Category: R

Fundamentals of Exploratory and Inferential Spatial Data Analysis in R workshop

Learn how to work with Spatial Data in R, while contributing to charity! Join our workshop on Fundamentals of Exploratory and Inferential Spatial Data Analysis in R which is a part of our workshops for Ukraine series. 

Here’s some more info: 

Title: Fundamentals of Exploratory and Inferential Spatial Data Analysis in R
Date:  Thursday, September 13th, 18:00 – 20:00 CEST (Rome, Berlin, Paris timezone)
Speaker: Denys Dukhovnov, Ph.D. student in Demography at University of California, Berkeley. His research revolves around small-area estimation and geographic inequalities in mortality in the United States. He holds a previous M.A. degree in Data Analytics and Applied Social Research, held multiple research positions in social science fields, and currently works as a researcher at the Human Mortality Database (HMD).
Description: This workshop will provide a hands-on overview of the exploratory and inferential spatial data analysis in R. The attendees will become familiar with statistical concepts of spatial adjacency and dependence and with various methods of measuring it (using such indicators as Moran’s I, Geary’s C, LISA/ELSA plots, etc.), as well as with statistical challenges of working with spatial data (e.g. modifiable areal unit problem or MAUP). In addition, the workshop will provide a foundational overview of inferential spatial analysis, specifically through the application of the basic types of spatial econometric regression models (SAR, SLX, SEM models). An emphasis will be made on the interpretation and reporting of the model performance and results. Prior familiarity with spatial data types and OLS regression is helpful, but not necessary.

How can I register?
  • Go to https://bit.ly/3wvwMA6 or  https://bit.ly/3PFxtNA and donate at least 20 euro. Feel free to donate more if you can, all proceeds go directly to support Ukraine.
  • Save your donation receipt (after the donation is processed, there is an option to enter your email address on the website to which the donation receipt is sent)
  • Fill in the registration form, attaching a screenshot of a donation receipt (please attach the screenshot of the donation receipt that was emailed to you rather than the page you see after donation).

If you are not personally interested in attending, you can also contribute by sponsoring the participation of a student, who will then be able to participate for free. If you choose to sponsor a student, all proceeds will also go directly to organizations working in Ukraine. You can either sponsor a particular student or you can leave it up to us so that we can allocate the sponsored place to students who have signed up for the waiting list.

How can I sponsor a student?
  • Go to https://bit.ly/3wvwMA6 or https://bit.ly/3PFxtNA and donate at least 20 euro (or 17 GBP or 20 USD or 750 UAH). Feel free to donate more if you can, all proceeds go to support Ukraine!
  • Save your donation receipt (after the donation is processed, there is an option to enter your email address on the website to which the donation receipt is sent)
  • Fill in the sponsorship form, and attaching the screenshot of the donation receipt (please attach the screenshot of the donation receipt that was emailed to you rather than the page you see after the donation). You can indicate whether you want to sponsor a particular student or we can allocate this spot ourselves to the students from the waiting list. You can also indicate whether you prefer us to prioritize students from developing countries when assigning place(s) that you sponsored.

You can also find more information about this workshop series,  a schedule of our future workshops as well as a list of our past workshops which you can get the recordings & materials of here.

Looking forward to seeing you during the workshop!

How to generate data from a model – Part 1


Summary

Traditionally, data scientists have built models based on data. This article details how to do the exact opposite i.e. generate data based on a model. This article is first in the series of articles on building data from model. 

Motivation & Practical Applications

Businesses across various industry domains are embracing Artificial Intelligence(AI) and Machine Learning(ML) driven solutions. Furthermore, it is observed that the recent increase in the cloud based Machine Learning Operations (ML Ops) tools such Azure ML has made AI/ML solutions relatively more accessible,  easy to deploy and in some cases more affordable. Additionally, it is also observed that there is an increase in the usage of Auto ML & feature engineering packages. These approaches reduce manual intervention during model build and retraining stages.  Since the focus is predominantly on building ML pipelines as opposed to the traditional approach of building models manually, the robustness of the pipelines needs to be inspected. This is still an evolving field and currently is being handled by model observability tools. This article proposes one such method of observability. The purpose of this method can be best represented in the form of a question as given below.

