As developers, the terminal can be our second home.
Sometimes Kaggle is not enough, and you need to generate your own data set.
Sometimes you open a big Dataset with Python’s Pandas, try to get a few metrics, and the whole thing just freezes horribly. Dask Dataframes may solve your problem.
As a Data Scientist, I spend about a third of my time looking at data and trying to get meaningful insights, the discipline some call exploratory data analysis. These are the tools I use the most. Today we will be looking at two awesome tools, following closely the code I uploaded on this github project. One is Jupyter Notebooks, and the other is a Python Framework called Pandas.
Whether you’re a Data Scientist, a Web Developer working in an API, or any other of a long list of roles, chances are you’ll stumble upon Python at some point. If so, List Comprehensions are to be expected. Some of us love Python for its simplicity, its fluidity and legibility. Others hate it for not being as performant as C or pure Assembly, having Duck Typing, or being single-threaded (ish). No matter what group you belong to, if you’re in…
Vim is the Swiss-army knife of text editing. It’s not enough that it has a feature and command for almost every use case and user: it will also let you customize it to add whatever specific things you think it’s missing. In this tutorial we’re going to see how to use two of those features: multiple windows, and multiple vim registers.