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How to convert an old data frame to new data frame in R?
To convert an old data frame to a new data frame, we can simply set the new name. For example, if we have a data frame called df and want to convert it to a new one let’s say df_new then it can be done as df_new<-df. But if we want to change the column names as well then data.frame needs to be used and the new column names will be assigned as shown in the below examples.
Example1
Consider the below data frame −
> x1<-rpois(20,5) > x2<-rpois(20,5) > df1<-data.frame(x1,x2) > df1
Output
x1 x2 1 8 6 2 4 9 3 3 2 4 3 5 5 7 4 6 4 8 7 8 6 8 12 12 9 8 6 10 8 6 11 3 4 12 8 3 13 8 8 14 1 8 15 7 7 16 7 2 17 6 6 18 8 4 19 1 7 20 3 7
Converting df1 to a new data frame −
> new_df1<-data.frame(v1=df1$x1,v2=df1$x2) > new_df1
Output
v1 v2 1 8 6 2 4 9 3 3 2 4 3 5 5 7 4 6 4 8 7 8 6 8 12 12 9 8 6 10 8 6 11 3 4 12 8 3 13 8 8 14 1 8 15 7 7 16 7 2 17 6 6 18 8 4 19 1 7 20 3 7
Example2
> y1<-rnorm(20) > y2<-rnorm(20) > df2<-data.frame(y1,y2) > df2
Output
y1 y2 1 0.16271874 -0.13815830 2 -0.71427991 0.59659353 3 0.91988256 -0.93139535 4 0.21826390 -1.05463645 5 -0.46250555 0.23841747 6 -2.33005442 0.01311722 7 0.07587324 -0.60952309 8 1.69626502 -0.54502419 9 -0.69264529 -1.61676626 10 0.52631934 -0.26636235 11 0.54617330 -1.52785395 12 0.06885748 0.79790822 13 1.21325507 1.36154991 14 -1.30941046 -2.13603119 15 0.87466151 -1.07515475 16 0.48641809 0.58819125 17 -1.06275086 -0.79261408 18 -0.59022569 0.08437131 19 -0.26362438 -1.31612747 20 -1.06148933 -0.36654012
Converting df2 to a new data frame −
> new_df2<-data.frame(Var1=df2$y1,Var2=df2$y2) > new_df2
Output
Var1 Var2 1 0.16271874 -0.13815830 2 -0.71427991 0.59659353 3 0.91988256 -0.93139535 4 0.21826390 -1.05463645 5 -0.46250555 0.23841747 6 -2.33005442 0.01311722 7 0.07587324 -0.60952309 8 1.69626502 -0.54502419 9 -0.69264529 -1.61676626 10 0.52631934 -0.26636235 11 0.54617330 -1.52785395 12 0.06885748 0.79790822 13 1.21325507 1.36154991 14 -1.30941046 -2.13603119 15 0.87466151 -1.07515475 16 0.48641809 0.58819125 17 -1.06275086 -0.79261408 18 -0.59022569 0.08437131 19 -0.26362438 -1.31612747 20 -1.06148933 -0.36654012
Updated on: 05-Mar-2021
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