Shiny Reviews

Pandas Reviews

Shiny mentions (32)

• R: Introduction to Data Science

  A lighterweight alternative to renv is to use Posit Public Package Manage (https://packagemanager.posit.co/) with a pinned date. That doesn't help if you're installing packages from a mix of places, but if you're only using CRAN packages it lets you get everything as of a fixed date. And of course on the web side you have shiny (https://shiny.posit.co), which now also comes in a python flavour. - Source: Hacker News / 4 months ago

• Reflex – Web apps in pure Python

  Sometimes the war is lost even before the battle begins. During grad school, I wrote a whole bunch of web apps entirely in R using Shiny. It was clunky as hell, but yeah, it worked. I went looking for what's up with Shiny these days and found this - https://shiny.posit.co/ So yeah, full on pivot into python. Pip install shiny. Alright! "No web development skills required. Develop web apps entirely in R I mean... - Source: Hacker News / 11 months ago

• PSA: You don't need fancy stuff to do good work.

  Python's pandas, NumPy, and SciPy libraries offer powerful functionality for data manipulation, while matplotlib, seaborn, and plotly provide versatile tools for creating visualizations. Similarly, in R, you can use dplyr, tidyverse, and data.table for data manipulation, and ggplot2, lattice, and shiny for visualization. These packages enable you to create insightful visualizations and perform statistical analyses... Source: about 1 year ago

• A project to show off my basic R skills

  We work along side bio-statisticians and data analysts, from my experience in this world I recommend to build some plots/graphs in R based on some information you find appealing. After you have some work to show off to potential employers , learn Shiny and publish those graphs online as your portfolio. Source: about 1 year ago

• Greatest projects that you have done?

  One of the most difficult yet most fun projects I’ve done. Using Shiny to make an app, all coded in R! Source: over 1 year ago

Pandas mentions (201)

• Essential Deep Learning Checklist: Best Practices Unveiled

  How to Accomplish: Use statistical analysis tools and libraries (e.g., Pandas for tabular data) to calculate and visualize these characteristics. For image datasets, custom scripts to analyze object sizes or mask distributions can be useful. Tools like OpenCV can assist in analyzing image properties, while libraries like Pandas and NumPy are excellent for tabular and numerical analysis. To address class... - Source: dev.to / 8 days ago

• Awesome List

  Pandas - A powerful data analysis and manipulation library for Python. Pandas Documentation - Official documentation. - Source: dev.to / 13 days ago

• The ultimate guide to creating a secure Python package

  It's also possible for you to give a package an alias by using the as keyword. For instance, you could use the pandas package as pd like this:. - Source: dev.to / about 1 month ago

• AWS Serverless Diversity: Multi-Language Strategies for Optimal Solutions

  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 / 2 months ago

• Pandas reset_index(): How To Reset Indexes in Pandas

  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 / about 2 months ago