What if we built the underlying data distributions, the outliers, the dependent variable and then put it through the ML Ops pipeline?  Wouldn’t we know where the pipeline worked well and where it could have done better?
This question motivated the build of a Software as a Service (SaaS) product called uncovr. This product can now be accessed through an R package conjurer by following the steps outlined below.

Data from Model Using R

Step 1: Register for the API

    • Head over to the API developer portal at (https://foyi.developer.azure-api.net/).
    • Click on the Sign up button on the home page.
    • Register your details such as email, password etc.
    • You will receive an email to verify your email id.
    • Once you verify your email id, your account will be setup and you will receive a confirmation email.
    • Once your account is set up, please head over to the products section on the developer portal and select the product starter. Currently, this is the only subscription available. Give your subscription a name, read and accept the terms and click Subscribe. 
    • On your profile page, under the subscriptions section, click on show next to the Primary key. That is the subscription key you will need to access the API.

Step 2: Install R Package Conjurer

Install the latest version of the package from CRAN as follows.
install.packages("conjurer")

Step 3: Generate data

Generate the data using the code below.

library(conjurer)
uncovrJson <- buildModelData(numOfObs = 1000, numOfVars = 3, key = "input your subscription key here")
df <- extractDf(uncovrJson=uncovrJson)

The above code has two steps. The first step is to connect to the API and source the data in JSON  format. The second step is to convert the JSON format to an R dataframe.

The components of the function buildModelData are as follows.
    • numOfObs is the number of observations i.e. rows of data that you would like to generate. Please note that the current version allows you to generate from a minimum of 100 observations to a maximum of 10,000. 
    • numOfVars is the number of independent variables i.e. columns in the data. Please note that the current version allows you to generate from a minimum of 1 variable to a maximum of 100.
    • key is the Primary key that you have sourced from the earlier step.
The data frame df (in the code above) will have three columns with the names iv1, iv2, iv3 and one column dv. The columns with prefix iv are the independent variables while the dv is the dependent variable. You can rename them to suit your needs. 
The model used in the current version to generate the data is a linear regression model. The details of the model formula and its estimated performance can be inspected as follows. 
    • To begin with, you can inspect the JSON data that is received from the API by using the code  str(uncovrJson). This should display all the components of the JSON file. The attributes prefixed as slope are the coefficients of the model formula corresponding to the number. For example, slope1 is the coefficient corresponding to iv1 i.e. independent variable 1. 
    • The regression formula used to construct the data for the example data frame is as follows.
      Please note that the formula takes the form of Y = mX + C.
      dv = intercept + (slope1*iv1) + (slope2*iv2) + (slope3*iv3) + error.
    • Please note that while the slopes i.e. the coefficients are at variable level, the error is at each observation level. These errors can be accessed as uncovrJson$error

Concluding Remarks

The underlying API uncovr is under development and as new functionality is released, the R package conjurer will be updated to reflect those changes. For any feature requests or bug reports, please follow the contribution guidelines on GitHub repository. If you would like to follow the future releases and news, please follow our LinkedIn page.

Learn data skills, earn points and win money prizes daily with Datacamp!

tl;dr

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DataCamp’s gamified learning experience ensures learners enjoy upskilling in data. And for a limited time only, they’ve made the experience rewarding too! Get a chance to win up to $1500* by simply learning data science on the DataCamp platform. Until Aug 31, the amount of XP you earn will determine the amount of cash money you can win—every day. Start learning for Free *Rules of the XP Learner Challenge:
Earn XP to win cash. Every right answer you get increases your chances of winning a prize.
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Learn More

Time to upskill in R? EARL’s workshop lineup has something for every data practitioner.

It’s well-documented that data skills are in high demand, making the industry even more competitive for employers looking for experienced data analysts, data scientists and data engineers – the fastest-growing job roles in the UK. In support of this demand, it’s great to see the government taking action to address the data skills gap as detailed in their newly launched Digital Strategy.

The range of workshops available at EARL 2022 is designed to help data practitioners extend their skills via a series of practical challenges. Led by specialists in Shiny, Purrr, Plumber, ML and time series visualisation, you’ll leave with tips and skills you can immediately apply to your commercial scenarios.

The EARL workshop lineup.


Time Series Visualisation in R.

