Flatbread:Python库,在Pandas中扩展了数据透视表。 轻松将总计小计和百分比添加到表中-源码

上传者: 42168830 | 上传时间: 2021-04-26 17:36:41 | 文件大小: 80KB | 文件类型: ZIP
大饼 关于 Flatbread是一个小型库,它扩展了pandas中的数据透视表功能。 可使用pita访问器通过DataFrame访问Flatbread。 该库包含使您能够轻松将合计/小计添加到数据透视表的一个或多个轴/级别的功能。 此外,大面包可以从数据透视表的每个轴/级别的总计/小计中计算百分比。 您可以将表中的现有值转换为百分比,但也可以将百分比整齐地添加到数据旁边。 如果不存在所需的(小计)总计,则面包将自动添加它们以执行计算。 默认情况下,保留(小计)总计,但您也可以删除它们。 该库还包含一些在matplotlib之上构建的功能,用于绘制数据。 姓名 最初,我计划将此库称为pita-透视表的缩写。 但是由于这个名字已经在pypi.org上使用,因此选择就落在了面包上。 安装 安装: pip install flatbread 数据透视表 让我们创建一个df进行测试: from

文件下载

资源详情

[{"title":"( 40 个子文件 80KB ) Flatbread:Python库,在Pandas中扩展了数据透视表。 轻松将总计小计和百分比添加到表中-源码","children":[{"title":"flatbread-master","children":[{"title":"setup.py <span style='color:#111;'> 1.59KB </span>","children":null,"spread":false},{"title":".gitignore <span style='color:#111;'> 95B </span>","children":null,"spread":false},{"title":"MANIFEST.in <span style='color:#111;'> 40B </span>","children":null,"spread":false},{"title":"flatbread","children":[{"title":"levels.py <span style='color:#111;'> 2.65KB </span>","children":null,"spread":false},{"title":"__init__.py <span style='color:#111;'> 931B </span>","children":null,"spread":false},{"title":"build","children":[{"title":"__init__.py <span style='color:#111;'> 0B </span>","children":null,"spread":false},{"title":"columns.py <span style='color:#111;'> 1.80KB </span>","children":null,"spread":false},{"title":"test.py <span style='color:#111;'> 2.93KB </span>","children":null,"spread":false},{"title":"drop.py <span style='color:#111;'> 630B </span>","children":null,"spread":false},{"title":"load.py <span style='color:#111;'> 834B </span>","children":null,"spread":false},{"title":"rows.py <span style='color:#111;'> 1.61KB </span>","children":null,"spread":false}],"spread":true},{"title":"aggregate","children":[{"title":"totals.py <span style='color:#111;'> 7.84KB </span>","children":null,"spread":false},{"title":"__init__.py <span style='color:#111;'> 208B </span>","children":null,"spread":false},{"title":"percentages.py <span style='color:#111;'> 8.77KB </span>","children":null,"spread":false}],"spread":true},{"title":"utils","children":[{"title":"sanity.py <span style='color:#111;'> 3.25KB </span>","children":null,"spread":false},{"title":"__init__.py <span style='color:#111;'> 208B </span>","children":null,"spread":false},{"title":"log.py <span style='color:#111;'> 1.42KB </span>","children":null,"spread":false},{"title":"readout.py <span style='color:#111;'> 2.67KB </span>","children":null,"spread":false}],"spread":true},{"title":"pivot.py <span style='color:#111;'> 8.39KB </span>","children":null,"spread":false},{"title":"config.py <span style='color:#111;'> 4.54KB </span>","children":null,"spread":false},{"title":"config.defaults.json <span style='color:#111;'> 1.51KB </span>","children":null,"spread":false},{"title":"axes.py <span style='color:#111;'> 5.01KB </span>","children":null,"spread":false},{"title":"plot","children":[{"title":"__init__.py <span style='color:#111;'> 0B </span>","children":null,"spread":false},{"title":"trendline.py <span style='color:#111;'> 23.04KB </span>","children":null,"spread":false}],"spread":false},{"title":"format","children":[{"title":"style.py <span style='color:#111;'> 4.51KB </span>","children":null,"spread":false},{"title":"__init__.py <span style='color:#111;'> 211B </span>","children":null,"spread":false}],"spread":false}],"spread":false},{"title":"static","children":[{"title":"noun_pita_3216932.svg <span style='color:#111;'> 4.47KB </span>","children":null,"spread":false},{"title":"2020-12-22.Date_of_Application.line.abs.svg <span style='color:#111;'> 54.01KB </span>","children":null,"spread":false},{"title":"template.svg <span style='color:#111;'> 239B </span>","children":null,"spread":false},{"title":"pita_table_example_001.svg <span style='color:#111;'> 15.92KB </span>","children":null,"spread":false},{"title":"2020-12-22.Date_Processed.line.cum.svg <span style='color:#111;'> 108.35KB </span>","children":null,"spread":false}],"spread":true},{"title":"LICENSE.txt <span style='color:#111;'> 34.33KB </span>","children":null,"spread":false},{"title":"README.md <span style='color:#111;'> 14.58KB </span>","children":null,"spread":false},{"title":"tests","children":[{"title":"test_levels.py <span style='color:#111;'> 2.25KB </span>","children":null,"spread":false},{"title":"__init__.py <span style='color:#111;'> 0B </span>","children":null,"spread":false},{"title":"aggregate","children":[{"title":"__init__.py <span style='color:#111;'> 0B </span>","children":null,"spread":false},{"title":"test_totals.py <span style='color:#111;'> 5.35KB </span>","children":null,"spread":false},{"title":"test_percentages.py <span style='color:#111;'> 1.64KB </span>","children":null,"spread":false}],"spread":true},{"title":"test_axes.py <span style='color:#111;'> 4.01KB </span>","children":null,"spread":false}],"spread":true},{"title":"environment.yml <span style='color:#111;'> 250B </span>","children":null,"spread":false}],"spread":true}],"spread":true}]

评论信息

免责申明

【只为小站】的资源来自网友分享,仅供学习研究,请务必在下载后24小时内给予删除,不得用于其他任何用途,否则后果自负。基于互联网的特殊性,【只为小站】 无法对用户传输的作品、信息、内容的权属或合法性、合规性、真实性、科学性、完整权、有效性等进行实质审查;无论 【只为小站】 经营者是否已进行审查,用户均应自行承担因其传输的作品、信息、内容而可能或已经产生的侵权或权属纠纷等法律责任。
本站所有资源不代表本站的观点或立场,基于网友分享,根据中国法律《信息网络传播权保护条例》第二十二条之规定,若资源存在侵权或相关问题请联系本站客服人员,zhiweidada#qq.com,请把#换成@,本站将给予最大的支持与配合,做到及时反馈和处理。关于更多版权及免责申明参见 版权及免责申明