Pandas
NumPy
Scikit-learn
OpenCV
Dataiku
Exploratory
htm.java
WEKA
Jest
react-testing-library
Vitest
Mochajs
Playwright
Vite
Jasmine
Node.js
PandasPandas 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 should be more popular than Jest. It has been mentiond 220 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.
The book introduces the core libraries essential for working with data in Python: particularly IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and related packages Familiarity with Python as a language is assumed; if you need a quick introduction to the language itself, see the free companion project, A…. - Source: dev.to / 14 days ago
Libraries for data science and deep learning that are always changing. - Source: dev.to / 5 months 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 / 6 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 / 6 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 / 8 months ago
Jest + type checking in CI. Ensured types and tests both passed. - Source: dev.to / 11 days ago
NestJS includes Jest out of the box for testing. Some people prefer changing it to Vitest, but honestly, Jest is more than good enough for now. Don’t waste time switching tools if they’re not the bottleneck. - Source: dev.to / 2 months ago
Testing ensures code reliability and maintainability. Jest, Vitest and React Testing Library are standard tools for unit and integration testing. Unit tests verify individual components, while integration tests ensure features work together. For example, testing a TodoList component might involve:. - Source: dev.to / 3 months ago
Jest or Vitest testing made tolerable. - Source: dev.to / 3 months ago
Jest for test results with emoji-level joy https://jestjs.io. - Source: dev.to / 4 months ago
NumPy - NumPy is the fundamental package for scientific computing with Python
react-testing-library - [`React Testing Library`][gh] builds on top of `DOM Testing Library` by adding
Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
Vitest - A blazing fast unit test framework powered by Vite
OpenCV - OpenCV is the world's biggest computer vision library
Mochajs - Mocha is a JavaScript test framework running on Node.js and the browser, making asynchronous testing simple.
