NumPy VS Seaborn
Compare NumPy VS Seaborn and see what are their differences
LibHunt tracks mentions of software libraries on relevant social networks. Based on that data, you can find the most popular projects and their alternatives.
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NumPy
Pandas
Scikit-learn
OpenCV
Dataiku
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WEKA
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Matplotlib
Backtrader
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Pandas
QuantConnect
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SeabornBased on our record, NumPy should be more popular than Seaborn. It has been mentiond 107 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.
In NumPy with * or multiply(). ` or multiply()` can multiply 0D or more D arrays by element-wise multiplication. - Source: dev.to / about 2 months ago
Data science projects often use numpy. However, numpy objects are not JSON-serializable and therefore require conversion to standard python objects in order to be saved:. - Source: dev.to / 2 months ago
Numpy: A library for scientific computing in Python. - Source: dev.to / 5 months ago
Python has become a preferred language for data analysis due to its simplicity and robust library ecosystem. Among these, NumPy stands out with its efficient handling of numerical data. Let’s say you’re working with numbers for large data sets—something Python’s native data structures may find challenging. That’s where NumPy arrays come into play, making numerical computations seamless and speedy. - Source: dev.to / 6 months ago
A majority of software in the modern world is built upon various third party packages. These packages help offload work that would otherwise be rather tedious. This includes interacting with cloud APIs, developing scientific applications, or even creating web applications. As you gain experience in python you'll be using more and more of these packages developed by others to power your own code. In this example... - Source: dev.to / 7 months ago
If you are doing data analysis I don't think any of the 3 pieces of software you mentioned are going to be that helpful. I see these products as tools for data visualization and reporting i.e. Presenting prepared datasets to users in a visually appealing way. They aren't as well suited for serious analytics. I can't comment on Superset or Tableau but I am familiar with Power BI (it has been rolled out across my... - Source: Hacker News / 2 months ago
It's referring to the seaborn library (https://seaborn.pydata.org/), a Python library for data visualization (built on top of matplotlib). - Source: Hacker News / 2 months ago
While it’s not perfect and it’s not ggplot2, Seaborn is definitely a big improvement over bare matplotlib. You can still use matplotlib to modify the plots it spits out if you want to but the defaults are pretty good most of the time. https://seaborn.pydata.org/. - Source: Hacker News / 3 months ago
Seaborn: A statistical data visualization library based on Matplotlib, enhancing the aesthetics and visual appeal of statistical graphics. - Source: dev.to / 2 months ago
You've done a great job presenting this. Maybe you already know, but seaborne is an extension of matplotlib that makes it pretty easy to "beautify" matplotlib charts. Source: 10 months ago
Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.
Matplotlib - matplotlib is a python 2D plotting library which produces publication quality figures in a variety...
Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
Backtrader - Backtrader is a complete and advanced python framework that is used for backtesting and trading.
OpenCV - OpenCV is the world's biggest computer vision library
Streak.world - Streak.world is one of the leading algo trading platforms, allowing you to design an algorithm to automate your trading strategies without any coding skills needed.