用简单的文本处理办法优化咱们的读书体验
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><strong style="color: blue;"><span style="color: black;">前言</span></strong></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;"> 延续之前的<span style="color: black;">用R语言读琅琊榜小说</span>，继续讲一下利用R语言做<span style="color: black;">有些</span>简单的文本处理、分词的事情。其实<span style="color: black;">便是</span>继续讲一下用R语言读书的事情啦，讲讲怎么用它里面简单的文本处理<span style="color: black;">办法</span>，来优化<span style="color: black;">咱们</span>的读书体验，<span style="color: black;">倘若</span>读邮件和读代码<span style="color: black;">亦</span>算阅读的话。。用的代码超级简单，不<span style="color: black;">触及</span>其他包</span></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><strong style="color: blue;"><span style="color: black;"><span style="color: black;">这儿</span>讲两个示例，结尾再来吐槽和总结。</span></strong></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;">1）R-Blogger订阅邮件拆分</span></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;">2） R代码库快速阅读<span style="color: black;">办法</span></span></p>
<h2 style="color: black; text-align: left; margin-bottom: 10px;"><span style="color: black;">1、R-Blogger订阅邮件拆分</span></h2>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;"> 这个案例用的文本数据来自于R-Blooger网站。<a style="color: black;"><span style="color: black;">R-Blogger</span></a>是一个专门收集和发布与R语言<span style="color: black;">关联</span><span style="color: black;">文案</span>的<span style="color: black;">地区</span>。它<span style="color: black;">供给</span>一个每日邮件订阅功能，会把今天好的<span style="color: black;">文案</span>，直接发到你邮箱去。本身网站是<span style="color: black;">不消</span>FQ就<span style="color: black;">能够</span>上的，<span style="color: black;">然则</span>订阅的确认邮件却<span style="color: black;">需求</span>FQ后<span style="color: black;">才可</span>上(基于google)</span></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;"> 我之前批量订阅了快半年吧，最<span style="color: black;">起始</span>的时候还<span style="color: black;">每日</span>都瞅瞅，<span style="color: black;">然则</span>它一封邮件信息量有些大，<span style="color: black;">况且</span>有些<span style="color: black;">文案</span>不太感兴趣，渐渐就兴趣转移，累计了一堆未读的在里面。</span></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;"><span style="color: black;">咱们</span><span style="color: black;">能够</span>利用outlook软件来批量<span style="color: black;">得到</span>这些邮件的文本。（outlook，选中所有R-Blogger邮件，另存为，<span style="color: black;">就可</span>把所有邮件存到一个txt文件里)</span></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><strong style="color: blue;"><span style="color: black;">接下来是代码示例。</span></strong></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;">源数据文本文件请在<span style="color: black;">这儿</span>下载：<span style="color: black;">http://vdisk.weibo.com/s/o_UNVWL3aJf</span></span></p><span style="color: black;"><span style="color: black;"><span style="color: black;">#</span><span style="color: black;">1</span></span><span style="color: black;">、读取数据</span><span style="color: black;"><span style="color: black;">r_blog<-readLines(</span></span><span style="color: black;">"F:/R/R-ReadBooks/R-blogger.txt"</span></span><span style="color: black;">)</span><span style="color: black;">r_blog[</span><span style="color: black;">20</span><span style="color: black;">:</span><span style="color: black;">30</span><span style="color: black;">]</span><span style="color: black;"><span style="color: black;"><span style="color: black;">#</span><span style="color: black;">2</span></span><span style="color: black;">、以</span><span style="color: black;">posted</span><span style="color: black;">为定位<span style="color: black;">要求</span>，分别提取出<span style="color: black;">文案</span>的时间、标题、作者等关系</span><span style="color: black;">#</span><span style="color: black;"><span style="color: black;">文案</span>发布时间</span><span style="color: black;"><span style="color: black;">sample(r_blog,</span><span style="color: black;">10</span><span style="color: black;">)</span><span style="color: black;"><span style="color: black;">#</span><span style="color: black;"><span style="color: black;">文案</span>标题</span><span style="color: black;"><span style="color: black;">sample(r_blog,</span><span style="color: black;">10</span><span style="color: black;">)</span><span style="color: black;"><span