment
Cant register users using this view with REST (Invalid password format or unknown hashing algorithm)
@api_view(['POST'])
def register(request):
serializer=UserSerializer(data=request.data)
if serializer.is_valid():
serializer.save()
#user=User.objects.create_user(username=request.data['username'])
#user.set_password(request.data['password']) #hash password
#user.save()
user=User.objects.get(username=request.data['username'])
token=Token.objects.create(user=user) #create token
return Reponse({"token":token.key, "user":serializer.data})
else:
return Response(serializer.errors)
Everything commented is something i tried before
imports:
from django.contrib.auth.models import User
from rest_framework.authtoken.models import Token
User serializer:
class UserSerializer(serializers.ModelSerializer):
class Meta(object):
model= User
fields = ['id','username','password','email']
​
/r/djangolearning
https://redd.it/181xhg4
@api_view(['POST'])
def register(request):
serializer=UserSerializer(data=request.data)
if serializer.is_valid():
serializer.save()
#user=User.objects.create_user(username=request.data['username'])
#user.set_password(request.data['password']) #hash password
#user.save()
user=User.objects.get(username=request.data['username'])
token=Token.objects.create(user=user) #create token
return Reponse({"token":token.key, "user":serializer.data})
else:
return Response(serializer.errors)
Everything commented is something i tried before
imports:
from django.contrib.auth.models import User
from rest_framework.authtoken.models import Token
User serializer:
class UserSerializer(serializers.ModelSerializer):
class Meta(object):
model= User
fields = ['id','username','password','email']
​
/r/djangolearning
https://redd.it/181xhg4
Reddit
From the djangolearning community on Reddit
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