For Data Science Learners
How to create a ggalluvial plot in R, The ggalluvial package’s vaccines data set includes a survey “that asked respondents their likelihood of receiving an influenza vaccination.” The discretized probability of immunization, the frequency of respondents, and the survey’s designation make up the response variable. Let’s install ggalluvial package install.packages(“ggalluvial”) library(ggalluvial) head(vaccinations) survey freq subject…
How to create a Sankey plot in R?, You must install the ggsankey library and modify your dataset using the package’s make_long function in order to produce a Sankey diagram in ggplot2. The data’s columns must correspond to the stages x (current stage), next_x (next stage), node (current node), and next_node (the following node). Keep…
While Python offers a more all-encompassing approach to data science, R is primarily employed for statistical analysis. R’s main goals are data analysis and statistics, while Python’s main goals are deployment and production. Python users tend to be programmers and developers, whereas R users are primarily academics and R&D experts. How to Standardize Data in…
Extract patterns in R, R’s str extract() function can be used to extract matching patterns from strings. It is part of the stringr package. The syntax for this function is as follows: str_extract(string, pattern) where: string: Character vector pattern: Pattern to extract The practical application of this function is demonstrated in the examples that follow….
Replace Inf Values with NA in R, you can substitute NA values for Inf values using the techniques listed below: Method 1: Replace Inf with NA in Vector x[is.infinite(x)] <- NA Example 1: Substitute NA for Inf in the Vector The code below demonstrates how to swap out all Inf values in a vector for…
Boosting in Machine Learning, A single predictive model, such as linear regression, logistic regression, ridge regression, etc., is the foundation of the majority of supervised machine learning methods. However, techniques such as bagging and random forests provide a wide range of models from repeated bootstrapped samples of the original dataset. The average of the predictions…
Read More “Boosting in Machine Learning:-A Brief Overview” »
Algorithm Classifications in Machine Learning, There is a vast array of algorithms available in the field of machine learning that can be utilized to comprehend data. One of two categories can be used to group these algorithms: Creating a model to estimate or predict an output based on one or more inputs is the first…
How do confidence intervals work?, In statistics, we’re frequently interested in calculating population parameters—numbers that capture some aspect of a population as a whole. The following are the two most typical population parameters: Population mean: the average value of a population’s variable (e.g. the mean height of males in the U.S.) Population proportion: the percentage…
How to Find Quartiles in R, A dataset is divided into four equal halves using values known as quartiles. The first quartile of a dataset corresponds to the 25th percentile. The second quartile of a dataset serves as a proxy for the 50th percentile. This sum corresponds to the median value of the dataset. The…
How to Use Italic Font in R, to create an italic typeface in R plots, use the basic syntax shown below. How to Use Italic Font in R These examples demonstrate how to apply this syntax in real-world situations. Example 1: The plot’s title in italic font The code below demonstrates how to use the…
