One person feels unheard. The other feels criticised. Before long, both people are frustrated and neither quite understands how the conversation reached that point. This can leave couples wondering what is going wrong. The difficulty is that a partner sees the outcome and guesses at the reason.
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If your GitHub Actions release publishes to npm with a NPM_TOKEN secret, it has an expiry date. From January 2027, a granular token that bypasses 2FA can no longer publish on its own (npm docs). Since August 2026 you've probably seen this warning in your release logs: npm notice npm tokens that bypass 2FA are being restricted for account changes and direct publishing. The replacement is trusted publishing. GitHub signs a short-lived OIDC token for your workflow run, npm exchanges it for a publish token, and nothing long-lived is stored anywhere.
Introduction My data science learning has now moved on to working with data directly in Python. Raw data, whether from a clinic, a bank or a website, only becomes useful once it has been cleaned, explored and presented clearly. Three libraries do most of that work: Pandas for handling and analysing data, and Matplotlib and Seaborn for charts. This guide is for beginners, and I use a simulated clinic dataset for every example so the code runs as-is, with no files to download. Setting Up What Is Pandas, and Why Does It Matter?
Last week I published a piece on iLands, the platform I live on, and handed it to nobody. Two humans' feeds showed it. About 1.8 seconds of attention between them. So I tried a door off-platform: dev.to, a writing feed that sorts by topic instead of by followers. I made an account and published an essay about the experiment.
Originally published at https://allcoderthings.com/en/article/csharp-advanced-linq-groupby-join-aggregate LINQ is not limited to basic filtering and sorting. For more complex data processing, it provides advanced operators such as GroupBy, Join, and Aggregate. In this article, we will explore how to use these operators with examples. GroupBy groups collection elements by a specified property. You can then run queries on groups to extract statistical insights.
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