style="color: black;">#</span><span style="color: black;"><span style="color: black;">文案</span>作者</span><span style="color: black;"><span style="color: black;">sample(r_blog,</span><span style="color: black;">5</span><span style="color: black;">)</span><span style="color: black;"><span style="color: black;"><span style="color: black;">#</span><span style="color: black;">3</span></span><span style="color: black;">、<span style="color: black;">按照</span><span style="color: black;">以上</span>信息，按<span style="color: black;">文案</span>拆分长文本（</span><span style="color: black;">4.5</span><span style="color: black;">M</span><span style="color: black;">）</span><span style="color: black;"><span style="color: black;">#</span><span style="color: black;">4</span></span><span style="color: black;">、以</span><span style="color: black;">library</span><span style="color: black;">为<span style="color: black;">要求</span>，<span style="color: black;">瞧瞧</span><span style="color: black;">近期</span>流行什么库</span><span style="color: black;"><span style="color: black;">library_list<-strsplit(r_blog,</span><span style="color: black;">"\\(|\\)|\\,"</span><span style="color: black;">)</span><span style="color: black;">library_list<-sapply(library_list,function(e) e[</span><span style="color: black;">2</span><span style="color: black;">])</span><span style="color: black;">library_list<-gsub(</span><span style="color: black;">"\\p{P}"</span><span style="color: black;">,</span><span style="color: black;">""</span><span style="color: black;">,library_list,perl=TRUE)</span><span style="color: black;">
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;">a<-sort(table(library_list),decreasing = TRUE)</p>
</span><span style="color: black;"><span style="color: black;">#</span><span style="color: black;">最流行</span><span style="color: black;"><span style="color: black;">head(a,</span></span><span style="color: black;">20</span></span><span style="color: black;">)</span><span style="color: black;"><span style="color: black;"><span style="color: black;">#</span><span style="color: black;">5</span></span><span style="color: black;">、以</span><span style="color: black;">github+http</span><span style="color: black;">为<span style="color: black;">要求</span>，选出邮件里<span style="color: black;">触及</span>到的所有</span><span style="color: black;">github</span><span style="color: black;"><span style="color: black;">位置</span></span><span style="color: black;"><span style="color: black;">url_raw<-r_blog</span><span style="color: black;">url_list<-sapply(strsplit(url_raw,</span><span style="color: black;">"<|>"</span><span style="color: black;">),function(e) e[</span><span style="color: black;">2</span><span style="color: black;">])</span><span style="color: black;">
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;">url_list<-unique(url_list[!is.na(url_list)])</p>sample(grep(
</span><span style="color: black;">"github"</span><span style="color: black;">,url_list,value=TRUE),</span><span style="color: black;">10</span><span style="color: black;">)</span>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;">样图：</span></p>
<h3 style="color: black; text-align: left; margin-bottom: 10px;"><span style="color: black;">2、代码文本分析</span></h3>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;"><span style="color: black;">刚才</span><span style="color: black;">已然</span><span style="color: black;">说到</span>，R语言<span style="color: black;">能够</span>处理<span style="color: black;">有些</span>简单的文本。<span style="color: black;">那样</span><span style="color: black;">咱们</span>扩展一下来想，代码.R，<span style="color: black;">为何</span><span style="color: black;">不可</span><span style="color: black;">亦</span>被视为是<span style="color: black;">咱们</span>要处理的文本，按之前的<span style="color: black;">规律</span>，去扫一下里面的文本数据？</span></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;">尤其是在<span style="color: black;">大众</span>都说要多写代码，多看别人的代码，多<span style="color: black;">累积</span>代码功能块，但每次打开别人的代码，都对那成千上百的英文望而生畏，用程序去处理代码块，<span style="color: black;">是不是</span>能得出<span style="color: black;">有些</span>规律，从更加客观敏捷的<span style="color: black;">方向</span>，做<span style="color: black;">有些</span>统计和分析呢？