How does time affect our perception of data? Is the timescale important? Is the direction of time relevant? Sometimes cumulative effects are not visible with traditional statistical methods, because smaller increments stay under the radar. When a time component is present, it’s likely that the current state of our problem depends on the previous states. With time series visualisations we can capture changes that may otherwise go undetected. Find out more.

Explainable Machine Learning.

Explaining how your ML products make decisions empowers people on the receiving end to question and appeal these decisions. Explainable AI is one of the many tools you need to ensure you’re using ML responsibly. AI and, more broadly, data can be a dangerous accelerator of discrimination and biases: skin diseases were found to be less effectively diagnosed on black skin by AI-powered software, and search engines advertised lower-paid jobs to women. Staying away from it might sound like a safer choice, but this would mean missing out on the huge potential it offers. Find out more.

Introduction to Plumber APIs.

90% of ML models don’t make it into production. With API building skills in your DS toolbox, you should be able to beat this statistic in your own projects. As the field of data science matures, much emphasis is placed on moving beyond scripts and notebooks and into software development and deployment. Plumber is an excellent tool to make the results from your R scripts available on the web. Find out more.

Functional Programming with Purrr.

Iteration is a very common task in Data Science. A loop in R programming is of course one option – but purrr (a package from the tidyverse) allows you to tackle iteration in a functional way, leading to cleaner and more readable code. Find out more.

How to Make a Game with Shiny.

Shiny is only meant to be used to develop dashboards, right? Or is it possible to develop more complex applications with Shiny? What would be the main limitations? Could R and Shiny be used as a general-purpose framework to develop web applications? Find out more.

Sound interesting? Check out the full details – our workshops spaces traditionally go fast so get yourself and your team booked in while there are still seats available. Book your Workshop Day Pass tickets now.

Charity R Workshops in support of Ukraine

Learn R (as well as Python and other tools for data analysis) and contribute to charity at the same time. 

Since April, we have been running a series of weekly workshops on R and other tools for data analysis, all proceeds from which go to support Ukraine. Our workshops cover topics for people with different prior levels of experience in R: from complete beginners to experienced users. All workshops are recorded, so you can register even if you are not able to attend in person!

Introduction to R Shiny

 Our next workshop on R will take place on August 4th and will cover Introduction to R Shiny.  You will (a) learn how to set up basic statistical simulations, (b) learn how to create data-based applications, and (c) cover the nuts and bolts of the user interface in Shiny.

 To register you can donate 20 euros here or here and fill in this registration form, attaching the donation confirmation which will be emailed to you. If you are a student who is not able to pay the registration fee, you can sign up for the waiting list here. If you are not interested in this workshop but would like to support us, make a donation & support students in learning, you can sponsor a student by donating 20 euros per student here or here and filling in this form. You can read more about this workshop here.
Introduction to Quarto

 We also will have a workshop on Introduction to Quarto on August 11th. You will learn how to create and publish documents using Quarto, a modern platform for creating professional articles, slide decks, websites, and other publications. By way of an introductory example, participants will be walked through the process of crafting and publishing their own personal professional website.

 To register you can donate 20 euros here or here  and fill in this registration form, attaching the donation confirmation which will be emailed to you. If you are a student who is not able to pay the registration fee, you can sign up for the waiting list here. If you are not interested in this workshop but would like to support us, make a donation & support students in learning, you can sponsor a student by donating 20 euros per student here or here and filling in this form. You can read more about this workshop here.

 Previous workshops

 If you make a donation, you can also get recordings and materials of any of our previous workshops. We have a wide range on workshops in R available from Introduction to R in Tidyverse and Data Visualization with ggplot to Text Data Analysis in R, Web Scraping in R and Introduction to Spatial Data Analysis in R. You can read more information about all of our past workshops and find out how to get access to the recordings and the materials here (scroll to ‘previous workshops’ section).

 More information

 You can find more information about any of our upcoming workshops here. You can also subscribe to our mailing list to get updates about the future workshops here. If you experience any issues with registration process or have any questions or suggestions, feel free to email me at [email protected]

Refine your R Skills with Free Access to DataCamp

Introducing Free Week 

DataCamp is excited to announce their Free Week commencing Monday, 18 July at 8 AM ET. Anyone interested in developing their R programming skills or improving their data literacy can enjoy unlimited free access for a week until 24 July at 11:59 PM. 

