Combinatorics.jl VS JLD2.jl

Compare Combinatorics.jl vs JLD2.jl and see what are their differences.

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Combinatorics.jl JLD2.jl
1 2
208 523
0.0% 1.3%
6.5 8.1
24 days ago 5 days ago
Julia Julia
GNU General Public License v3.0 or later GNU General Public License v3.0 or later
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

Combinatorics.jl

Posts with mentions or reviews of Combinatorics.jl. We have used some of these posts to build our list of alternatives and similar projects.
  • Odds of matching six sided dice
    1 project | /r/Probability | 18 Sep 2021
    For the exact solution, I split it into a few parts, one of which required iterating over multiset combinations, for which there is already code provided in the Combinatorics.jl package. I copy/pasted the pieces that I needed:

JLD2.jl

Posts with mentions or reviews of JLD2.jl. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-02-17.

What are some alternatives?

When comparing Combinatorics.jl and JLD2.jl you can also consider the following projects:

julia - The Julia Programming Language

Chain.jl - A Julia package for piping a value through a series of transformation expressions using a more convenient syntax than Julia's native piping functionality.

Plots.jl - Powerful convenience for Julia visualizations and data analysis

Rocket.jl - Functional reactive programming extensions library for Julia

StatsWithJuliaBook

PlotDocs.jl - Documentation for Plots.jl

julia_titanic_model - Titanic machine learning model and web service

seaborn - Statistical data visualization in Python

DataFrames.jl - In-memory tabular data in Julia

NumPy - The fundamental package for scientific computing with Python.

Pandas - Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more

ScikitLearn.jl - Julia implementation of the scikit-learn API https://cstjean.github.io/ScikitLearn.jl/dev/