</span></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;"> 源数据<span style="color: black;">源自</span>于这本书： 《<span style="color: black;">设备</span>学习：实用案例解析》</span></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;"> <img src="data:image/svg+xml,%3C%3Fxml version=1.0 encoding=UTF-8%3F%3E%3Csvg width=1px height=1px viewBox=0 0 1 1 version=1.1 xmlns=http://www.w3.org/2000/svg xmlns:xlink=http://www.w3.org/1999/xlink%3E%3Ctitle%3E%3C/title%3E%3Cg stroke=none stroke-width=1 fill=none fill-rule=evenodd fill-opacity=0%3E%3Cg transform=translate(-249.000000, -126.000000) fill=%23FFFFFF%3E%3Crect x=249 y=126 width=1 height=1%3E%3C/rect%3E%3C/g%3E%3C/g%3E%3C/svg%3E" style="width: 50%; margin-bottom: 20px;"> 该书代码的github<span style="color: black;">位置</span>如下，可直接下载： <span style="color: black;">https://github.com/johnmyleswhite/ML_for_Hackers</span></span></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;">请看代码示例。</span></p><span style="color: black;"><span style="color: black;"><span style="color: black;">#</span><span style="color: black;">1.</span></span><span style="color: black;">读入原始数据，确实<span style="color: black;">能够</span>如文本<span style="color: black;">同样</span>一行行读入，<span style="color: black;">这儿</span>需要遍历的<span style="color: black;">办法</span>读入数据，<span style="color: black;">由于</span>文件夹里不止一个</span><span style="color: black;">R</span><span style="color: black;">文件</span><span style="color: black;"><span style="color: black;">fileslist<-</span>list</span></span><span style="color: black;">.files(</span><span style="color: black;">"F:/Code/ML_for_Hackers-master/"</span><span style="color: black;">,recursive = TRUE,pattern=</span><span style="color: black;">"\\.R$"</span><span style="color: black;">,full.names = TRUE)</span><span style="color: black;">code_detail<-NULL</span><span style="color: black;"><span style="color: black;">for</span><span style="color: black;"> (i in </span><span style="color: black;">1</span><span style="color: black;">:length(fileslist))</span></span><span style="color: black;">{</span><span style="color: black;">
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"> code_detail<-c(code_detail,readLines(fileslist))</p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;">}</p>
</span><span style="color: black;"><span style="color: black;"><span style="color: black;">#</span><span style="color: black;">2</span></span><span style="color: black;">、<span style="color: black;">瞧瞧</span>用了什么</span><span style="color: black;">R</span><span style="color: black;">包</span><span style="color: black;"><span style="color: black;">library_list<-strsplit(code_detail,</span><span style="color: black;">"\\(|\\)|\\,"</span><span style="color: black;">)</span><span style="color: black;">library_list<-sapply(library_list,function(e) e[</span><span style="color: black;">2</span><span style="color: black;">])</span><span style="color: black;">library_list<-gsub(</span><span style="color: black;">"\\p{P}"</span><span style="color: black;">,</span><span style="color: black;">""</span><span style="color: black;">,library_list,perl=TRUE)</span><span style="color: black;">
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;">a<-sort(table(library_list),decreasing = TRUE)</p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;">a</p>
</span><span style="color: black;"><span style="color: black;"><span style="color: black;">#</span><span style="color: black;">3</span></span><span style="color: black;">、<span style="color: black;">瞧瞧</span>注释占总代码行的多少</span><span style="color: black;"><span style="color: black;">zhushi<-code_detail</span><span style="color: black;">
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;">length(zhushi)/length(code_detail)</p>
