R – Data Frames

02 Dec, 2021
R Programming Language is an open-source programming language that is widely used as a statistical software and data analysis tool. Data Frames in R Language are generic data objects of R which are used to store the tabular data. Data frames can also be interpreted as matrices where each column of a matrix can be of the different data types. DataFrame is made up of three principal components, the data, rows, and columns. 
To create a data frame in R use data.frame() command and then pass each of the vectors you have created as arguments to the function.
Example: 
R
# R program to create dataframe # creating a data framefriend.data <- data.frame(    friend_id = c(1:5),    friend_name = c("Sachin", "Sourav",                    "Dravid", "Sehwag",                    "Dhoni"),    stringsAsFactors = FALSE)# print the data frameprint(friend.data)
Output: 
      friend_id friend_name
1         1      Sachin
2         2      Sourav
3         3      Dravid
4         4      Sehwag
5         5       Dhoni
One can get the structure of the data frame using str() function in R. It can display even the internal structure of large lists which are nested. It provides one-liner output for the basic R objects letting the user know about the object and its constituents. 
Example: 
R
# R program to get the# structure of the data frame # creating a data framefriend.data <- data.frame(    friend_id = c(1:5),    friend_name = c("Sachin", "Sourav",                    "Dravid", "Sehwag",                    "Dhoni"),    stringsAsFactors = FALSE)# using str()print(str(friend.data))
Output: 
'data.frame':    5 obs. of  2 variables:
 $ friend_id  : int  1 2 3 4 5
 $ friend_name: chr  "Sachin" "Sourav" "Dravid" "Sehwag" ...
NULL
In R data frame, the statistical summary and nature of the data can be obtained by applying summary() function. It is a generic function used to produce result summaries of the results of various model fitting functions. The function invokes particular methods which depend on the class of the first argument. 
Example: 
R
# R program to get the# summary of the data frame # creating a data framefriend.data <- data.frame(    friend_id = c(1:5),    friend_name = c("Sachin", "Sourav",                    "Dravid", "Sehwag",                    "Dhoni"),    stringsAsFactors = FALSE)# using summary()print(summary(friend.data))
Output: 
    friend_id friend_name       
 Min.   :1   Length:5          
 1st Qu.:2   Class :character  
 Median :3   Mode  :character  
 Mean   :3                     
 3rd Qu.:4                     
 Max.   :5   
Extract data from a data frame means that to access its rows or columns. One can extract a specific column from a data frame using its column name. 
Example: 
R
# R program to extract# data from the data frame # creating a data framefriend.data <- data.frame(    friend_id = c(1:5),    friend_name = c("Sachin", "Sourav",                    "Dravid", "Sehwag",                    "Dhoni"),    stringsAsFactors = FALSE) # Extracting friend_name columnresult <- data.frame(friend.data$friend_name)print(result)
Output: 
    friend.data.friend_name
1                  Sachin
2                  Sourav
3                  Dravid
4                  Sehwag
5                   Dhoni
A data frame in R can be expanded by adding new columns and rows to the already existing data frame. 
Example: 
R
# R program to expand# the data frame # creating a data framefriend.data <- data.frame(    friend_id = c(1:5),    friend_name = c("Sachin", "Sourav",                    "Dravid", "Sehwag",                    "Dhoni"),    stringsAsFactors = FALSE) # Expanding data framefriend.data$location <- c("Kolkata", "Delhi",                       "Bangalore", "Hyderabad",                       "Chennai")resultant <- friend.data# print the modified data frameprint(resultant)
Output: 
    friend_id friend_name  location
1         1      Sachin   Kolkata
2         2      Sourav     Delhi
3         3      Dravid Bangalore
4         4      Sehwag Hyderabad
5         5       Dhoni   Chennai
In R, one can perform various types of operations on a data frame like accessing rows and columns, selecting the subset of the data frame, editing data frames, delete rows and columns in a data frame, etc. Please refer to DataFrame Operations in R to know about all types of operations that can be performed on a data frame.
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