<?xml version="1.0" encoding="utf-8" ?><rss version="2.0"><channel><title><![CDATA[ofoliao的博客]]></title><description><![CDATA[]]></description><link>https://blog.youkuaiyun.com/ofoliao</link><language>zh-cn</language><generator>https://blog.youkuaiyun.com/</generator><copyright><![CDATA[Copyright &copy; ofoliao]]></copyright><item><title><![CDATA[R语言read.csv万能读取各种文件编码的方式]]></title><link>https://blog.youkuaiyun.com/ofoliao/article/details/129992213</link><guid>https://blog.youkuaiyun.com/ofoliao/article/details/129992213</guid><author>ofoliao</author><pubDate>Thu, 06 Apr 2023 16:15:46 +0800</pubDate><description><![CDATA[使用R语言读取csv文件的时候，由于文件的字符集不同，有时往往会有乱码。最近整理一个读取csv的方式，足以应付99%的情况。]]></description><category></category></item><item><title><![CDATA[R语言sort,order和rank的区别和联系]]></title><link>https://blog.youkuaiyun.com/ofoliao/article/details/129991741</link><guid>https://blog.youkuaiyun.com/ofoliao/article/details/129991741</guid><author>ofoliao</author><pubDate>Thu, 06 Apr 2023 16:02:24 +0800</pubDate><description><![CDATA[排的是原vectro的哪个值（下标）？（是vector哪个index？]]></description><category></category></item><item><title><![CDATA[4种差异检验]]></title><link>https://blog.youkuaiyun.com/ofoliao/article/details/129991539</link><guid>https://blog.youkuaiyun.com/ofoliao/article/details/129991539</guid><author>ofoliao</author><pubDate>Thu, 06 Apr 2023 15:54:14 +0800</pubDate><description><![CDATA[【代码】4种差异检验。]]></description><category></category></item><item><title><![CDATA[shiny server重启app]]></title><link>https://blog.youkuaiyun.com/ofoliao/article/details/126625131</link><guid>https://blog.youkuaiyun.com/ofoliao/article/details/126625131</guid><author>ofoliao</author><pubDate>Wed, 31 Aug 2022 15:43:20 +0800</pubDate><description><![CDATA[shiny server重新启动更新代码后的app]]></description><category></category></item><item><title><![CDATA[R语言中文字符串排序]]></title><link>https://blog.youkuaiyun.com/ofoliao/article/details/126489752</link><guid>https://blog.youkuaiyun.com/ofoliao/article/details/126489752</guid><author>ofoliao</author><pubDate>Tue, 23 Aug 2022 17:46:27 +0800</pubDate><description><![CDATA[设置locale，解决中文字符串排序在各个系统中不一致问题]]></description><category></category></item><item><title><![CDATA[R Shiny App文件默认加载顺序]]></title><link>https://blog.youkuaiyun.com/ofoliao/article/details/125934251</link><guid>https://blog.youkuaiyun.com/ofoliao/article/details/125934251</guid><author>ofoliao</author><pubDate>Fri, 22 Jul 2022 17:48:13 +0800</pubDate><description><![CDATA[描述R Shiny App目录下文件的默认加载顺序]]></description><category></category></item><item><title><![CDATA[pycharm PyQt5 designer pyuic pyrcc 设置]]></title><link>https://blog.youkuaiyun.com/ofoliao/article/details/121998553</link><guid>https://blog.youkuaiyun.com/ofoliao/article/details/121998553</guid><author>ofoliao</author><pubDate>Tue, 15 Feb 2022 17:25:51 +0800</pubDate><description><![CDATA[PyQt5Designer欢迎使用Markdown编辑器新的改变功能快捷键合理的创建标题，有助于目录的生成如何改变文本的样式插入链接与图片如何插入一段漂亮的代码片生成一个适合你的列表创建一个表格设定内容居中、居左、居右SmartyPants创建一个自定义列表如何创建一个注脚注释也是必不可少的KaTeX数学公式新的甘特图功能，丰富你的文章UML 图表FLowchart流程图导出与导入导出导入

python3.9
pycharm

pip install PyQt5
pip install PyQt5-too]]></description><category></category></item><item><title><![CDATA[R语言data.frame label的设置]]></title><link>https://blog.youkuaiyun.com/ofoliao/article/details/120902942</link><guid>https://blog.youkuaiyun.com/ofoliao/article/details/120902942</guid><author>ofoliao</author><pubDate>Fri, 22 Oct 2021 12:01:29 +0800</pubDate><description><![CDATA[假设dataframe为
df &lt;- data.frame(age = c(20, 30, 40), 
                   sex = factor(c(1, 2, 1), labels = c("男", "女"))
                   )

使用attr设定label属性
attr(df[["age"]], "label") &lt;- "年龄"
attr(df[["sex"]], "label") &lt;- "性别"