</span><span style="color: black;"><span style="color: black;">#</span><span style="color: black;"><span style="color: black;">这儿</span>约占</span><span style="color: black;">30</span><span style="color: black;">%</span><span style="color: black;"><span style="color: black;">#</span><span style="color: black;">4</span></span><span style="color: black;">、<span style="color: black;">瞧瞧</span>自定义了什么函数</span><span style="color: black;"><span style="color: black;">function_list<-code_detail</span><span style="color: black;">function_list<-sapply(strsplit(function_list,</span><span style="color: black;">" "</span><span style="color: black;">),function(e) e[</span><span style="color: black;">1</span><span style="color: black;">])</span><span style="color: black;">sample(function_list,</span><span style="color: black;">30</span><span style="color: black;">)</span>
<h2 style="color: black; text-align: left; margin-bottom: 10px;"><span style="color: black;">3、总结</span></h2>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;"> <span style="color: black;">那样</span><span style="color: black;">此刻</span>来总结一下三个样例的特点。</span></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;"><img src="data:image/svg+xml,%3C%3Fxml version=1.0 encoding=UTF-8%3F%3E%3Csvg width=1px height=1px viewBox=0 0 1 1 version=1.1 xmlns=http://www.w3.org/2000/svg xmlns:xlink=http://www.w3.org/1999/xlink%3E%3Ctitle%3E%3C/title%3E%3Cg stroke=none stroke-width=1 fill=none fill-rule=evenodd fill-opacity=0%3E%3Cg transform=translate(-249.000000, -126.000000) fill=%23FFFFFF%3E%3Crect x=249 y=126 width=1 height=1%3E%3C/rect%3E%3C/g%3E%3C/g%3E%3C/svg%3E" style="width: 50%; margin-bottom: 20px;"> <span style="color: black;">倘若</span>用一个数据分析的框架去套的话，<span style="color: black;">她们</span>都符合<span style="color: black;">需要</span>分析、获取数据、处理数据、分析再整合数据等等一套基本流程。其实这个<span style="color: black;">亦</span>是<span style="color: black;">咱们</span><span style="color: black;">平常</span>做分析<span style="color: black;">亦</span>好，搞报表<span style="color: black;">亦</span>好都要遵循的一套定理。</span></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;"><span style="color: black;">况且</span>用这几类文本数据入门R语言的数据处理与分析流程，<span style="color: black;">亦</span>能很好地保持住学习者的兴趣。</span></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;"> 当年我学R时最大的痛苦<span style="color: black;">便是</span>，在courseraJHU的R课里，老师总是<span style="color: black;">爱好</span>用<span style="color: black;">各样</span>社会统计数据，天气数据，生物数据给<span style="color: black;">咱们</span>举例子。<span style="color: black;">然则</span>这些数据一来专业性太强，二来多为欧美社会的数据，用起这些数据时总觉得非常痛苦。</span></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;"><span style="color: black;">因此</span>当我之前弄那个R语言看琅琊榜小说时，我<span style="color: black;">发掘</span>这些数据才是<span style="color: black;">咱们</span><span style="color: black;">平常</span>都感兴趣的，学来确实<span style="color: black;">能够</span>用的，<span style="color: black;">每一个</span>人都有自己的一套分析技法的，你<span style="color: black;">能够</span>很轻易得去设计一套数据分析流程，<span style="color: black;">得到</span>一个推论和结论的数据。<strong style="color: blue;"><span style="color: black;">况且</span>这些<span style="color: black;">办法</span>用得好，<span style="color: black;">咱们</span>的阅读体验、读书体验会有很高的<span style="color: black;">加强</span>，且加速了知识<span style="color: black;">累积</span>归类的过程。</strong></span></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;"><span style="color: black;">咱们</span><span style="color: black;">周边</span>都充斥着数据，<span style="color: black;">为何</span><span style="color: black;">不可</span>把文本<span style="color: black;">亦</span>看成是另类的一种数据呢？一个合格的想往处理数据方向走的人，<span style="color: black;">最少</span>要在生活里随时随地能<span style="color: black;">发掘</span>文字<span style="color: black;">背面</span>的奥秘与数字吧？</span></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;"><span style="color: black;">另一</span>，需要指出的是：</span></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;"><strong style="color: blue;"><span style="color: black;">1</span></strong><strong style="color: blue;"><span style="color: black;">）数据本身有自己的特性，以及处理目的，联系业务、<span style="color: black;">认识</span>业务，绝对不是口头白说。</span></strong></span></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;"> 像读琅琊榜小说，<span style="color: black;">咱们</span>要关注的是以【<span style="color: black;">名人</span>】来串联【情节】，以及<span style="color: black;">名人</span>与<span style="color: black;">名人</span>的关系，<span style="color: black;">因此</span>如<strong style="color: blue;">text</strong><span style="color: black;">这般</span>的多<span style="color: black;">要求</span>筛选就比比皆是,而<span style="color: black;">针对</span>R-blogger，<span style="color: black;">由于</span>这个数据来自于多个作者，且有时间跨度，<span style="color: black;">怎样</span>有效地选出这些作者，<span style="color: black;">而后</span><span style="color: black;">怎样</span>去决定<span style="color: black;">那些</span>内容对<span style="color: black;">咱们</span>有用，在时间变换下人们关注趋势有什么变化，这些处理就更加重要了。