Visualization of EMA
Here, we will be visualizing the marks compared to the 3-day exponentially weighted moving average through the line plot.
R
library(ggplot2) library(reshape2) library(pracma) df <- data.frame(Rank=1:10, Marks=c(65, 60, 54, 46, 37, 30, 29, 25, 24, 19)) # Exponentially weighted moving average # using the 3 previous marks df$EMA <- movavg(df$Marks, n=3, type='e') df <- melt(df , id.vars = 'Rank', variable.name = 'series') ggplot(df, aes(Rank, value)) + geom_line(aes(colour = series)) |
Output:
How to Calculate an Exponential Moving Average in R?
In this article, we will look the how to Calculate an Exponential Moving Average in R Programming Language.
Exponential moving average (EMA) tells us the weighted mean of the previous K data points. EMA places a greater weight and significance on the most recent data points. To get the EMA we will use pracma package in the R programming language. To install run the following commands:
install.packages("pracma")
Creating Dataframe for demonstration
R
# create data frame df <- data.frame(Rank=1:10, Marks=c(65, 60, 54, 46, 37, 30, 29, 25, 24, 19)) # Display data frame print(df) |
Output:
Rank Marks 1 1 65 2 2 60 3 3 54 4 4 46 5 5 37 6 6 30 7 7 29 8 8 25 9 9 24 10 10 19