For those who are new to R or are supporting teams using R, now is the time to dig deeper into the programming language. DataCamp offers R courses from introductory courses to more advanced topics, meaning you’ll find learning opportunities no matter your level. 

Free Access for Individuals 

To access DataCamp Free Week for individuals, you’ll only need your email address when signing up on their Free Week page.
Once you’ve signed up, you will have access to their entire library of 387 courses, 83 projects, 55 practice sessions, and 15 assessments across Python, R, SQL, Power BI, Tableau, and more. If you are an R loyalist, you’ll be happy to hear about our 149 courses specializing in your favorite programming language.
Free Week access for individuals starts at 8 am ET on 18 July and finishes at 11.59 pm ET on 24 July. 
Not only that, but to ensure you finish the week off with confidence, you also have access to the following resources:

Moreover, for their intermediate and advanced learners solely interested in developing your R skills, their skill and career tracks are perfect for you. They have skill and career tracks specially curated for developing R programming skills where you get to develop your knowledge in the following areas:

Free Access for Teams

DataCamp recognizes and appreciates the increasing dependence that companies have on data-driven decisions. With that, we created DataCamp for Business to help businesses upskill their workforce to become data-driven.
In DataCamp for Business, you and your team will have access to the following resources:
  • Build learning programs with their team to create custom learning paths just for your team (eg. if your team specializes in R, their team will help create R-specialized learning pathways)
  • Report on your ROI using DataCamp’s visualization and spreadsheet tools to thoroughly understand your team’s progress
  • Upskill your company by investing in professional development for all roles and skill levels
  • Get started and scale using DataCamp’s integrations

If you want to start developing your team today, sign up to DataCamp Teams during Free Week, and gain seven days of free access from the point of sign up. 
You will receive seven days’ free access from the point of sign-up, and your payment will automatically renew after that period. 
We cannot wait for you to join them along with 2,500 other companies that have upskilled their team with DataCamp. They are proud to have a diverse list of clients, including top companies from consulting, the FTSE 1000, and 180+ government agencies. 

Why this is the year you should take the stage at EARL 2022…

EARL is Europe’s largest R community event dedicated to showcasing commercial applications of the R language. As a conference, it has always lived up to its promise of connecting and inspiring R users with creative suggestions and solutions, sparking new ideas, solving problems and sharing perspectives to advance the community. 

2022 marks the return of face-to-face EARL (6th – 8th September at the Tower Hotel in London) – now run by Ascent, the new home of Mango Solutions. Over the past eight years, EARL has attracted some fascinating presentations from some engaging, authentic speakers, both experienced and first timers. This year, we’re keen to understand how recent global events and trends that have disrupted our view of ‘normal’ have impacted, changed or driven your R projects: from inspirational innovation to reducing operational cost and creating richer customer experiences. If you have an interesting application of R, our call for abstracts is now open and we’re inviting you to share your synopsis with us. Deadline for submissions is Thursday 30th June.  Maybe you’ve built a Shiny app that helps detect bias, or you’ve been on a data journey you’d like to share. Perhaps you’ve built a data science syllabus for young minds or created an NLP tool to automate clinical processes. If you are searching for inspiration, potential applications of R might come under the following categories:
  • Responding to global events with R
  • The role of R in the business data science toolbox
  • Overcoming the challenges of using R commercially
  • Efficient R: dealing with huge data
  • Sustainable R / R for good
  • R tools & packages (eg. Shiny R, Purrr)
  • Building your R community
  • Women in R
  • The future of R in enterprise: 2022 and beyond
We are also looking for short form submissions: 10-minute lightning talks on a wide range of applications.

What’s presenting at EARL really like?  

