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statsmodels VS python pillow

Compare statsmodels VS python pillow and see what are their differences

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statsmodels logo statsmodels

Statsmodels: statistical modeling and econometrics in Python - statsmodels/statsmodels

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The friendly PIL fork (Python Imaging Library). Contribute to python-pillow/Pillow development by creating an account on GitHub.
  • statsmodels Landing page
    Landing page //
    2023-08-18
  • python pillow Landing page
    Landing page //
    2023-08-18

statsmodels videos

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Linear Regressions with StatsModels

More videos:

  • Review - Code review - Z Test using statsmodels
  • Review - Code Review: Analyse Training VAR statsmodels with a real world dataset

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Category Popularity

0-100% (relative to statsmodels and python pillow)

statsmodels

python pillow

Development Tools
31 31%
Development Tools
69% 69
Data Science And Machine Learning
24 24%
Data Science And Machine Learning
76% 76
Game Development
100 100%
Game Development
0% 0
Python Tools
0 0%
Python Tools
100% 100

User comments

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Reviews

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python pillow Reviews

10 Python Libraries for Computer Vision
Pillow (PIL Fork) is a powerful library for image processing tasks. It supports various image formats and provides functionalities such as resizing, cropping, filtering, and adding text to images. Whether you’re working with photographs or generating visual content, Pillow offers an array of tools to manipulate images effectively.
Source: clouddevs.com

Social recommendations and mentions

Based on our record, statsmodels seems to be more popular. It has been mentiond 4 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

statsmodels mentions (4)

  • [P] statsmodels.tsa.holtwinters.ExponentialSmoothing results in NaN forecasts and parameters when fitting on entire dataset using known parameters from training model.
    I reckon you're more likely to get a good response on their Github page than here. Unless a dev happens to see this post. Source: over 1 year ago
  • How do you usually build your models?
    Since you are using python, pandas, scikit-learn, scipy, and statsmodels are what you are looking for. Source: over 1 year ago
  • Can we solve serverless cold starts?
    In case you're really worried about cold start latency and your application load shows high variance in the number of concurrent requests, you might want to get a bit fancier. You could use time-series forecasting to anticipate how many containers should be warmed at each point in time. StatsModels is an open-source project that offers the most common algorithms for working with time-series. Here's a good... - Source: dev.to / almost 3 years ago
  • Advice required to choose appropriate software for an assignment
    Can't you get a student discount for Stata? R would definitely be able to handle everything. For Python, have a look through the statsmodel package https://github.com/statsmodels/statsmodels. Source: about 3 years ago

python pillow mentions (0)

We have not tracked any mentions of python pillow yet. Tracking of python pillow recommendations started around Mar 2021.

What are some alternatives?

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Mahotas - Mahotas is a computer vision and image processing library for Python.

python xlrd - Please use openpyxl where you can... Contribute to python-excel/xlrd development by creating an account on GitHub.

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