{ "info": { "author": "Max Harlow", "author_email": "maxharlow@gmail.com", "bugtrack_url": null, "classifiers": [ "Development Status :: 5 - Production/Stable", "Environment :: Console", "Intended Audience :: Developers", "Intended Audience :: End Users/Desktop", "Intended Audience :: Science/Research", "License :: OSI Approved :: Apache Software License", "Natural Language :: English", "Operating System :: OS Independent", "Programming Language :: Python :: 2.7", "Programming Language :: Python :: 3.6", "Topic :: Scientific/Engineering :: Information Analysis", "Topic :: Utilities" ], "description": "CSV Pivot\n=========\n\nPivot tables for CSV files in the terminal.\n\nTested on Python 3.6 and 2.7.\n\n\nInstalling\n----------\n\n pip install csvpivot\n\n\nUsage\n-----\n\nSay you have a CSV file such as:\n\n name,country,gender,salary\n Oliver,UK,M,10000\n Jack,UK,M,21000\n Emily,UK,F,32000\n Harry,UK,M,43000\n Adam,France,M,54000\n Paul,France,M,65000\n Louise,France,F,76000\n Alice,France,F,87000\n Emma,Germany,F,98000\n\nWe could then find the average salary in each country:\n\n $ csvpivot test.csv --rows country --values 'mean(salary)'\n\n country,mean(salary)\n France,70500\n Germany,98000\n UK,26500\n\nIt would be useful to find out the maximum and minimum values too though:\n\n $ csvpivot test.csv --rows country --values 'mean(salary)' 'min(salary)' 'max(salary)'\n\n country,mean(salary),min(salary),max(salary)\n France,70500,54000,87000\n Germany,98000,98000,98000\n UK,26500,10000,43000\n\nAs well as `mean`, `min`, and `max`, CSV Pivot also supports `median`, `sum`, `stddev`, `count`, `countuniq`, `concat`, and `concatuniq`. All require numerical values apart from the last two. If numbers contain commas they are interpreted as thousands separators and removed.\n\nColumns are also supported. 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