R语言data manipulation学习笔记之创建变量、重命名、数据融合

数据分析中数据处理也就是data manipulation是十分繁琐的，为此我将在博客里特意建一个分类：Data Manipulation。本文将讲讲如何在R语言中创建变量、重命名以及merge。

create a dataset

fy <- c(2010,2011,2012,2010,2011,2012,2010,2011,2012)
company <- c("Apple","Apple","Apple","Google","Google","Google","Microsoft","Microsoft","Microsoft")
revenue <- c(65225,108249,156508,29321,37905,50175,62484,69943,73723)
profit <- c(14013,25922,41733,8505,9737,10737,18760,23150,16978) 
companiesData <- data.frame(fy, company, revenue, profit)
head(companiesData)
##     fy   company revenue profit
## 1  2010   Apple   65225  14013
## 2  2011   Apple  108249  25922
## 3  2012   Apple  156508  41733
## 4  2010  Google   29321   8505
## 5  2011  Google   37905   9737
## 6  2012  Google   50175  10737

接下来我们需要查看数据集的结构，用str()函数查看

str(companiesData)
## 'data.frame':    9 obs. of  4 variables:
##  $ fy     : num  2010 2011 2012 2010 2011 ...
##  $ company: Factor w/ 3 levels "Apple","Google",..: 1 1 1 2 2 2 3 3 3
##  $ revenue: num  65225 108249 156508 29321 37905 ...
##  $ profit : num  14013 25922 41733 8505 9737 ...

可以看到年份fy这里是是数值型，我们需要更改为因子型，方便后期处理

companiesData$fy <- factor(companiesData$fy, ordered = TRUE)

现在数据已经整理过好了，下面我们来添加变量，比如我们可以看看各个公司的利润率

companiesData$margin <- (companiesData$profit/companiesData$revenue)*100
#查看数据
head(companiesData)
##     fy company revenue profit   margin
## 1 2010   Apple   65225  14013 21.48409
## 2 2011   Apple  108249  25922 23.94664
## 3 2012   Apple  156508  41733 26.66509
## 4 2010  Google   29321   8505 29.00651
## 5 2011  Google   37905   9737 25.68790
## 6 2012  Google   50175  10737 21.39910

小数点位数太多了，这里我们保留一位

companiesData$margin <- round(companiesData$margin, 1)
head(companiesData)
##     fy company revenue profit margin
## 1 2010   Apple   65225  14013   21.5
## 2 2011   Apple  108249  25922   23.9
## 3 2012   Apple  156508  41733   26.7
## 4 2010  Google   29321   8505   29.0
## 5 2011  Google   37905   9737   25.7
## 6 2012  Google   50175  10737   21.4

这样我们就创建了一个新的变量margin，当然也可以删除变量，只要复制需要删除的变量NULL就行了。

#delete variable margin
companiesData$margin <- NULL
head(companiesData)
##     fy company revenue profit
## 1 2010   Apple   65225  14013
## 2 2011   Apple  108249  25922
## 3 2012   Apple  156508  41733
## 4 2010  Google   29321   8505
## 5 2011  Google   37905   9737
## 6 2012  Google   50175  10737

再顺便介绍一下transform函数，用于创建变量，transform的格式如下

dataFrame <- transform(dataFrame, newColumn = oldColumn1 + oldColumn2)
companiesData <- transform(companiesData, margin=round((profit/revenue)*100), 1)
head(companiesData)
##     fy company revenue profit margin X1
## 1 2010   Apple   65225  14013     21  1
## 2 2011   Apple  108249  25922     24  1
## 3 2012   Apple  156508  41733     27  1
## 4 2010  Google   29321   8505     29  1
## 5 2011  Google   37905   9737     26  1
## 6 2012  Google   50175  10737     21  1

接下来讲一下merge，主要是merge函数，它要求进行融合的两个数据集需要有共同的变量即id，使用格式如下：

finaldt <- merge(dataset1, dataset2, by="id")

这里我们再创建一个数据集用于merge

#creat another dataset
company <- c("Apple","Google","Microsoft")
ava1 <- c(1,2,3)
data2 <- data.frame(company, ava1)
head(data2)
##     company ava1
## 1     Apple    1
## 2    Google    2
## 3 Microsoft    3

数据集data2与数据集companiesData具有共同的变量company(id)

#merge the two dataset
newdata <- merge(companiesData, data2, by="company")

这样就得到一个完整的数据集了，当然添加行、列还有两个很有用的函数：rbind()以及cbind(),这里就不介绍了 最后讲一下重命名，其实很简单

companiesData$company <- c("A", "A", "A", "G", "G", "G", "M", "M", "M")
head(companiesData)
##     fy company revenue profit margin X1
## 1 2010       A   65225  14013     21  1
## 2 2011       A  108249  25922     24  1
## 3 2012       A  156508  41733     27  1
## 4 2010       G   29321   8505     29  1
## 5 2011       G   37905   9737     26  1
## 6 2012       G   50175  10737     21  1
#rename the colname
colnames(companiesData) <- c("Year", "Com", "Rev", "Pro", "Mar")

seessioninfo

sessionInfo()
## R version 3.4.0 (2017-04-21)
## Platform: x86_64-w64-mingw32/x64 (64-bit)
## Running under: Windows 8.1 x64 (build 9600)
## 
## Matrix products: default
## 
## locale:
## [1] LC_COLLATE=Chinese (Simplified)_China.936 
## [2] LC_CTYPE=Chinese (Simplified)_China.936   
## [3] LC_MONETARY=Chinese (Simplified)_China.936
## [4] LC_NUMERIC=C                              
## [5] LC_TIME=Chinese (Simplified)_China.936    
## 
## attached base packages:
## [1] stats     graphics  grDevices utils     datasets  methods   base     
## 
## loaded via a namespace (and not attached):
##  [1] compiler_3.4.0  backports_1.1.0 magrittr_1.5    rprojroot_1.2  
##  [5] tools_3.4.0     htmltools_0.3.6 yaml_2.1.14     Rcpp_0.12.11   
##  [9] stringi_1.1.5   rmarkdown_1.5   knitr_1.16      stringr_1.2.0  
## [13] digest_0.6.12   evaluate_0.10

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浙江大学作物遗传育种在读研究生（生物信息学方向）
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