Overview PyCharm, DataSpell, and VS Code offer strong features for large projects.JupyterLab and Google Colab simplify data ...

Already using NumPy, Pandas, and Scikit-learn? Here are seven more powerful data wrangling tools that deserve a place in your ...

Positron is Posit's new, free IDE for data science. Users can work with Python and R. It explicitly does not replace RStudio. A central feature of Positron is the Variable & Data Frame Explorer. It ...

These simple operations and others are why NumPy is a building block for statistical analysis with Python. NumPy also makes ...

Python, Julia, and Rust are three leading languages for data science, but each has different strengths. Here's what you need to know. The most powerful and flexible data science tool is a programming ...

In what might be seen as a challenge to the super-popular combination of Visual Studio Code and its Python extension, JetBrains is testing its own IDE for data scientists. Called JetBrains DataSpell, ...

It's not surprising that a data science/machine learning survey says most pros use a Jupyter-based IDE for their work, as Jupyter Notebooks (and Python) are pervasive in the industry. What might be ...

Java can handle large workloads, and even if it hits limitations, peripheral JVM languages such as Scala and Kotlin can pick up the slack. But in the world of data science, Java isn't always the go-to ...

What first interested you in data analysis, Python and pandas? I started my career working in ad tech, where I had access to log-level data from the ads that were being served, and I learned R to ...

What are some use cases for which it would be beneficial to use Haskell, rather than R or Python, in data science? originally appeared on Quora: the place to gain and share knowledge, empowering ...