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My Posit::conf 2023 Experience - A Conference of Insights, Knowledge, Connections, and Explorations

The Posit::conf 2023 (formerly known as RStudio conference) was held in Hyatt Regency in Chicago, Illinois, USA from 16 to 20 September, 2023. This was the first conference held since the name was changed from RStudio to Posit. It was a conference full of learning, making connections, and feeling inspired. As an attendee, I had the privilege of participating in workshops, attending various events, listening to great talks, meeting talented individuals, and experiencing the empowering atmosphere of R Ladies.

Some useful functions to wrangle with time series data

Time series data wrangling

Building a website using Quarto

In this post, you will learn how to build a website using Quarto.

Error: C stack usage is too close to the limit

Delete .Rprofile

Logistic Regression: Model Building and Interpretation

Logistic regression is a widely used modelling approach, however little is known about the modelling processes and interpretation of model outputs. This post demonstrates how to build a logistic model with R and how to interpret the results.

Zoom Your Plots with ggforce

You can use facet_zoom from the ggforce package to zoom out graphs instead of using your mouse (Contextual zoom).

Formatting axis labels in ggplot

With the ggplot2 package, you’ve got full control over the axes labels in charts. Here we are going to look at some of the most commonly needed formatting options in order to make your graph aesthetically pleasing

Coronavirus Dashboard - Sri Lanka

The 2019 Novel Coronavirus COVID-19 (2019-nCoV) Data in Sri Lanka

Covid-19/ Coronavirus data in Sri Lanka

The 2019 Novel Coronavirus COVID-19 (2019-nCoV) Data in Sri Lanka

Weighted LOESS (LOcal regrESSion)

LOcal regrESSion (LOESS) or LOcally WEighted Scatter-plot Smoother (LOWESS) LOESS or LOWESS is a nonparametric technique to fit a smooth curve through points in a scatter plot. This approach uses locally estimated linear regression at its core. The following code illustrates how to include a loess line using the ggplot2 package. library(ggplot2) set.seed(1) x <- rnorm(60) y <- c(rnorm(40), 10, rnorm(19)) df <- data.frame(x=x, y=y) ## Without weights ggplot(data=df, aes(x=x, y=y)) + geom_point() + geom_smooth(method=loess, legend=FALSE) Furthermore your can plot loess smoothing weighting the observations as follows: