如何在R数据框中对多个对象进行分类

Question

这只是我正在使用的数据框的一小部分：

id       drug        start        stop          dose    unit    route   
2010003  Amlodipine  2009-02-04   2009-11-19    1.5     mg      Oral    
2010003  Amlodipine  2009-11-19   2010-01-11    1.5     mg      Oral      
2010004  Cefprozil   2004-03-12   2004-03-19    175     mg      Oral    
2010004  Clobazam    2002-12-30   2003-01-01    5       mg      Oral

我有一个Stata do文件，它显示了我要做的事情：

replace class = "ACE Inhibitor" if strmatch(upper(drug), "CAPTOPRIL*")
replace class = "ACE Inhibitor" if strmatch(upper(drug), "ENALAPRIL*")
replace class = "ACE Inhibitor" if strmatch(upper(drug), "ENALAPRILAT*")
replace class = "ACE Inhibitor" if strmatch(upper(drug), "FOSINOPRIL*")
replace class = "ACE Inhibitor" if strmatch(upper(drug), "LISINOPRIL*")
replace class = "ACE Inhibitor" if strmatch(upper(drug), "RAMIPRIL*")
replace class = "Acne Medication" if strmatch(upper(drug), "ADAPALENE*")
replace class = "Acne Medication" if strmatch(upper(drug), "ADAPALENE/BENZOYL PEROXIDE*")
replace class = "Acne Medication" if strmatch(upper(drug), "BENZOYL PEROXIDE*")
replace class = "Acne Medication" if strmatch(upper(drug), "BENZOYL PEROXIDE/CLINDAMYCIN*")
replace class = "Acne Medication" if strmatch(upper(drug), "ISOTRETINOIN*")
replace class = "Acne Medication" if strmatch(upper(drug), "ERYTHROMYCIN/TRETINOIN*")
replace class = "Acne Medication/Acute Promyelocytic Leukemia Medication" if strmatch(upper(drug), "TRETINOIN*")
replace class = "Alpha Agonist" if strmatch(upper(drug), "XYLOMETAZOLINE*")
replace class = "Alpha Blocker" if strmatch(upper(drug), "DOXAZOSIN*")
replace class = "Alpha Blocker" if strmatch(upper(drug), "PHENOXYBENZAMINE*")
replace class = "Alpha Blocker" if strmatch(upper(drug), "PHENTOLAMINE*")
replace class = "Alpha Blocker" if strmatch(upper(drug), "PRAZOSIN*")
replace class = "Alpha Blocker" if strmatch(upper(drug), "TAMSULOSIN*")
replace class = "Alpha Blocker" if strmatch(upper(drug), "TERAZOSIN*")
replace class = "Alpha/Beta Blocker" if strmatch(upper(drug), "CARVEDILOL*")
replace class = "Alpha/Beta Blocker" if strmatch(upper(drug), "LABETALOL*")
replace class = "Alpha-1 Agonist" if strmatch(upper(drug), "PHENYLEPHRINE*")
replace class = "Alpha-1 Agonist" if strmatch(upper(drug), "MIDODRINE*")
replace class = "Alpha-2 Agonist" if strmatch(upper(drug), "CLONIDINE*")
replace class = "Alpha-2 Agonist" if strmatch(upper(drug), "DEXMEDETOMIDINE*")
replace class = "Anaesthetic, general" if strmatch(upper(drug), "KETAMINE*")
replace class = "Anaesthetic, general" if strmatch(upper(drug), "THIOPENTAL*")
replace class = "Anaesthetic, local" if strmatch(upper(drug), "BENZOCAINE*")
replace class = "Anaesthetic, local" if strmatch(upper(drug), "BUPIVACAINE*")
replace class = "Anaesthetic, local" if strmatch(upper(drug), "BUPIVACAINE/FENTANYL*")
replace class = "Anaesthetic, local" if strmatch(upper(drug), "TETRACAINE*")
replace class = "Anaesthetic, local" if strmatch(upper(drug), "XYLOCAINE*")
replace class = "Anaesthetic, local/Antiarrythmic" if strmatch(upper(drug), "LIDOCAINE*")
replace class = "Anaesthetic, local/Antiseptic" if strmatch(upper(drug), "HEXYLRESORCINOL*")
replace class = "Anaesthetic, topical" if strmatch(upper(drug), "LIDOCAINE/PRILOCAINE*")
replace class = "Anaesthetic, topical" if strmatch(upper(drug), "PROPARACAINE*")
replace class = "Analgesic" if strmatch(upper(drug), "ACETAMINOPHEN*")
replace class = "Analgesic" if strmatch(upper(drug), "BELLADONNA & OPIUM SUPPOSITORY*")

