AssociationRulesJobs

library(arules)

## Warning: package 'arules' was built under R version 4.2.1

## Loading required package: Matrix

## 
## Attaching package: 'arules'

## The following objects are masked from 'package:base':
## 
##     abbreviate, write

library(tidygraph)

## Warning: package 'tidygraph' was built under R version 4.2.1

## 
## Attaching package: 'tidygraph'

## The following object is masked from 'package:stats':
## 
##     filter

library(arulesViz)

## Warning: package 'arulesViz' was built under R version 4.2.1

DSSalary<-read.transactions("D:/archive (2)/SM_DSJobs_2.csv", sep=",")

## Warning in asMethod(object): removing duplicated items in transactions

summary(DSSalary)

## transactions as itemMatrix in sparse format with
##  246 rows (elements/itemsets/transactions) and
##  306 columns (items) and a density of 0.02322121 
## 
## most frequent items:
##     100       L      US      MI      SE (Other) 
##     134     132     110     103      77    1192 
## 
## element (itemset/transaction) length distribution:
## sizes
##   6   7   8 
##  10 200  36 
## 
##    Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
##   6.000   7.000   7.000   7.106   7.000   8.000 
## 
## includes extended item information - examples:
##   labels
## 1  <100K
## 2   <10K
## 3   <15K

inspect(DSSalary[1:20])

##      items                           
## [1]  {company_location,              
##       company_size,                  
##       employee_residence,            
##       experience_level,              
##       job_title,                     
##       remote_ratio,                  
##       Salary bin,                    
##       salary_in_usd}                 
## [2]  {<10K,                          
##       0,                             
##       2876,                          
##       Data Scientist,                
##       MI,                            
##       MX,                            
##       S}                             
## [3]  {<10K,                          
##       100,                           
##       4000,                          
##       Data Engineer,                 
##       IR,                            
##       M,                             
##       MI}                            
## [4]  {<10K,                          
##       0,                             
##       4000,                          
##       Data Scientist,                
##       EN,                            
##       M,                             
##       VN}                            
## [5]  {<10K,                          
##       3D Computer Vision Researcher, 
##       50,                            
##       5423,                          
##       IN,                            
##       M,                             
##       MI}                            
## [6]  {<10K,                          
##       100,                           
##       5695,                          
##       Data Scientist,                
##       IN,                            
##       MI,                            
##       S,                             
##       US}                            
## [7]  {<10K,                          
##       50,                            
##       5707,                          
##       Data Science Consultant,       
##       EN,                            
##       IN,                            
##       M}                             
## [8]  {<10K,                          
##       0,                             
##       5898,                          
##       Big Data Engineer,             
##       CH,                            
##       EN,                            
##       IN,                            
##       L}                             
## [9]  {<10K,                          
##       0,                             
##       6072,                          
##       Data Analyst,                  
##       EN,                            
##       IN,                            
##       S}                             
## [10] {<10K,                          
##       100,                           
##       6072,                          
##       IN,                            
##       L,                             
##       MI,                            
##       Product Data Analyst}          
## [11] {<10K,                          
##       50,                            
##       8000,                          
##       Data Analyst,                  
##       L,                             
##       MI,                            
##       PK}                            
## [12] {<10K,                          
##       100,                           
##       9272,                          
##       BI Data Analyst,               
##       EN,                            
##       KE,                            
##       S}                             
## [13] {<15K,                          
##       100,                           
##       10000,                         
##       Data Analyst,                  
##       EN,                            
##       NG,                            
##       S}                             
## [14] {<15K,                          
##       12000,                         
##       50,                            
##       M,                             
##       Machine Learning Scientist,    
##       MI,                            
##       PK}                            
## [15] {<15K,                          
##       100,                           
##       12000,                         
##       AI Scientist,                  
##       EN,                            
##       M,                             
##       PK,                            
##       US}                            
## [16] {<15K,                          
##       100,                           
##       12000,                         
##       AI Scientist,                  
##       BR,                            
##       EN,                            
##       S,                             
##       US}                            
## [17] {<15K,                          
##       0,                             
##       13000,                         
##       BR,                            
##       Data Scientist,                
##       MI,                            
##       S}                             
## [18] {<15K,                          
##       0,                             
##       13105,                         
##       Data Engineer,                 
##       M,                             
##       MI,                            
##       TR}                            
## [19] {<15K,                          
##       100,                           
##       13400,                         
##       Data Scientist,                
##       EN,                            
##       L,                             
##       UA}                            
## [20] {<20K,                          
##       100,                           
##       15966,                         
##       DE,                            
##       EN,                            
##       ML Engineer,                   
##       S}

itemFrequencyPlot(DSSalary, topN = 20, type = "absolute", main = "top 20 most frequent Items")

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Note that the echo = FALSE parameter was added to the code chunk to prevent printing of the R code that generated the plot.