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Extract Data Frame Columns Stored in a List in R
Suppose we have two frames each having 5 columns that are stored in a list in R and the data that belongs to same columns has some kind of inherent relationship or we want to check whether there exists a relationship between them then we might want to extract those columns. Therefore, we can use lapply function for this extraction. For example, if we have a list called LIST that store two data frames then column 3 of each data frame can be extracted by using the command lapply(LIST,"[",3).
Example
Consider the below data frames and list of these data frames −
df1<-data.frame(x1=rnorm(20),x2=rnorm(20)) df2<-data.frame(y1=rnorm(20),y2=rnorm(20)) List<-list(df1,df2) List
Output
[[1]] x1 x2 1 -0.2616691 0.4838822161 2 -0.4962192 -0.2029131423 3 -0.6289051 0.6067368122 4 -1.8650979 -0.2673970799 5 -0.1144585 1.2794435497 6 -0.7950920 0.3237400683 7 -0.7473936 0.5272240477 8 -1.1275262 0.8650962534 9 -0.2354747 1.0057184299 10 1.3755067 0.0961681148 11 -0.1747653 1.2535584458 12 -1.5245065 1.0977974301 13 -1.9052953 -0.6178104611 14 0.6634748 0.3078744775 15 -0.3464213 -0.9288219551 16 -1.7638077 -1.3873331806 17 -0.6839449 -0.0006287789 18 -0.1494119 0.1155562131 19 -0.3583126 0.2606700288 20 -0.6148202 -0.5952164804 [[2]] y1 y2 1 -0.211831075 0.80770142 2 0.275355837 -0.37532157 3 0.026130608 0.07003241 4 -0.214784788 0.36447807 5 -0.706518246 -2.35280957 6 -0.786380214 -0.83800239 7 0.599793658 1.00900869 8 -0.952037717 0.31360048 9 -0.820999108 1.37718684 10 -1.912105297 -0.48305776 11 0.436298130 0.56800539 12 1.126854489 0.26761877 13 -2.148552234 -1.54496557 14 1.832004140 -0.93939487 15 -0.587988585 0.74063570 16 0.945827064 -0.30905531 17 -1.571678758 -0.44346002 18 -0.704557448 -0.78744069 19 -0.009306419 0.71375917 20 0.734797879 -1.88248741
Extracting column 2 from each data frame stored in List −
Example
lapply(List,"[",2)
Output
[[1]] x2 1 0.4838822161 2 -0.2029131423 3 0.6067368122 4 -0.2673970799 5 1.2794435497 6 0.3237400683 7 0.5272240477 8 0.8650962534 9 1.0057184299 10 0.0961681148 11 1.2535584458 12 1.0977974301 13 -0.6178104611 14 0.3078744775 15 -0.9288219551 16 -1.3873331806 17 -0.0006287789 18 0.1155562131 19 0.2606700288 20 -0.5952164804 [[2]] y2 1 0.80770142 2 -0.37532157 3 0.07003241 4 0.36447807 5 -2.35280957 6 -0.83800239 7 1.00900869 8 0.31360048 9 1.37718684 10 -0.48305776 11 0.56800539 12 0.26761877 13 -1.54496557 14 -0.93939487 15 0.74063570 16 -0.30905531 17 -0.44346002 18 -0.78744069 19 0.71375917 20 -1.88248741
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