R in Practice: Pipes
The more I write code in R, the more I am impressed with the facilities that the language provides which is perfectly tailored to cleaning and tidying data, one of the most crucial steps in statistical analysis.
Hey there 👋 I’m Erhan, a software engineer. I build distributed systems and web services, most recently at Adobe. I write here about the things I build — Away from the keyboard I take photographs, draw comics and play electric guitar.
Low-level — a podcast with asyncore about software development, games and technology in general. In Turkish, for now.
Frames from wandering about with a Leica — mostly light, water and the shapes people leave behind.
A glossy Markdown editor for macOS — Obsidian-style vaults, live preview with embedded charts and diagrams, and a Claude writing agent built in.
The more I write code in R, the more I am impressed with the facilities that the language provides which is perfectly tailored to cleaning and tidying data, one of the most crucial steps in statistical analysis.
Once you get a job, and code for others and get paid for it, you are a professional, a part of the whole, a cell in business organism and the business needs to survive in the competitive economy.
The need of orchestration of heterogeneous infrastructure, non-unified characteristics of the hardware on different server systems and fluctuating resource needs of software and the challenges in resource utilisation, urges us to rethink, how to deal with the vast amount of servers in our datacenters.
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