### Taking the data out of the glue with regex in R

code

rtip

operations

glue

unglue

Regular expressions, or regex, are…

### Mastering Data Manipulation in R with the Sweep Function

code

rtip

operations

Welcome to another exciting journey into the world of data manipulation in R! In this blog post, we’re going to explore a powerful tool in R’s arsenal: the

`sweep`

function. Whether you’re a seasoned R programmer or just starting out, understanding…

###
Introducing `plot_regression_residuals()`

from tidyAML: Unveiling the Power of Visualizing Regression Residuals

tidyaml

rtip

data-analysis

data-science

Greetings, fellow R enthusiasts! Today, we’re diving into the depths of tidyAML, specifically exploring a new gem in its arsenal:

`plot_regression_residuals()`

. Strap in as we embark on a journey to unravel the mysteries of regression residuals and witness how this function revolutionizes the way we visualize and understand…
### Unleash the Power of Your Data: Extend Excel with Python and R!

rtip

excel

python

data-analysis

viz

Have you ever felt limited by Excel’s capabilities? Sure, it’s fantastic for basic…

### 🚀 Exciting News! 🚀

tidyaml

rtip

data-analysis

data-science

I’m thrilled to announce the latest release of tidyAML, version 0.0.5, now available for download on CRAN or GitHub! 🎉

### How to Subset Data Frame in R by Multiple Conditions

code

rtip

operations

dplyr

datatable

In data analysis with R, subsetting data frames based on multiple conditions is a common task. It…

### Conquering R’s Apply Family: Your Guide to apply(), lapply(), sapply(), and tapply()

code

rtip

operations

Welcome, fellow R warriors! Today, we delve into the heart of vectorized operations with R’s “apply” family:

`apply()`

, `lapply()`

, `sapply()`

, and `tapply()`

. These functions are your secret weapons for efficiency and elegance, so buckle…
### R for the Real World: Counting those Business Days like a Pro!

code

rtip

timeseries

Hi fellow coders…

### Exploring the Enhanced Features of tidyAML’s internal_make_wflw_predictions()

code

rtip

tidyaml

Hey R enthusiasts! Steve here, and today I’m excited to share some fantastic updates about a key function in the tidyAML package –

`internal_make_wflw_predictions()`

. The latest version addresses issue #190, ensuring that all crucial data is now included in the predictions. Let’s dive…
### TidyDensity Powers Up with Data.table: Speedier Distributions for Your Data Exploration

code

benchmark

datatable

tidydensity

I’m thrilled to announce a major upgrade to the TidyDensity package that’s sure to accelerate your data analysis workflows. We’ve integrated the lightning-fast

`data.table`

package for generating tidy distribution data…
### Benchmarking the Speed of Cumulative Functions in TidyDensity

code

tidydensity

benchmark

Statistical…

### Testing stationarity with the ts_adf_test() function in R

rtip

healthyrts

timeseries

Hey there, R enthusiasts! Today, we’re going to dive into the fascinating world of time series analysis using the

`ts_adf_test()`

function from the `healthyR.ts`

R library. If you’re into data, statistics, and R coding, this is a must-know…
###
Unveiling Data Distribution Patterns with `stripchart()`

in R

rtip

viz

Data visualization is a powerful tool that allows us to uncover patterns and insights within datasets. One such tool in the R programming arsenal is the

`stripchart()`

function. If you’re looking to reveal distribution patterns in your data with style and simplicity, then this function might just become your new best friend. In this blog…

###
Solving Systems of Equations in R using the `solve()`

Function

rtip

linearequations

In mathematical modeling and data analysis, it is often necessary to solve systems of equations to find the values of unknown variables. R provides the

`solve()`

function, which is a powerful tool for solving systems of linear equations. In this blog post, we will explore the purpose of solving systems of equations, explain…

### A Handy Guide to read.delim() in R - Unraveling the Magic of Reading Tabular Data

rtip

Welcome, data enthusiasts! If you’re diving into the realm of data analysis with R, one function you’ll undoubtedly encounter is

`read.delim()`

. It’s an essential tool that allows you to read tabular data from a delimited text file and load it into R for further analysis. But fret not, dear reader, as I’ll walk you…
### R Functions for Getting Objects

rtip

Welcome, fellow programmers, to this exciting journey into the world of R functions! Today, we’ll explore four powerful functions:

`get()`

, `get0()`

, `dynGet()`

, and `mget()`

. These functions may sound mysterious, but fear not; we’ll demystify them together and see how they can be incredibly handy tools in your R toolkit. So…
### The intersect() function in R

rtip

Welcome to another exciting blog post where we delve into the world of R programming. Today, we’ll be discussing the

`intersect()`

function, a handy tool that helps us find the common elements shared between two or more vectors in R. Whether you’re a seasoned R programmer or just starting your journey…
### A Closer Look at the R Function identical()

rtip

In the realm of programming, R is a widely-used language for statistical computing and data analysis. Within R, there exists a powerful function called

