627.Given a table salary, such as the one below, that has m=male and f=female values. Swap all f and m values (i.e., change all f values to m and vice versa) with a single update query and no intermediate temp table. For example: | id | name | sex |…

select sname,score,case when score>=20 and score<30 then 20when score>=30 and score<40 then 30when score<=40 and score<50 then 40else 50end as score_new from teacher…

主要是对项目中用过的 oracle 函数进行总结,并做出目录,方便后续项目是快速查找,提高效率. 01.Round (数值的四舍五入) 描述:传回一个数值,该数值是按照指定的小数位元数进行四舍五入运算的结果. SELECT Round(Number,[Decimal_Places])FROM Dual; param:Number:欲处理的数值Decimal_Places:四舍五入,小数取几位(预设为0)Sample: )FROM Dual; output:123.5 )FROM Dual; ou…

In this blog post I share some lesser-known (at least I believe they are) tricks that use mainly functions from dplyr. Removing unneeded columns Did you know that you can use - in front of a column name to remove it from a data frame? mtcars %>% sele…

转载: https://github.com/twbattaglia/RNAseq-workflow Introduction RNAseq is becoming the one of the most prominent methods for measuring celluar responses. Not only does RNAseq have the ability to analyze differences in gene expression between samples,…

好多同学把统计和数据清洗搞混,直接把原始数据发给我,做个统计吧,这个时候其实很大的工作量是在数据清洗和处理上,如果数据很杂乱,清洗起来是很费工夫的,反而清洗好的数据做统计分析常常就是一行代码的事情. Data scientists only spend 20% of their time creating insights, the rest wrangling data. 想想今天就给大家写一篇数据处理的常用函数介绍吧.全是自己的一丢丢经验,肯定不会是最优的,仅仅是给个参考,因为在R中同一个目…

本文示例代码及文件已上传至我的Github仓库https://github.com/CNFeffery/DataScienceStudyNotes 1 简介 pandas发展了如此多年,所包含的功能已经覆盖了大部分数据清洗.分析场景,但仍然有着相当一部分的应用场景pandas中尚存空白亦或是现阶段的操作方式不够简洁方便. 今天我要给大家介绍的Python库pyjanitor就内置了诸多功能方法,可以在兼容pandas中数据框等数据结构的同时为pandas补充更多功能.它是对R中著名的数据清洗包j…