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Data Manipulation and Transformation Tutorials

How to Use with() and within() Functions in R

  • R-PROGRAMMING
In R we use with() and within() function to evaluate expression based on dataframe. The following methods show how you can do it with syntax. Method 1: Use with() Function with(df,expression) Method 2: Use within() Function within(df,expression) expression : expression to evaluate The with() evaluates the expression without modifying the original data frame. The within() evaluates the expression and creates a copy of the original data frame. Let’s first create data frame to apply expression:
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Import CSV with Column Names that Contain Spaces

  • R-PROGRAMMING
Suppose you want to import CSV file and keep the spaces in the column names, you can use the check.names=FALSE argument. The following method shows how you can do it with syntax. Method 1: Import CSV file with Column Names Contains Spaces df <- read.csv("data.csv",check.names=FALSE) The following example shows how to import CSV with column names that contain spaces in R. Import CSV file with Column Names Contains Spaces Let’s first import csv file in R without using check.
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Remove a Column in a Data Frame in R

  • R-PROGRAMMING
To remove column from dataframe in R, you can use four different ways: The following methods show how you can do it with syntax. Method 1: Use subset() with Negative Index subset(df, select = -n) Method 2: Use subset() with Column Name subset(df, select = -column_name) Method 3: Use Indexing Operator df[, !names(df) %in% c('column_name')] Method 4: Use select() Function library(dplyr) df %>% select(-column_name) The following examples show how to remove column from dataframe in R.
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Add a New Column to Data Frame in R

  • R-PROGRAMMING
To add new column to data frame in R, you can use two different methods. The following methods show how you can do it with syntax. Method 1: Use $ Operator df$new_column <- c(value1,value2,value3,....) Method 2: Use cbind() Function df <- cbind(df,new_column = c(value1,value2,value3,....)) Let’s first create data frame using data.frame() function: # Create data frame df <- data.frame(Start_date=as.Date(c("2000-05-21","1998-03-28","2001-01-19","2003-04-27","2004-11-26","2008-11-25")), Machine_name = c("Machine1","Machine2","Machine3","Machine4","Machine5","Machine6"), Value = c(108,120,135,95,98,105),Reading= c(110,97,91,89,80,85)) # Print data frame print(df) Output:
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Convert Numeric to Character Column in R Data Frame

  • R-PROGRAMMING
To convert numeric to character column of data frame in R, you can use as.character() function. The following method shows how you can do it with syntax. Method: Use as.character() Function as.character(df$column_name) Let’s first create data frame and check data type of each column data frame: # Create data frame df <- data.frame(Start_date=as.Date(c("2000-05-21","2000-05-22","2000-05-23","2000-05-24","2000-05-25","2000-05-26")), Machine_name = c("Machine1","Machine2","Machine1","Machine3","Machine2","Machine3"), Value = c(108,120,135,95,98,105),Reading= c(110,97,91,89,80,85)) # Print data frame print(df) # print datatype print(str(df)) Output:
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How to Aggregate Multiple Columns in R

  • R-PROGRAMMING
You can use aggregate() function for multiple column of data frame in R.The aggregate() function is basically used calculate statistical summary of multiple columns of data frame based on group. The following method shows how you can do it with syntax. Method: Use aggregate() Function aggregate(column1 ~ column2, data = data frame, FUN = mean) column1: Column used for applying aggregate() function. column2: Column used for applying group_by function. The following examples show how to use aggregate() function in R.
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How to Calculate Expected Value in R

  • R-PROGRAMMING
To calculate expected value in R, there two different ways are available in R. The following methods show how you can do it with syntax. Method 1: Use sum() Function sum(data*probability) Method 2: Use mean() Function mean(data) The following example shows how to calculate expected value in R. Using sum() Function Let’s see how to use sum() function to calculate expected value when we have sample data and probability values:
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How to Count Number of Elements in List in R

  • R-PROGRAMMING
To count the number of elements in list in R, you can use length() function or length() function. The length() function gives count of number of elements in list and lengths() function gives count of number of elements in each component of list. The following methods show how you can do it with syntax. Method 1: Use length() Function length(list) Method 2: Use lengths() Function lengths(list) The following examples show how to count number of elements in list.
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How to Count Number of Occurrences in Columns in R

  • R-PROGRAMMING
To count number of occurences in columns of data frame in R, you can use table() function or count() function from dplyr package. The following method shows how you can do it with syntax. Method 1: Use table() Function table(df) Method 2: Use count() Function library(dplyr) count(df) The following examples show how to count occurences in column of data frame in R. Count Occurrences in Columns in R Using table() Function Let’s see how we can use table() function to count number occurences in columns of data frame:
2 min Read 1

How to Count Number of Rows in R

  • R-PROGRAMMING
To count number of rows in R data frame, you can use nrow() function. The following method shows how you can do it with syntax. Method: Use nrow() Function nrow(df) The following example shows how to use nrow() function to count number of rows in data frame. Using nrow() Function Let’s see how to use nrow() function in R: # Create dafaframe df <- data.frame(Machine_name=c("A","B","C","D","E","F","G","H","A","B","A","C","D","B","E","H"), Pressure=c(12.39,11.25,12.15,13.48,13.78,12.89,12.21,12.58,9.6,8.85,7.89,10.24,12.36,11.45,9.47,8.12), Status=c("OK","Suspect","OK","OK","Suspect","Suspect","Suspect","OK","OK","OK","OK","OK","Suspect","Suspect","Suspect","OK")) # Count total rows in data frame r <- nrow(df) # Print count of rows print(r) Output:
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How to Create the Identity Matrix in R

  • R-PROGRAMMING
To create identity matrix in R, you can use diag() function. The following method shows how you can do it with syntax. Method: Use diag() Function diag(n) The following example shows how to create identity matrix in R using diag() function. Using diag() Function Let’s see how use diag() function to create identity matrix: # Create identity matrix ident <- diag(5) # Print identity matrix print(ident) Output: [,1] [,2] [,3] [,4] [,5] [1,] 1 0 0 0 0 [2,] 0 1 0 0 0 [3,] 0 0 1 0 0 [4,] 0 0 0 1 0 [5,] 0 0 0 0 1 Here the output shows identity matrix of 5X5 whicj created using diag() function.
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How to Manually Enter Raw Data in R

  • R-PROGRAMMING
In R, you can manually enter raw data in using c() function to create vectors. The following methods shows how to do it with syntax. Method 1: Enter Raw Data Using Vector x <- c(value1,value2,...) Method 2: Enter Raw Data to a Data Frame data.frame(vector1, vector2, vector3) Method 3 : Enter Raw Data in Matrix cbind(vector1,vector2,...) The following examples shows how to enter raw data in R. Create Vector to Enter Raw Data Let’s see example to create vector:
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