Based on our record, Pandas should be more popular than Seaborn. It has been mentiond 198 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.
Python is a natural fit for serverless development. It boasts a vast array of libraries, including Powertools for AWS and robust libraries for data engineers. Its versatility and excellent developer experience make it a top choice for serverless projects, offering a seamless and enjoyable development experience. - Source: dev.to / 17 days ago
In data analysis, managing the structure and layout of data before analyzing them is crucial. Python offers versatile tools to manipulate data, including the often-used Pandas reset_index() method. - Source: dev.to / 10 days ago
Dash is a Python framework that enables you to build interactive frontend applications without writing a single line of Javascript. Internally and in projects we like to use it in order to build a quick proof of concept for data driven applications because of the nice integration with Plotly and pandas. For this post, I'm going to assume that you're already familiar with Dash and won't explain that part in detail.... - Source: dev.to / 2 months ago
Last year I worked through the challenges using VisiData, Datasette, and Pandas. I walked through my thought process and solutions in a series of posts. - Source: dev.to / 5 months ago
Data analysis involves scrutinizing datasets for class imbalances or protected features and understanding their correlations and representations. A classical tool like pandas would be my obvious choice for most of the analysis, and I would use OpenCV or Scikit-Image for image-related tasks. - Source: dev.to / 5 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
NumPy - NumPy is the fundamental package for scientific computing with 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
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