<span style="color: black;">乃至</span>要设计<span style="color: black;">有些</span>分词、文本挖掘、频率统计的内容。</span></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;"> 而<span style="color: black;">针对</span>代码的甄选，<span style="color: black;">咱们</span>要<span style="color: black;">熟悉</span><span style="color: black;">把握</span>正则表达式，能够在多个{},()中选出<span style="color: black;">有些</span>共通的东西，还要把<span style="color: black;">哪些</span>乱命名的变量通通筛选出来，抛离掉，只留下函数啊、技术的关键应用点。<span style="color: black;">这儿</span><span style="color: black;">更加多</span>考察的是取数的能力，<span style="color: black;">由于</span>它不像前两个案例的文本<span style="color: black;">那样</span>规整易取。</span></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;">仅仅只是<span style="color: black;">这儿</span>指的三个简单的案例，<span style="color: black;">她们</span>的处理<span style="color: black;">办法</span>就大相径庭，<span style="color: black;">况且</span><span style="color: black;">倘若</span>弄小说不懂<span style="color: black;">名人</span>带动情节，看订阅<span style="color: black;">无</span>自己的看邮件习惯，<span style="color: black;">乃至</span>不懂代码的话，<span style="color: black;">亦</span>没办法对上面的数据做进一步的处理。</span></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;"> <span style="color: black;">因此</span><span style="color: black;">熟练</span>业务，<span style="color: black;">不仅</span>是<span style="color: black;">熟练</span>业务数据的特点，<span style="color: black;">亦</span>要<span style="color: black;">熟练</span>业务的<span style="color: black;">需要</span>，自己能找出<span style="color: black;">有些</span><span style="color: black;">能够</span>深入的点来继续挖掘</span></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;"><strong style="color: blue;"><span style="color: black;">2</span></strong><strong style="color: blue;"><span style="color: black;">）从趋势<span style="color: black;">来讲</span>，人人都会编程会<span style="color: black;">作为</span>更广范围内的一个硬<span style="color: black;">需求</span></span></strong></span></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;"><span style="color: black;">这儿</span>有<span style="color: black;">有些</span>畅想：</span></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;">从文本处理的<span style="color: black;">方向</span>，当<span style="color: black;">咱们</span>要背单词时，<span style="color: black;">为何</span><span style="color: black;">不可</span>找一部美剧或电影的字幕，导入R里面，<span style="color: black;">而后</span>匹配一下雅思托福词汇，<span style="color: black;">或</span>单词本，把要背的单词所在的段落<span style="color: black;">所有</span>选出来阅读？（灵感<span style="color: black;">源自</span>：书《单词社交网络》）</span></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;"><span style="color: black;">而后</span>以前<span style="color: black;">哪些</span>编写汇总集、梳理角色关系<span style="color: black;">非常</span>痛苦的编辑工作，<span style="color: black;">是不是</span><span style="color: black;">能够</span>用一个简单的代码程序替代，让人从无<span style="color: black;">道理</span>的翻找典故里<span style="color: black;">摆脱</span>出来，更加专注于对内部<span style="color: black;">规律</span>的思考？<span style="color: black;">再也不</span>需要人工去剪切网页、摘抄报纸，一切的一切，就只是记关键词与出处？（<span style="color: black;">咱们</span>中学时要看的<span style="color: black;">哪些</span>经典诗词解析）</span></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;"><span style="color: black;">而后</span><span style="color: black;">针对</span>一个网站的运营，如<span style="color: black;">哪些</span>经常要关注敌方上什么促销的运营<span style="color: black;">来讲</span>，<span style="color: black;">是不是</span><span style="color: black;">能够</span>简单弄个爬虫，<span style="color: black;">定时</span>给自己推送其他家的价格促销，从而<span style="color: black;">认识</span><span style="color: black;">她们</span>的运营策略？（其实<span style="color: black;">此刻</span>若干大电商都在做，但工具下放到运营<span style="color: black;">自己</span>的，还<span style="color: black;">无</span><span style="color: black;">那样</span>多）</span></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;"> <span style="color: black;">倘若</span>写剧本的，要经典桥段<span style="color: black;">能够</span>自己写个程序把想要的意境从成千上万本剧本小说里摘出来<span style="color: black;">瞧瞧</span>，那效率该有多大<span style="color: black;">加强</span>啊，只需要学会一点点<span style="color: black;">博主</span>程，<span style="color: black;">咱们</span>就<span style="color: black;">能够</span>把自己从重复性劳动中解放出来，去做真正有价值的事情时，我觉得这才是非计算机人士业余学编程最有价值的<span style="color: black;">地区</span>。