Pandas is particularly recommended for data scientists, analysts, and engineers who need to perform data cleaning, transformation, and analysis as part of their work. It is also suitable for academics and researchers dealing with data in various formats and needing powerful tools for their data-driven research.
Based on our record, Pandas seems to be a lot more popular than Design Principles. While we know about 219 links to Pandas, we've tracked only 9 mentions of Design Principles. 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.
Libraries for data science and deep learning that are always changing. - Source: dev.to / about 1 month ago
# Read the content of nda.txt Try: Import os, types Import pandas as pd From botocore.client import Config Import ibm_boto3 Def __iter__(self): return 0 # @hidden_cell # The following code accesses a file in your IBM Cloud Object Storage. It includes your credentials. # You might want to remove those credentials before you share the notebook. Cos_client = ibm_boto3.client(service_name='s3', ... - Source: dev.to / about 2 months ago
As with any web scraping or data processing project, I had to write a fair amount of code to clean this up and shape it into a format I needed for further analysis. I used a combination of Pandas and regular expressions to clean it up (full code here). - Source: dev.to / about 2 months ago
Python’s Growth in Data Work and AI: Python continues to lead because of its easy-to-read style and the huge number of libraries available for tasks from data work to artificial intelligence. Tools like TensorFlow and PyTorch make it a must-have. Whether you’re experienced or just starting, Python’s clear style makes it a good choice for diving into machine learning. Actionable Tip: If you’re new to Python,... - Source: dev.to / 4 months ago
This tutorial provides a concise and foundational guide to exploring a dataset, specifically the Sample SuperStore dataset. This dataset, which appears to originate from a fictional e-commerce or online marketplace company's annual sales data, serves as an excellent example for learning and how to work with real-world data. The dataset includes a variety of data types, which demonstrate the full range of... - Source: dev.to / 9 months ago
Your comment is an interesting one, and I can see how it’s be helpful for some folks who are just setting out in their careers. I was asking not about style guides, but the nuanced differences between heuristics, such as NNg’s, and design principles for decision-making: https://principles.design/. Source: over 2 years ago
Principle Design is a Free Resource to learn more about designing better user interfaces and logos for your business. Access 195+ Examples and 1445 principles to learn more about design. (no-signup). Source: over 2 years ago
Http://styleguides.io/ and https://principles.design/ are worth keeping an eye on, especially for trends that come up and to see what the industry is up to. Source: over 2 years ago
Https://principles.design/ (collection, guiding ethos). Source: over 2 years ago
Https://paperform.co/blog/principles-of-design/ https://principles.design/ https://99designs.com/blog/tips/principles-of-design/. - Source: Hacker News / about 3 years ago
NumPy - NumPy is the fundamental package for scientific computing with Python
Product Disrupt - A design student's list of resources to learn Product Design
Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
Atlassian Design - Design, develop, and deliver
OpenCV - OpenCV is the world's biggest computer vision library
Checklist Design - The best UI and UX practices for production ready design.