We asked our 2019 presenters what prompted their decision to speak at our last in-person EARL and their advice to others who may be considering submitting an abstract for EARL 2022. For Mitchell Stirling, Capacity and Modelling Manager at Heathrow Airport, the opportunity to present helped fulfil a professional ambition. “I discussed with my line manager, slightly tongue in cheek, that it should be an ambition in 2019 when he signed off a conference attendance in Scotland the previous year. As the work I’d been doing developed in 2019 and the opportunity presented itself, I started to think “why not?” – this is interesting and if I can show it interestingly, hopefully others would agree. I was slightly wary of the technical nature of the event, with my exposure to coding in R still better measured in minutes than hours (never mind days) but a reassurance that people would be interested in the ‘what’ and ‘why’ as well as the ‘how’, won me over.”  Dr Zhanna Mileeva, a Data Scientist at NBrown Group confirmed that making a contribution to the data science community was an important factor in her decision to submit an abstract: “After some research I found the EARL conference as a great cross-sector forum for R users to share Data Science, AI and ML engineering knowledge, discuss modern business problems and pathways to solutions. It was a fantastic opportunity to contribute to this community, learn from it and re-charge with some fresh ideas.” In past years EARL has attracted speakers from across the globe and last year, Harold Selman, Lead Data Scientist at Ordina (NL) came from the Netherlands to speak at the conference. “I knew the EARL conference as a visitor and had given some presentations in The Netherlands, so I decided to give it a shot. The staff of the EARL conference are very helpful and open to questions, which made being a speaker very pleasant.”  Some of our presenters have enjoyed the experience so much they have presented more than once. Chris Billingham, Lead Data Scientist at Manchester Airport Group’s Digital Agency MAG-O, is one such speaker. “I’ve had the good fortune to present twice at EARL.  I saw it as an opportunity to challenge myself to present at the biggest R conference in the UK.” 

How to submit your abstract. 

Feeling inspired? You can find the abstract submission form on our website. Here’s our recommendations for a successful submission.
  • Topic: Your topic can relate to any real-world application of R. We aim to represent a range of industry sectors and a balance of technical and strategic content.
  • Clarity: The talk synopsis should provide an overview of the topic and why you believe it will be of interest or resonate with the audience. We suggest an introduction or problem statement alongside any supporting facts that determine the talk objectives or expected takeaways.
  • Storytelling: Aim to demonstrate how the tools and techniques you used helped to transform and translate value with a clear and compelling narrative.
  • Approval: Before you submit, it’s a good idea to ensure your application has been approved by your wider organisation and or team.
  • Novel: Is the application particularly new or innovative? If your application of R is new or distinctive and not widely written about in the industry, please provide as much supporting information as you can for review purposes.
  • Target audience: 34% of our attendees are R practitioners and 46% of delegates typically have senior or leadership roles – consider the alignment of your proposal with these audiences.
We hope these hints and tips have been helpful – but feel free to get in touch if you have any questions by contacting [email protected]. 

EARL your way: book your tickets now!

Your EARL tickets are now live to purchase here. Offering you every possible EARL ticket combination, here is a quick summary of what you can expect. You can simply choose a 3-day jam-packed conference pass or a 1 or 2-day option to customise an itinerary that works for you.

Grab your EARLy bird tickets right away – limited for a period of 2 weeks and 2 weeks only, we are delighted to be offering an unlimited amount of tickets ranging from 15-25% discount on all ticket options, depending if you are NHS, not for profit or an academic.

Team networking.

Why not bring your colleagues along for a much needed team social at the largest commercial R event in the UK? Offering lots of networking opportunities from brands in similar markets – there will be plenty of time to swap market experiences, over coffee, at lunch or at our evening reception. We are certainly proud to be a part of such an enthusiastic community.

Full or half day workshop on day 1.

We are running a 1-day series of workshops to kick off EARL on 6th September, covering all areas of R from explainable machine learning, to time series visualisation, functional programming with purr, an introduction to plumber APIs to having some fun and making games in Shiny. There is plenty of choice with morning and afternoon sessions agenda.

Full conference pass.

Our all-access pass to EARL gives you full access to a 1-day workshop, full 2-day conference pass and access to the evening reception at the unforgettable Drapers Hall on day 2 – the former home of Henry VIII. We have got an impressive line-up of keynotes including mathematician, science presenter and all-round badass – Hannah Fry, Top 100 Global Innovator in Data & Analytics – Harry Powell and the unmissable Financial Times columnist John Burn-Murdock. To add to this excitement, we have approved used cases from Bumble, Samaritans, BBC, Meta, Bank of England, Dogs Trust, NHS, and partners RStudio alongside many more.

1 or 2-day conference pass.

If you would like access to the keynotes, session talks and abundance of networking opportunities, you can choose from a 1 or 2-day pass aligned to your areas of interest. The 2-day conference pass gives you access to the main evening reception.

Evening reception.

