Data is displayed in the format of the table in the R data frame. There are different data types inside the R data frames. The character can be the first column, second and third can be numeric or logical. However, each column must have the same type of data.
Following are some R data frame characteristics:
- The column’s name must be non-empty
- The rows name must be different
- The data is stored in a data frame can be a factor, character or numeric type.
- Every column carry the same number of data items.
![R Data Frame](https://tutorialsart.com/wp-content/uploads/2021/09/DF.png)
To create a data frame the data.frame()
function is used.
df <- data.frame ( a = c("Python", "R", "C++"), b = c(34, 67, 87), c = c(56, 25, 78) ) df
Output
![df1](https://tutorialsart.com/wp-content/uploads/2021/09/df1.jpg)
Summarize the Data
To summarize the data from a Data Frame we can use the summary()
function:
df <- data.frame ( a = c("Python", "R", "C++"), b = c(34, 67, 87), c = c(56, 25, 78) ) df summary(df)
Output
![df2](https://tutorialsart.com/wp-content/uploads/2021/09/df2.jpg)
Access Items of R Data Frame
To access columns from a data frame we can use single brackets [ ]
, double brackets [[ ]]
or $
.
df <- data.frame ( a = c("Python", "R", "C++"), b = c(34, 67, 87), c = c(56, 25, 78) ) df[2] df[["a"]] df$a
Output
![df3](https://tutorialsart.com/wp-content/uploads/2021/09/df3.jpg)
Add Rows
To add new rows in a Data Frame we can use the rbind()
function:
df <- data.frame ( a = c("Python", "R", "C++"), b = c(100, 150, 120), c = c(60, 30, 45) ) dfr <- rbind(df, c("Python", 110, 110)) dfr
Output
![1 40](https://tutorialsart.com/wp-content/uploads/2021/09/1-40.png)
Add Columns
To add new columns in a Data Frame we can use the cbind()
function:
df <- data.frame ( a = c("Python", "R", "C++"), b = c(100, 150, 120), c = c(60, 30, 45) ) dfc <- cbind(df, Java = c(1000, 6000, 2000)) dfc
Output
![1 41](https://tutorialsart.com/wp-content/uploads/2021/09/1-41.png)
Remove Rows and Columns
To remove rows and columns in a Data Frame we can use the c()
function:
df <- data.frame ( a = c("Python", "R", "C++"), b = c(100, 150, 120), c = c(60, 30, 45) ) dfn <- df[-c(1), -c(1)] dfn
Output
![1 42](https://tutorialsart.com/wp-content/uploads/2021/09/1-42.png)
Amount of Rows and Columns
To find the amount of rows and columns in a Data Frame we can use the dim()
function:
df <- data.frame ( a = c("Python", "R", "C++"), b = c(100, 150, 120), c = c(60, 30, 45) ) dim(df)
Output
![1 43](https://tutorialsart.com/wp-content/uploads/2021/09/1-43.png)
To find the number of columns we can also use the ncol()
function and to find the number of rows nrow()
function can be used:
df <- data.frame ( a = c("Python", "R", "C++"), b = c(100, 150, 120), c = c(60, 30, 45) ) ncol(df) nrow(df)
Output
![1 44](https://tutorialsart.com/wp-content/uploads/2021/09/1-44.png)
R Data Frame Length
To find the number of columns in a Data Frame we can use the length()
function (similar to ncol()
):
df <- data.frame ( a = c("Python", "R", "C++"), b = c(100, 150, 120), c = c(60, 30, 45) ) length(df)
Output
![1 45](https://tutorialsart.com/wp-content/uploads/2021/09/1-45.png)
Combining Data Frames
To combine two or more data frames in R vertically we can use the rbind()
function:
df1 <- data.frame ( a = c("Python", "R", "C++"), b = c(100, 150, 120), c = c(60, 30, 45) ) df2 <- data.frame ( a = c("Python", "R", "C++"), b = c(100, 150, 120), c = c(60, 30, 45) ) dfn <- rbind(df1, df2) dfn
Output
![1 46](https://tutorialsart.com/wp-content/uploads/2021/09/1-46.png)
And to combine two or more data frames in R horizontally we can use the cbind()
function.
df3 <- data.frame ( a = c("Python", "R", "C++"), b = c(100, 150, 120), c = c(60, 30, 45) ) df4 <- data.frame ( a = c("Python", "R", "C++"), b = c(100, 150, 120), c = c(60, 30, 45) ) dfnn <- cbind(df3, df4) dfnn
Output
![1 47](https://tutorialsart.com/wp-content/uploads/2021/09/1-47.png)