Joining Rows and Columns in Data Frame
In R, we can join two vectors or merge two data frames using functions. There are basically two functions that perform these tasks:
cbind():
We can combine vectors, matrix or data frames by columns using cbind() function.
Syntax: cbind(x1, x2, x3)
where x1, x2 and x3 can be vectors or matrices or data frames.
rbind():
We can combine vectors, matrix or data frames by rows using rbind() function.
Syntax: rbind(x1, x2, x3)
where x1, x2 and x3 can be vectors or matrices or data frames.
Example:
R
# Cbind and Rbind function in Rname <- c("Shaoni", "esha", "soumitra", "soumi")age <- c(24, 53, 62, 29)address <- c("puducherry", "kolkata", "delhi", "bangalore")# Cbind functioninfo <- cbind(name, age, address)print("Combining vectors into data frame using cbind ")print(info)# creating new data framenewd <- data.frame(name=c("sounak", "bhabani"), age=c("28", "87"), address=c("bangalore", "kolkata"))# Rbind functionnew.info <- rbind(info, newd)print("Combining data frames using rbind ")print(new.info) |
Output:
[1] "Combining vectors into data frame using cbind "
name age address
[1,] "Shaoni" "24" "puducherry"
[2,] "esha" "53" "kolkata"
[3,] "soumitra" "62" "delhi"
[4,] "soumi" "29" "bangalore"
[1] "Combining data frames using rbind "
name age address
1 Shaoni 24 puducherry
2 esha 53 kolkata
3 soumitra 62 delhi
4 soumi 29 bangalore
5 sounak 28 bangalore
6 bhabani 87 kolkata
Data Reshaping in R Programming
Generally, in R Programming Language, data processing is done by taking data as input from a data frame where the data is organized into rows and columns. Data frames are mostly used since extracting data is much simpler and hence easier. But sometimes we need to reshape the format of the data frame from the one we receive. Hence, in R, we can split, merge and reshape the data frame using various functions.
The various forms of reshaping data in a data frame are:
- Transpose of a Matrix
- Joining Rows and Columns
- Merging of Data Frames
- Melting and Casting
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