(R Tutorials for Business Analyst)
R Data Frame: Create, Append, Select, Subset
What is a Data Frame?
A data frame is a list of vectors which are of equal length. A matrix contains only one type of data, while a data frame accepts different data types (numeric, character, factor, etc.).
In this tutorial, you will learn-
- What is a Data Frame?
- How to Create a Data Frame
- Append a Column to Data Frame
- Select a Column of a Data Frame
- Subset a Data Frame
How to Create a Data Frame
We can create a data frame by passing the variable a,b,c,d into the data.frame() function. We can name the columns with name() and simply specify the name of the variables.
data.frame(df, stringsAsFactors = TRUE)
Arguments:
- df: It can be a matrix to convert as a data frame or a collection of variables to join
- stringsAsFactors: Convert string to factor by default
We can create our first data set by combining four variables of same length.
# Create a, b, c, d variables a <- c(10,20,30,40) b <- c('book', 'pen', 'textbook', 'pencil_case') c <- c(TRUE,FALSE,TRUE,FALSE) d <- c(2.5, 8, 10, 7) # Join the variables to create a data frame df <- data.frame(a,b,c,d) df
Output:
## a b c d ## 1 1 book TRUE 2.5 ## 2 2 pen TRUE 8.0 ## 3 3 textbook TRUE 10.0 ## 4 4 pencil_case FALSE 7.0
We can see the column headers have the same name as the variables. We can change the column name with the function names(). Check the example below:
# Name the data frame names(df) <- c('ID', 'items', 'store', 'price') df
Output:
## ID items store price ## 1 10 book TRUE 2.5 ## 2 20 pen FALSE 8.0 ## 3 30 textbook TRUE 10.0 ## 4 40 pencil_case FALSE 7.0
# Print the structure str(df)
Output:
## 'data.frame': 4 obs. of 4 variables: ## $ ID : num 10 20 30 40 ## $ items: Factor w/ 4 levels "book","pen","pencil_case",..: 1 2 4 3 ## $ store: logi TRUE FALSE TRUE FALSE ## $ price: num 2.5 8 10 7
By default, data frame returns string variables as a factor.
Slice Data Frame
It is possible to SLICE values of a Data Frame. We select the rows and columns to return into bracket precede by the name of the data frame.
A data frame is composed of rows and columns, df[A, B]. A represents the rows and B the columns. We can slice either by specifying the rows and/or columns.
From picture 1, the left part represents the rows, and the right part is the columns. Note that the symbol : means to. For instance, 1:3 intends to select values from 1 to 3.
In below diagram we display how to access different selection of the data frame:
- The yellow arrow selects the row 1 in column 2
- The green arrow selects the rows 1 to 2
- The red arrow selects the column 1
- The blue arrow selects the rows 1 to 3 and columns 3 to 4
Note that, if we let the left part blank, R will select all the rows. By analogy, if we let the right part blank, R will select all the columns.
We can run the code in the console:
## Select row 1 in column 2 df[1,2]
Output:
## [1] book ## Levels: book pen pencil_case textbook
## Select Rows 1 to 2 df[1:2,]
Output:
## ID items store price ## 1 10 book TRUE 2.5 ## 2 20 pen FALSE 8.0
## Select Columns 1 df[,1]
Output:
## [1] 10 20 30 40
## Select Rows 1 to 3 and columns 3 to 4 df[1:3, 3:4]
Output:
## store price ## 1 TRUE 2.5 ## 2 FALSE 8.0 ## 3 TRUE 10.0
It is also possible to select the columns with their names. For instance, the code below extracts two columns: ID and store.
# Slice with columns name df[, c('ID', 'store')]
Output:
## ID store ## 1 10 TRUE ## 2 20 FALSE ## 3 30 TRUE ## 4 40 FALSE
Append a Column to Data Frame
You can also append a column to a Data Frame. You need to use the symbol $ to append a new variable.
# Create a new vector quantity <- c(10, 35, 40, 5) # Add `quantity` to the `df` data frame df$quantity <- quantity df
Output:
## ID items store price quantity ## 1 10 book TRUE 2.5 10 ## 2 20 pen FALSE 8.0 35 ## 3 30 textbook TRUE 10.0 40 ## 4 40 pencil_case FALSE 7.0 5
Note: The number of elements in the vector has to be equal to the no of elements in data frame. Executing the following statement
quantity <- c(10, 35, 40) # Add `quantity` to the `df` data frame df$quantity <- quantity
Gives error:
Error in `$<-.data.frame`(`*tmp*`, quantity, value = c(10, 35, 40)) replacement has 3 rows, data has 4
Select a Column of a Data Frame
Sometimes, we need to store a column of a data frame for future use or perform operation on a column. We can use the $ sign to select the column from a data frame.
# Select the column ID df$ID
Output:
## [1] 1 2 3 4
Subset a Data Frame
In the previous section, we selected an entire column without condition. It is possible to subset based on whether or not a certain condition was true.
We use the subset() function.
subset(x, condition) arguments: - x: data frame used to perform the subset - condition: define the conditional statement
We want to return only the items with price above 10, we can do:
# Select price above 5 subset(df, subset = price > 5)
Output:
ID items store price 2 20 pen FALSE 8 3 30 textbook TRUE 10 4 40 pencil_case FALSE 7
Disclaimer: The information and code presented within this recipe/tutorial is only for educational and coaching purposes for beginners and developers. Anyone can practice and apply the recipe/tutorial presented here, but the reader is taking full responsibility for his/her actions. The author (content curator) of this recipe (code / program) has made every effort to ensure the accuracy of the information was correct at time of publication. The author (content curator) does not assume and hereby disclaims any liability to any party for any loss, damage, or disruption caused by errors or omissions, whether such errors or omissions result from accident, negligence, or any other cause. The information presented here could also be found in public knowledge domains.
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