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.
TasteDive is particularly recommended for individuals who enjoy discovering new media, such as music enthusiasts, movie buffs, avid readers, and anyone who likes to explore new entertainment possibilities based on their existing preferences.
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Based on our record, Pandas should be more popular than TasteDive. It has been mentiond 219 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.
Libraries for data science and deep learning that are always changing. - Source: dev.to / 29 days 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
They still exist. They rebranded to TasteDive, but are still doing the same service: https://tastedive.com/. - Source: Hacker News / 7 months ago
P.S. You can also use sites like BestSimilar and TasteDive. Source: about 2 years ago
Https://tastedive.com is good as you can look up your favourites and find similar artists. Source: about 2 years ago
Tastedive is one that I have come to love. Source: about 2 years ago
You can also check out https://tastedive.com/ or https://likewisetv.com/. Source: over 2 years ago
NumPy - NumPy is the fundamental package for scientific computing with Python
Letterboxd - Letterboxd is a social site for sharing your taste in film, now in public beta.
Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
IMDb - Internet Movie Database
OpenCV - OpenCV is the world's biggest computer vision library
Simkl - Simkl is a TV, anime, and movie tracker that keeps a history of all the shows and movies you watch in one, central location. It’s a mobile app, a website, Google Chrome extension to keep track of everything you watch and integrates with many TV apps