This year we have opted for an unforgettable experience at Drapers Hall (the former home of Henry VIII), where you will get the ability to network with colleagues, delegates and speakers over drinks, canapes, and dinner in unforgettable surroundings. Transport is provided in a provide London red bus transfer. This year promises an unforgettable experience, with a heavy weight line up, use cases from leading brands and the opportunity at last to share and network to your heart’s content. We look forward to meeting you. Book your tickets now.

useR! 2022 – all virtual – is next week!

useR! 2022 logo

Hello!

The all-virtual useR! 2022 conference opens next week, on 20 June, with 6 keynotes, 18 tutorials, and dozens of talks and posters to choose from.

Keynote speakers include Paola Moraga, Amanda Cox, the Afrimapr project, Julia Silge, Sebastian Meyer, and Mine Dogucu.

See the program overview at the conference website:
https://user2022.r-project.org/program/overview/

If you haven’t yet enrolled, sign up here
(free for people from low income countries, and price ranges from $6 to $85, depending on the country and if student/academia or industry):
https://user2022.r-project.org/participate/registration/

Sincerely,
The organizing committee of useR! 2022
— 


If curious, here are the fees

Conference Fees

Conference fees help pay for the virtual platform, honoraria for tutorial and keynote speakers, and other expenses. The fees depend on the country where you live, and whether you work in industry or academia or are a student. The academia rate applies to non-profit organizations and government employees and the student rate applies to retired people. Freelancers are encouraged to select the rate that best applies.
High Income Country    Higher Middle Income Country    Lower Middle Income Country    Low Income Country   
Industry    $85 $29 $12 waived
Academia    $65 $22 $9 waived
Student $45 $14 $6 waived

Tutorial Fees

The fees listed below are for two tutorials. If you book only one tutorial, you will get a 50% discount. If you select three tutorials the fee will be 50% higher.
High Income Country    Higher Middle Income Country    Lower Middle Income Country    Low Income Country   
Industry    $75 $22 $9 waived
Academia    $55 $19 $8 waived
Student $35 $12 $5 waived



You may go ahead and sign-up here:
https://user2022.r-project.org/participate/registration/

useR! 2022 is almost here / casi ha llegado / approche à grands pas

useR! 2022 logo
[ES: Desplazándose hacia abajo por favor para el texto en español.
FR: Faites défiler svp pour le text français.]

Hello!

The all-virtual useR! 2022 conference opens on 20 June – less than 1 month from now – with 6 keynotes, 18 tutorials, and dozens of talks and posters to choose from. Tutorial spots are first-come, first-reserved, and some sessions are already sold out!

If you’ve already registered, we thank you – we’re looking forward to welcoming you at the new conference platform next month.

If you haven’t yet enrolled, now’s the time! Sign up at our website: https://user2022.r-project.org/participate/registration/

We’re excited about this year’s lineup, and we can’t wait to share it all with you!

Sincerely,
The organizing committee of useR! 2022

 — 

¡Hola!

La conferencia completamente virtual useR! 2022 abre el 20 de junio, en menos de un mes, con 6 charlas principales, 18 tutoriales y decenas de charlas y posters para elegir. Los espacios disponibles para tutoriales son por orden de llegada. ¡Algunas sesiones ya están agotadas!

Agradecemos a las personas que ya se registraron: las personas que hacemos useR! estamos ansiosas por saludarte en la nueva plataforma de la conferencia el próximo mes.

Si aún no te has inscrito ¡ahora es el momento! Regístrate ahora en nuestro sitio web: https://user2022.r-project.org/participate/registration/ 

¡El equipo está muy entusiasmado con el programa de este año y no vemos la hora de compartirlo contigo! 

Sinceramente,
Comité organizador de useR! 2022

— 

Bonjour!

La conférence virtuelle useR! 2022 s’ouvre le 20 juin, dans moins d’un mois, avec 6 discours luminaires, 18 tutoriels et des dizaines de courts discours et d’affiches. Certaines séances sont déjà complètes.

Aux personnes déjà inscrites: nous vous remercions. Nous nous réjouissons de vous accueillir sur la nouvelle plateforme de conference le mois prochain.

Si vous n’êtes pas déjà inscrit, c’est le moment! 

https://user2022.r-project.org/participate/registration/

Nous sommes ravis du programme de cette année et nous avons hate de le partager avec vous.

Amicalement,
Comité d’organisation d’useR! 2022