Data Frame in R

The Data Frame in R is a table or two dimensional data structure. In R Data Frames, data is stored in row and columns, and we can access the data frame elements using the row index and column index. Following are the some of the characteristics of the Data Frame:

• A data frame is a list of variables and it must contain same number of rows with unique row names.
• The Column Names should not be Empty
• Although it supports duplicate column names by using check.names = FALSE, It is always preferable to use unique Column names.
• The data stored in a data frame can be Character type, Numeric type, or Factors

In this article we will show you, How to Create a Data Frame, How to Access Data Frame Columns and Rows, Manipulate the individual or Row level or Column level Elements, Creating Named Data Frames, and some of the important functions supported by the Data Frame in R Programming with example

R Create Data Frame

In this example, we will create a Data Frame with different element. Following code snippet will show you the most common way to create a Data Frame in R Programming.

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From the above code snippet you can observe that, First we created four vectors of different type and then we created the data frame using those four vectors.

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Creating Named Data Frame in R

In this example, we will show you the steps involved in creating named Data Frame in R programming. Syntax behind this is: DataFrame_Name <- data.frame(“index_Name1” = Item1, “index_Name2″ = Item2,… ,”index_NameN” = ItemN )

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Accessing R Data Frame Elements

In R programming, We can access the Data Frame item in multiple ways. In this example we will show you, How to access the data frame items using the index position. Using this index value, we can access each and every item present in the Data Frame. Index value starts at 1 and end at n where n is the number of items in a data frame. For example, if we declare a data frame that stores 10 items (10 columns) then index starts at 1 and ends at 10. To access 1^st value use DataFrame_Name[1] and to access the 10^th value, use DataFrame_Name[10].

We can also access the Item values using the Column Name. For example, to access the 1^st value use DataFrame_Name[“1st Column Name”] and to access the 9^th value, use DataFrame_Name[“9th Column Name”]. Lets see the example for better understanding:

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Access Elements of a Data Frame in R

We can also access the Data frame elements using the [[ double brackets. In this example we will show you, How to access the data frame items using this [[. This will return the result as a Vector with Level information

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From the above screenshot you can observe that, this is returning the same result as the above example but it is returning vector, rather than data frame.

Accessing R Data Frame items using $

In R Programming, We can also access the Data frame elements using the $ dollar symbol. In this example we will show you, How to access the elements of data frame in R using this $. This will return the result as a Vector with Level information. Syntax behind this is: <Data Frame>$Column_Name

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Accessing Low Level elements of R Data Frame

In R programming, We can access the lower level elements of the items (or individual cell) in a Data Frame using the index position. Using this index value, we can access each and every individual element present in the data frame. Index value starts at 1 and end at n where n is the number of elements in a row or column. Syntax behind this is: <Data Frame>[Row_Number, Column_Number]

For example, if we declare a data frame that has 6 row elements and 4 column elements. To access or alter 1^st value use DataFrame_Name[1, 1], to access 2^nd row 3^rd column value use DataFrame_Name[2, 3], and to access the 6^th row 4^th column use DataFrame_Name[6, 4]. Lets see the example for better understanding:

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Accessing Multiple Values from R Data

In our previous example we shown you, How to access the single element from the Data Frame. In this example we will show you, How to access multiple items from the Data Frame. To achieve the same, we use the R Vector

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Access R Data Frame Elements at Lower Level using $

In R Programming, We can also access the Data frame elements at lower level (individual cell) using the $ dollar symbol. In this example we will show you, How to access the individual cells in a data frame using this $. This will return the result as a Vector with Level information

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Modifying R Data Frame Elements

In R programming, We can access the data frame elements using the index position. Using this index value, we can alter or change each and every individual element present in the data frame. In this example we will show you, How to modify the individual Cell value, and entire column items Lets see the example for better understanding:

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Add Elements to R Data Frame

In this example we will show you, How to add the new elements to existing Data Frame in R programming.

• cbind(Data Frame, Values): This method is used to add extra Column with values. In general, we prefer Vector as values parameter
• rbind(Data Frame, Values): This method is used to add extra Row with values.

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Important Functions of Data Frame in R

Following functions are some of the most useful functions supported by the Data frame in R programming.

• typeof(Data Frame): This method will tell you the type of the Data Frame. Since, the data frame is a kind of list, this function will return a list
• class(Data Frame): This method will tell you the class of the Data Frame
• length(Data Frame): This method will count number of items (columns) in a Data Frame
• nrow(Data Frame): This method will return the total number of Rows present in the Data Frame.
• ncol(Data Frame): This method will return the total number of Columns available in the Data Frame.
• dim(Data Frame): This method will return the total number of Rows and Columns present in the Data Frame.

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Head and Tail Functions in R Data Frame

Following functions are the very useful functions supported by the Data Frame in R Programming. If your data is too big and you want to extract the top performing records then you can use these functions

• head(Data Frame, limit): This method will return top six elements (if you Omit the limit). If you specify the limit as 2 then, it will return first 2 records. It is something like selecting top 10 records.
• tail(Data Frame, limit): This method will return last six elements (if you Omit the limit). If you specify the limit as 4, it will return last four records.

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Special Functions in R Data Frame

Following two are the very useful functions supported by the Data Frame in R. It is always good to check the structure of the data before we start manipulating, or inserting new records

• str(Data Frame): This method will return return the structure of the data present in the Data Frame.
• summary(Data Frame): This method will return the nature of the data, and the statistical summery such as: Minimum, Median, Mean, Median etc.

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