`identical()`

that allows programmers to compare objects for exact equality. In this blog post, we will delve into the syntax and…

### Pulling a formula from a recipe object

rtip

recipes

tidymodels

The

`formula()`

function in R is a generic function that…
###
The `do.call()`

function in R: Unlocking Efficiency and Flexibility

rtip

As a programmer, you’re always on the lookout for tools that can enhance your productivity and make your code more efficient. In the world of R programming, the

`do.call()`

function is one such gem. This often-overlooked function is a powerful tool that allows you to dynamically call other functions, opening up a world of possibilities for…

### Why Check File Size Output for Different Methods?

rtip

excel

openxlsx

xlsx

writexl

When working with data, it is important to be aware of the file size of…

###
Exploring Data with TidyDensity: A Guide to Using `tidy_empirical()`

and `tidy_four_autoplot()`

in R

rtip

tidydensity

dplyr

purrr

Yesterday I had the need to see data that had a grouping column in it. I wanted to use the

`tidy_four_autoplot()`

function on it from the `{TidyDensity}`

library on it. This post will explain how I did it. The…

###
Mastering File Manipulation with R’s `list.files()`

Function

rtip

files

When it comes to working with files in R, having a powerful tool at your disposal can make a world of difference. Enter the

`list.files()`

function, a versatile and handy utility that allows you to effortlessly navigate through directories, retrieve file names, and perform various file-related operations. In…

### Building models with {shiny} and {tidyAML} Part 3

rtip

shiny

tidymodels

tidyaml

As data science continues to be a sought-after field…

### Looking at Daily Log Returns with tidyquant, TidyDensity, and Shiny

rtip

shiny

tidydensity

tidyquant

timeseries

In…

### A Bootstrapped Time Series Model with auto.arima() from {forecast}

rtip

timeseries

bootstrap

Time series analysis is a powerful…

### Converting a {tidyAML} tibble to a {workflowsets}

code

rtip

tidyaml

workflowsets

tidymodels

The

`{tidyAML}`

package…

### Off to CRAN! {tidyAML}

code

rtip

tidyaml

tidymodels

Are you tired of spending hours tuning and testing different machine learning models for your regression or classification problems? The new R package

`{tidyAML}`

is here to simplify the process for you! tidyAML is a simple interface for automatic machine learning that fits the tidymodels framework, making it easier for you to solve…
### Boilerplate XGBoost with {healthyR.ai}

code

rtip

xgboost

healthyrai

XGBoost, short for “eXtreme Gradient Boosting,” is a powerful…

### An Update on {tidyAML}

code

rtip

tidyaml

automl

I have been doing a lot of work on a new package called

`{tidyAML}`

. `{tidyAML}`

is a new R package that makes it easy to use the `{tidymodels}`

ecosystem to perform automated machine learning (AutoML). This package provides a simple and intuitive interface that allows users to quickly generate machine learning…

### Calendar Heatmap with {healthyR.ts}

code

rtip

healthyrts

timeseries

Calendar heatmaps are a useful visualization tool for…

### Simulating Time Series Model Forecasts with {healthyR.ts}

code

weeklytip

healthyrts

timeseries

simulation

Time series models are a powerful tool for forecasting future values…

### Create a Faceted Historgram Plot with {healthyR.ai}

code

rtip

histograms

healthyrai

One of the most important steps in data analysis is visualizing the distribution…

### Create Multiple {parsnip} Model Specs with {purrr}

code

rtip

parsnip

purrr

If you want to generate multiple

`parsnip`

model…

### Extract Boilerplate Workflow Metrics with {healthyR.ai}

code

rtip

healthyrai

When working with the

`{tidymodels}`

framework there are ways to pull model metrics from a `workflow`

, since `{healthyR.ai}`

is built on and around the `{tidyverse}`

and `{tidymodels}`

we can do the same. This post will focus on the…

### Summary Statistics with {TidyDensity}

code

weeklytip

tidydensity

datatable

Many times someone may want to see a summary or cumulative statistic for a given set of data or even from several simulations of data. I went over bootstrap plotting earlier this month, and this is a form of what we will go over today although slightly more…

### Data Preprocessing Scale/Normalize with {healthyR.ai}

code

rtip

healthyrai

recipes

A large portion of data modeling occurrs not only in the data cleaning phase but also in the

*data preprocessing*phase. This can include things like*scaling*or*normalizing*data before proceeding to the modeling phase. I will discuss one such function…

### Auto Prep data for XGBoost with {healthyR.ai}

code

rtip

healthyrai

xgboost

Sometimes we may want to…

### Bootstrapping and Plots with TidyDensity

code

tidydensity

bootstrap

weeklytip

Many times in the real world we have a data set which is actually a sample as we typically do not know what the actual population is. This is where

**bootstrapping**tends to come into play. It allows us to get a hold on what the possible parameter values are by taking repeated samples of the data that is…### TidyDensity Primer

code

weeklytip

tidydensity

This is going to serve as a sort of primer for the

`{TidyDensity}`

package.
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