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Data Analysis and Visualization Tutorials

How to Calculate Manhattan Distance in R

  • R-PROGRAMMING
To calculate manhattan distance in R, you can use dist() function with method argument or create function manually. The Manhattan distance is the sum of absolute differences in each dimension of the data points. The following method shows how you can do it with syntax. Method 1: Use dist() Function dist(matrix,method="manhattan") Method 2: Create Function Manually manhattan_dist <- function(x, y){ dist <- abs(x-y) dist <- sum(dist) return(dist) } The following example shows how to calculate manhattan distance in R.
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How to Calculate Partial Correlation in R

  • R-PROGRAMMING
To calculate partial correlation in R, you can use pcor() function from ppcor package. The partial correlation is used to calculate correlation between two columns of data frame while controlling third column of data frame. The following method shows how you can do it with syntax. Method: Use pcor() Function library(ppcor) p <- pcor(df) The following example shows how to calculate partial corrlation in R. Use pcor() to Calculate Partial Correlation Let’s see how we can calculate partial correlation of data frame:
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How to Calculate Point-Biserial Correlation in R

  • R-PROGRAMMING
To calculate point-biserial correlattion in R, you can use cor.test() function. The point-biserial correlation coefficient measures the strength and direction of the association between a continuous variable and a binary variable. The following method shows how you can do it with syntax. Method: Use cor.test() Function cor.test(vector1,vector2) The following example shows how to calculate point-biserial correlation in R. Using cor.test() Function Let’s see how we can calculate point-biserial correlation using cor.
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How to Calculate Polychoric Correlation in R

  • R-PROGRAMMING
To calculate polychoric correlation in R, you can use polycor() function from polycor package. The polychoric correlation measures the association between two ordinal variables by estimating the correlation between the underlying continuous variables. The following method shows how you can do it with syntax. Method: Use polycor() Function library(polycor) polychor(vector1,vector2) There is value for polychoric correlation ranges from -1 to 1. -1 :-indicates a perfect negative correlation. 0:- indicates no correlation.
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How to Create a Pie Chart in R

  • R-PROGRAMMING
To create a pie chart in R, you can use three different ways using base R, using ggplot2 package or using plotrix library. The following methods show how you can do it with syntax. Method 1: Use pie() Function pie(values, labels = labels, main = "Pie Chart") Method 2: Use ggplot() Function library(ggplot2) ggplot(df, aes(x = "", fill = category, weight = value)) + geom_bar(width = 1) + coord_polar("y", start = 0) + labs(x = NULL, y = NULL, fill = NULL, title = "Pie Chart") Method 3: Use pie3D() Function
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How to Find and Visualize Quartiles in R

  • R-PROGRAMMING
To find and and visualize quartile values in R, you can use quantile() function boxplot() function respectively. The following methods show how you can do it with syntax. Method: Use quantile() Function quantile(data) Method: Use boxplot() Function boxplot(data, ylab = "y", xlab = "x", main = "Boxplot with Quartiles") The following examples show how to find and visualize quartile values in R using quantile() and boxplot() function. Using quantile() Function Let’s see how we can use quantile() function in R:
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How to Use cor() to Calculate Correlation Coefficients in R

  • R-PROGRAMMING
The cor() function is used to calculate correlation between two variables in R. This function returns value between -1 to 1. The following method shows how you can do it with syntax. Method: Use cor() Function cor(x,y) The following example shows how to use cor() function in R. Use cor() to Calculate Correlation Between Two Vectors Let’s see how we can calculate correlation between two vectors using cor() function: # Create vector x <- c(77,85,89,85,82,88,81,89) y <- c(77,78,79,81,84,85,85,89) # Find correlation coefficient cor(x,y) Output:
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How to Use length() Function in R

  • R-PROGRAMMING
The length() function is used to find the length of list,vector or data frame. The following method shows how you can do it with syntax. Method: Use length() Function length(x) The following examples show how to use length() function in R. Use length() Function to Find Length of Vector Suppose we want to find length of vector using length() function: # Define vector vector1 <-c(45,85,89,78,12,36,68,32,12) # Find length len <- length(vector1) # Show length print(len) Output:
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How to Use lines() Function in R

  • R-PROGRAMMING
The lines() function is used to add lines to an existing plot in R. The following method shows how you can do it with syntax. Method: Use lines() Function lines(x, y, col, lwd, lty) x: Vector of x-coordinates y: Vector of y-coordinates col: Color of line lwd: Line width lty: Type of line The following example shows how to use lines() function in R: Use lines() Function to Add Line in Plot Let’s see how we can add line to plot using lines() function:
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How to Use mean Function in R

  • R-PROGRAMMING
The mean() function is used to calculate mean value of numeric vector,dataframe or list in R. The following method shows how you can do it with syntax. Method: Use mean() Function mean(x) The following examples show how to use mean() function in R. Use mean() Function to Calculate Mean of Vector Let’s see how we can calculate mean of numeric vector using mean() function: # Declare vector x <- c(2.39,11.25,12.15,13.48,13.78,12.89,12.21,12.58) # Calculate mean of vector mean_x = mean(x) # Show mean print(mean_x) Output:
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How to Use the quantile() Function in R

  • R-PROGRAMMING
The quantile() function in R used to calculate sample quantiles values from dataset.The quantile are values that divide dataset into equal groups. The following method shows how you can do it with syntax. Method: Use quantile() Function quantile(x, probs = seq(0, 1, 0.25),na.rm=FALSE) x : name of dataset probs : numeric dataset of probabilities na.rm : used for whether to remove NA values. The following examples show how to use quantile() function in R.
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