RSpec VS Pandas
Compare RSpec VS Pandas and see what are their differences
LibHunt tracks mentions of software libraries on relevant social networks. Based on that data, you can find the most popular projects and their alternatives.
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RSpec
Cucumber
JUnit
PHPUnit
Arquillian
Selenium
Capybara
Testcontainers
Pandas
NumPy
Scikit-learn
OpenCV
Dataiku
Exploratory
htm.java
WEKA
RSpec 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 RSpec. 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.
I am very comfortable with Minitest in Ruby. When I started to learn Rails, though, I was surprised by how different RSpec was. In case .NET testing is equally unlike the xUnit style, I should learn the idioms. - Source: dev.to / 3 months ago
It supports both RSpec and Minitest as well as any other testing gem. There are flexible configurations options which allow to configure editor with needed testing tool. - Source: dev.to / 7 months ago
I'm a huge supporter for TDD(Test Driven Development). Almost every piece code should be tested. During my co-op more than half of the time I spent writing test for my PR. I believe that experience really helped me understand the necessity of testing. I was surprised to see how similar the testing framework in JS and Ruby are. I used Jest which is very similar to RSpec I have used during my co-op. To mock http... - Source: dev.to / 7 months ago
The describe and it keywords are popularly used in other JavaScript testing frameworks to write and organize unit tests. This style originated in Ruby's Rspec testing library and is commonly known as spec-style testing. - Source: dev.to / 11 months ago
5. Automated Tests: Unit tests are automated tests that verify the behavior of a small unit of code in isolation. I like to write unit tests for every bug reported by a user. This way, I can reproduce the bug in a controlled environment and verify that the fix works as expected and that we wont see a regression. There are many different JavaScript test frameworks like Jest, cypress, mocha, and jasmine. We use... - Source: dev.to / 11 months ago
Libraries for data science and deep learning that are always changing. - Source: dev.to / about 2 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 / 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 / 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 / 10 months ago
Cucumber - Cucumber is a BDD tool for specification of application features and user scenarios in plain text.
NumPy - NumPy is the fundamental package for scientific computing with Python
JUnit - JUnit is a simple framework to write repeatable tests.
Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
PHPUnit - Application and Data, Build, Test, Deploy, and Testing Frameworks
OpenCV - OpenCV is the world's biggest computer vision library