</span></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;">顺便，<span style="color: black;">近期</span>在用codecademy刷python课程，感谢这世界上总是有人愿意把一个枯燥的编程学习过程做的像打游戏<span style="color: black;">那样</span>生动有趣实时可互动。越多人做这些编程推广的事情，就会有越多人能自如编写比本文<span style="color: black;">说到</span><span style="color: black;">哪些</span>文本处理更<span style="color: black;">繁杂</span>的程序脚本，编程的门槛是越来越低了。</span></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;"> ---</span></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;">最后<span style="color: black;">便是</span>，多读书，多<span style="color: black;">瞧瞧</span>。。当初写这些代码本质上是想要阅读得快一点，记得牢一点，整理东西快一点，绝对不是为了<span style="color: black;">累积</span>资料而不看书的。<span style="color: black;">倘若</span>辛辛苦苦写了个代码帮<span style="color: black;">咱们</span>把所有感兴趣的文字都取了出来，却什么<span style="color: black;">亦</span>不看，这跟做数据分析不愿意跟<span style="color: black;">哪些</span>业务打交道<span style="color: black;">认识</span>实情的<span style="color: black;">白痴</span>有啥区别呢。。。</span></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;">顺便附上用R玩过的其他事情，欢迎吐槽：</span></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;"><span style="color: black;">·</span><span style="color: black;"><a style="color: black;"><span style="color: black;">R语言：xlsx包安装与结合VBA快速把xls</span></a>x文件转化为csv</span></span></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;"><span style="color: black;">·</span><span style="color: black;"><a style="color: black;"><span style="color: black;">R语言：处理<span style="color: black;">反常</span>值的三个示例 tryCatch</span></a></span></span></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;"><span style="color: black;">·</span><span style="color: black;"><a style="color: black;"><span style="color: black;">R语言：爬虫初尝试-RVEST包</span></a></span></span></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;"><span style="color: black;">·</span><span style="color: black;"><a style="color: black;"><span style="color: black;">R语言：ggplot2精细化制图示例</span></a></span></span></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;"><span style="color: black;">·</span><span style="color: black;"><a style="color: black;"><span style="color: black;">R语言：Kindle爬特价书示例(rvest)+R输出HTML网页示例</span></a></span></span></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;"><span style="color: black;">·</span><span style="color: black;"><a style="color: black;"><span style="color: black;">R语言：用R语言读琅琊榜小说</span></a></span></span></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;">PS又PS：</span></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;"> 这文加<a style="color: black;"><span style="color: black;">用R语言读琅琊榜小说</span></a><span style="color: black;">一块</span>，是之前为一个演讲准备的演示材料，<span style="color: black;">不外</span>当时太紧张了，还准备<span style="color: black;">有些</span>别的东西<span style="color: black;">而后</span>最后忘记讲了哈哈哈哈——结论是<span style="color: black;">倘若</span>上台讲话，<span style="color: black;">必定</span>要把想讲的东西写个小抄，<span style="color: black;">或</span>放在PPT的要点里，<span style="color: black;">否则</span>铁定忘记= =</span></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><strong style="color: blue;"><span style="color: black;">【直播课程<span style="color: black;">举荐</span>】</span></strong></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;"><img src="data:image/svg+xml,%3C%3Fxml version=1.0 encoding=UTF-8%3F%3E%3Csvg width=1px height=1px viewBox=0 0 1 1 version=1.1 xmlns=http://www.w3.org/2000/svg xmlns:xlink=http://www.w3.org/1999/xlink%3E%3Ctitle%3E%3C/title%3E%3Cg stroke=none stroke-width=1 fill=none fill-rule=evenodd fill-opacity=0%3E%3Cg transform=translate(-249.000000, -126.000000) fill=%23FFFFFF%3E%3Crect x=249 y=126 width=1 height=1%3E%3C/rect%3E%3C/g%3E%3C/g%3E%3C/svg%3E" style="width: 50%; margin-bottom: 20px;"><strong style="color: blue;">点击“阅读原文”，<span style="color: black;">就可</span>进入学习界面哦~~~</strong></span></p>
对于这个问题，我有不同的看法... 感谢你的精彩评论，带给我新的思考角度。
页:
[1]