Keras provides a simple and flexible API to build and experiment with neural networks. I used it in both python and R, but I decided to write this post in R since there are less examples and tutorials. This series of posts will focus on text classification using keras. The introductory post will show a minimal example to explain: text pre-processing in keras. how and why to use embeddings. [Read More]
R-Ladies at DataFest Tbilisi
In November 2018, I attended DataFest Tbilisi 2018 as I was invited by R-Ladies Tbilisi to give a talk, a workshop and mentor participants in a Datathon. It was a great opportunity and I would particularly highlight the second and third day were we had R-Ladies Room for R lovers with a series of workshops and a Datathon organized and led by R-Ladies who were the main representatives of the R community there. [Read More]
Handling R errors the rlang way
Custom conditions, subclasses and more!
Every day we deal with errors, warnings and messages while writing, debugging or reviewing code. The three types belong to conditions in R. You might hope to see as few of them as possible, but actually they are so helpful when they describe the problem concisely and refer to its source. So if you write functions or code for yourself or others, it is a good practice to spend more time in writing descriptive conditions. [Read More]
Tidy Eval Meets ggplot2
The Bang Bang Plots
Almost a year ago I wrote about my My First Steps into The World of Tidy Eval. At the end I tweeted asking Hadley Wickham and Lionel Henrey whether ggplot2 was compatible with the tidy eval, They said that it was on the todo list. Finally, ggplot2 3.0.0 got released last week with the support of tidy eval, so I thought it was time to write about it! ggplot2 3.0.0 now on CRAN — https://t. [Read More]
#runconf18: My First rOpenSci Unconf Experience
Last week I had the opportunity to attend rOpenSci #runconf18. It was a remarkable event, in which ~60 diverse people gathered to work on projects related to open data, package development, data visualization, reproducibility, education and more. But before talking about the unconf details, let me tell you my story with rOpenSci! I don’t remember exactly the first time I heard about rOpenSci, but I think it was around two years ago. [Read More]
What do you want to do with strings?
A couple of days ago, I passed by Sarah Drasner’s Array Explorer. It was through a retweet by Emily Robinson, who proposed the idea of a similar app for working with strings in R. I thought about giving it a try, and I deployed a preliminary Shiny App Stringr Explorer; which is still under development. In the following sections, I will give a brief about the data extracted from the package documentation to use in the Stringr Explorer app, and I’ll be glad to get better suggestions and contributions. [Read More]
Adding Skimr Spark Histograms in Dataframe Columns
A couple of weeks ago, I was looking for a package, I previously passed by, that prints summary statistics with inline histograms. I checked all my bookmarks and liked tweets, but I couldn’t find it! So I asked on twitter. fortunately Maëlle Salmon read the tweet and guided me to skimr by ropenscilabs, who actually release many useful packages. In this post, I will focus on spark histograms in summary statistics and beyond. [Read More]
My First Steps into The World of Tidy Eval
A couple of months ago, Tidy eval was something that I passed by, but didn’t have time to explore. As usual, sometimes one gets busy with the daily work, and puts some stuff aside to come back to. However, I like to find ways that give me a higher level of flexibility and more control. So mid June, I had an inquiry regarding programming around dplyr. I wasn’t sure how to pass a variable column names to purrr::map, so I opened an issue; purrr::map() support for SE/variable column names? [Read More]
Highlights from UseR! 2017
Teaching R to new UseRs, the journey of package development, and more!
In the first week of July, the 14th UseR! conference took place in Brussels as the biggest UseR!. For me, it was the first UseR! and I believe it was a good opportunity to get exposed to different approaches in the data world, see different applications, learn about new packages and meet people in the R community, all in one place. There were lots of interesting things to be highlighted. [Read More]