我想在R中做同样的分类，但我不知道Stata。

请注意，药物可以有多个class。

非常感谢任何建议和帮助。

Answer 1

作为第一步，我将从您的Stata脚本导入所有药物数据（假设数据不是一个干净，可用的格式）：

drug_class_data <- read.table("Desktop/stata_script", header=FALSE, sep='"',stringsAsFactors = FALSE)  
drug_class_data <-drug_class_data[,c(2,4)] 
colnames(drug_class_data) <- c('Drug_class','Drug')

删除尾随* - 用作Stata脚本中的通配符

drug_class_data$Drug = gsub("\\*", "", drug_class_data$Drug)

这为您提供了一个包含2列的数据框（'Drug_class'＆amp;'Drug'） - 该行从Stata脚本的每一行中提取引号中的所有数据（以下面的粗体突出显示）：

  

替换class =“ ACE抑制剂”如果strmatch（上层（药物），“ CAPTOPRIL * ”）

然后我将其保存为一个文件，您可以根据需要将其导入（我假设这些数据不像这样，因为您在Stata示例中对所有这些值进行了硬编码）。

write.csv(drug_class_data, file = "drug_class_data.csv",row.names=FALSE)

从那里取决于你是否想要：

1）每个药物实例有多行，其中一个文本列明确指定了药物类别。每种药物的行数=它所属的药物类别数。这种方法有一些优点，但它会导致大量重复数据。

2）每种药物的单行和每种药物类别的多个布尔列 - “ACE抑制剂”，“痤疮药物”等 - 包含二进制TRUE或FALSE以指示它是否是该类的成员。 / p>

我个人赞成选项2作为下游分析的起点。 （正如你所提到的，药物可能被归类为多个类别，也有几个药物类别呈现等级 - “麻醉，局部”可能是'麻醉，局部/抗心律失常'，'麻醉，局部/防腐'等的主要术语） / p>

将数据框中所有独特的药物类别提取到列表中：

drug_class_list <- unique(drug_class_data[,1])

然后我会使用下面的丑陋代码创建一个新的数据帧：

create_flat_table <- function(df_drugs, df_classes){   
# Extract list of drug classes present in df

class_list <- unique(df_classes[,1])  
# Reiterate over this list creating a new column in the drug df and populating it with data   
drugs <- as.list(drug_data['drug'])  
results <- df_drugs   
for(class in class_list){   
class_drugs <- df_classes[df_classes$Drug_class == class,]   
boolean_list <- toupper(df_drugs[,2])%in%class_drugs[,2]
results <- cbind(results, boolean_list )   }   
colnames(results) <- c(colnames(df_drugs), class_list)   
return(results) }

combined_df <- create_flat_table(drug_data, drug_class_data)

结果数据框如下所示：

请注意，在此示例中，我更改了数据，以便您的玩具数据集中至少有一种药物与您的药物类缩略列表中的类匹配。

Answer 2

假设import sys import gi gi.require_version('Gtk', '3.0') from gi.repository import Gtk, Gio, GObject class Application(Gtk.Application): def __init__(self): app_id = "org.iea.etc" flags = Gio.ApplicationFlags.FLAGS_NONE super(Application, self).__init__(application_id=app_id, flags=flags) def do_activate(self): # c.Controller(m.Model(), v.View(application=self)) Controller(None, View(application=self)) def do_startup(self): Gtk.Application.do_startup(self) class Controller(object): def __init__(self, model, view): self._model = model self._view = view self._view.connect('switch_serial_toggled', self._on_switch_serial_toggled) self._view.show_all() def _on_switch_serial_toggled(self, switch, state): if switch.get_active(): print('Switch ON') else: print('Switch OFF') class View(Gtk.ApplicationWindow): __gsignals__ = { 'switch_serial_toggled': (GObject.SIGNAL_RUN_FIRST, None, ()) } def __init__(self, **kw): super(View, self).__init__(**kw) self._switch_serial = Gtk.Switch() self._switch_serial.connect("notify::active", self.on_switch_serial_toggled) self.add(self._switch_serial) def on_switch_serial_toggled(self, switch, state): self.emit('switch_serial_toggled') if __name__ == '__main__': app = Application() exit_status = app.run(sys.argv) sys.exit(exit_status) 和statscript在最后的注释中可重复显示。然后使用glob模式DF将类和模式提取到translate并将连接DF提取到它。

pat

注意

translate <- read.table(text = statascript, as.is = TRUE)[c(4, 7)]
names(translate) <- c("class", "pat")

library(sqldf)
sqldf("select DF.*, translate.class 
       from DF 
       left join translate on upper(class) glob pat")