也可以使用attr查看label att]]></description><category></category></item><item><title><![CDATA[R语言data.frame的Encoding（中文乱码解决方式）]]></title><link>https://blog.youkuaiyun.com/ofoliao/article/details/120847560</link><guid>https://blog.youkuaiyun.com/ofoliao/article/details/120847560</guid><author>ofoliao</author><pubDate>Tue, 19 Oct 2021 15:48:48 +0800</pubDate><description><![CDATA[查看data.frame的列的字符编码方式
使用Encoding函数查看：
df %&gt;% 
    select_if(is.character) %&gt;%  # 选择是character的列
    map(Encoding) %&gt;%            # 显示该列的encoding
    as.data.frame                # list整理成表

更进一步，采用stringi package的stri_enc_mark函数获取encoding方式
librar]]></description><category></category></item><item><title><![CDATA[windows获得文件hash值的方式]]></title><link>https://blog.youkuaiyun.com/ofoliao/article/details/117656859</link><guid>https://blog.youkuaiyun.com/ofoliao/article/details/117656859</guid><author>ofoliao</author><pubDate>Mon, 07 Jun 2021 12:40:24 +0800</pubDate><description><![CDATA[powershell
get-filehash file.csv -algorithm SHA512 | format-list

Algorithm: SHA1 | SHA256 | SHA384 | SHA512 | MACTripleDES | MD5 | RIPEMD160
cmd
certutil -hashfile  file.csv SHA512

Algorithm:  MD2 MD4 MD5 SHA1 SHA256 SHA384 SHA512

]]></description><category></category></item><item><title><![CDATA[R语言字符串日期转换和本地设置]]></title><link>https://blog.youkuaiyun.com/ofoliao/article/details/116480677</link><guid>https://blog.youkuaiyun.com/ofoliao/article/details/116480677</guid><author>ofoliao</author><pubDate>Fri, 07 May 2021 09:22:48 +0800</pubDate><description><![CDATA[使用R语言的as.Date进行日期转换时，需要注意本地设置(locale setting)，否则有可能转换失败。
&gt; as.Date("01jul2020", format = "%d%b%Y")
[1] NA

&gt; lc &lt;- Sys.getlocale("LC_TIME")   # get the LC_TIME and save it
&gt; Sys.setlocale("LC_TIME", "C")    # set to C lang default
[1] "C"
&gt; ]]></description><category></category></item><item><title><![CDATA[R语言服务器环境安装全局package]]></title><link>https://blog.youkuaiyun.com/ofoliao/article/details/116448431</link><guid>https://blog.youkuaiyun.com/ofoliao/article/details/116448431</guid><author>ofoliao</author><pubDate>Thu, 06 May 2021 10:55:28 +0800</pubDate><description><![CDATA[一般个人电脑上安装R的package使用命令install.packages()就可以了，默认安装在个人的home目录下（Windows/Linux）。有时需要在服务器环境安装每个登录账号都能使用的package，该如何做呢？
1. 查看当前的package查找路径
# Search Paths for Packages
&gt; .libPaths()
[1] "C:/Users/myhome/Documents/R/win-library/4.0" "C:/Program Files/R/R-4.0.3]]></description><category></category></item><item><title><![CDATA[R语言命令行执行代码的3种方式（传递参数和环境变量）]]></title><link>https://blog.youkuaiyun.com/ofoliao/article/details/115869383</link><guid>https://blog.youkuaiyun.com/ofoliao/article/details/115869383</guid><author>ofoliao</author><pubDate>Wed, 21 Apr 2021 09:50:31 +0800</pubDate><description><![CDATA[大部分情况在IDE环境中运行R程序，但有时也需要在shell中运行，想其他语言的脚本一样。在shell中如何运行R语言的代码呢？

为了简化使用，把R/Rscript的可执行路径加入path环境变量。（bash，windows cmd）

使用R
首先看看R的help
c:\R&gt; R --arch x64 --help
Usage: Rterm [options] [&lt; infile] [&gt; outfile] [EnvVars]

Start R, a system for statist]]></description><category></category></item><item><title><![CDATA[AWS Redhat Enterprise Server安装桌面步骤]]></title><link>https://blog.youkuaiyun.com/ofoliao/article/details/114627819</link><guid>https://blog.youkuaiyun.com/ofoliao/article/details/114627819</guid><author>ofoliao</author><pubDate>Wed, 10 Mar 2021 11:12:53 +0800</pubDate><description><![CDATA[安装EPEL

EPEL(http://fedoraproject.org/wiki/EPEL) 的全称叫 Extra Packages for Enterprise Linux 。EPEL是由 Fedora 社区打造，为 RHEL 及衍生发行版如 CentOS、Scientific Linux 等提供高质量软件包的项目。装上了 EPEL之后，就相当于添加了一个第三方源。和rpmfusion.org的相比较的话，rpmfusion 主要为桌面发行版提供大量rpm包，而EPEL则为服务器版本提供大量的rpm包]]></description><category></category></item><item><title><![CDATA[Bioconductor设置清华大学的镜像]]></title><link>https://blog.youkuaiyun.com/ofoliao/article/details/114623660</link><guid>https://blog.youkuaiyun.com/ofoliao/article/details/114623660</guid><author>ofoliao</author><pubDate>Wed, 10 Mar 2021 08:34:42 +0800</pubDate><description><![CDATA[在Home目录下增加/修改.Rprofile文件，在文件最后加上镜像设置：
options(BioC_mirror="https://mirrors.tuna.tsinghua.edu.cn/bioconductor")


再次打开RhuoRStudio即可生效。

]]></description><category></category></item><item><title><![CDATA[Shiny server的app目录映射规则]]></title><link>https://blog.youkuaiyun.com/ofoliao/article/details/107349459</link><guid>https://blog.youkuaiyun.com/ofoliao/article/details/107349459</guid><author>ofoliao</author><pubDate>Tue, 14 Jul 2020 22:44:42 +0800</pubDate><description><![CDATA[shiny sever配置成site host模式之后，在site根目录下可以deploy多个app，每个app一个目录。
+---/srv/shiny-server
|   +---shinyApp1
|       +---server.R
|       +---ui.R
|   +---shinyApp2
|       +---app.R
|       +---www
|           +--- a.html
|   +---assets
|       +---style.css
|  ]]></description><category></category></item><item><title><![CDATA[R Shiny App增加对百度统计的支持]]></title><link>https://blog.youkuaiyun.com/ofoliao/article/details/107142094</link><guid>https://blog.youkuaiyun.com/ofoliao/article/details/107142094</guid><author>ofoliao</author><pubDate>Sun, 05 Jul 2020 17:51:27 +0800</pubDate><description><![CDATA[方法很简单，在百度统计的代码存放在一个js文件中，比如baidu_stat.js,
var _hmt = _hmt || [];
(function() {
  var hm = document.createElement("script");
  hm.src = "https://hm.baidu.com/hm.js?XXXXXXXXXXXXXXXXX";
  var s = document.getElementsByTagName("script")[0]; 
  s.parentNode.ins]]></description><category></category></item><item><title><![CDATA[缺失值的插值处理]]></title><link>https://blog.youkuaiyun.com/ofoliao/article/details/106934132</link><guid>https://blog.youkuaiyun.com/ofoliao/article/details/106934132</guid><author>ofoliao</author><pubDate>Tue, 23 Jun 2020 23:23:06 +0800</pubDate><description><![CDATA[缺失值根据情况可以删除对应的行或者列，但是在需要尽量保持原始数据的情况下，可以使用插值的方式进行处理。
使用mean/median/mode数进行插值
library(Hmisc)
impute(vector_data, mean)
impute(vector_data, median)
impute(vector_data, 100)  # 直接赋值
# 不使用函数
vector_data[is.na(vector_data)] &lt;- mean(vector_data, na.rm = T)  

]]></description><category></category></item><item><title><![CDATA[多重检验的p值校正：FWER和FDR]]></title><link>https://blog.youkuaiyun.com/ofoliao/article/details/106920870</link><guid>https://blog.youkuaiyun.com/ofoliao/article/details/106920870</guid><author>ofoliao</author><pubDate>Tue, 23 Jun 2020 22:50:15 +0800</pubDate><description><![CDATA[先回忆一下假设检验的来两类错误(参考：深入理解假设检验的两类错误和功效)：
对于多重检验来说，假设做了m次test，V是假阳性的次数，S是真阳性的次数，R是V+S。 列表如下：




H0H_0H0​    Do not reject H0H_0H0​ 
Reject H0H_0H0​
Total




TRUE
U      V 
m0m_0m0​


FALSE T
S
m−m0m-m_0m−m0​


Total
m-R
R m


FWER: Family-wise error rate
FWE]]></description><category></category></item><item><title><![CDATA[R语言如何删除数据集中指定的行或列？]]></title><link>https://blog.youkuaiyun.com/ofoliao/article/details/106593035</link><guid>https://blog.youkuaiyun.com/ofoliao/article/details/106593035</guid><author>ofoliao</author><pubDate>Sat, 06 Jun 2020 21:50:04 +0800</pubDate><description><![CDATA[按索引删除
只是最基本的删除方式，比如：

删除第1到10行：df[-c(1:10),]
删除第5到10列：df[,-c(5:10)]

按名字删除
无论行列，可以找出对应索引或构造相同长度TRUE/FALSE的向量，把不需要的行/列删除

index

-which(colnames(df) %in% c("a","b"))
-grep("a|b",colnames(df)


T/F vector

!colnames(df) %in% c("z","u")
!grepl("a|b", colnames]]></description><category></category></item></channel></rss>