使用qsv从终端配置文件和清理大型CSV数据集

Inspect, profile, normalize, and diff large CSV files before loading them into downstream analytics or automation workflows.

Prerequisites

qsv binary and CSV datasets

Use the upstream install or setup path that matches your environment:

Requirements and caveats from upstream:

| py✨<br>📇🔣 | Create a new computed column or filter rows by evaluating a Python expression on every row of a CSV file. Python's [f-strings](https://www.freecodecamp.org/news/python-f-strings-tutori...
🔣: requires UTF-8 encoded input.

Basic usage or getting-started notes:

| describegpt<br>📇🗃️🤖🌐🪄📚⛩️ | <a name="describegpt_deeplink"></a>Infer a "neuro-symbolic" Data Dictionary, De...
| luau✨<br>📇🌐🔣📚 | <a name="luau_deeplink"></a>Create multiple new computed columns, filter rows, compute aggregations and build complex...
| moarstats<br>📇🏎️ | Add up to an additional 55 statistical measures, including extended outlier, robust & bivariate statistics to an existing stats CSV file. ([example](docs/moarstats/NYC_31...
Source: https://github.com/1991513ccie-png/skills
Extracted from upstream docs: https://raw.githubusercontent.com/dathere/qsv/HEAD/README.md