EARL Purrr workshop
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This week we spoke to Xinye Li, Head of Data Science at Mango Solutions, to talk about his career thus far and what people can expect to learn at the ‘Functional Programming with Purrr’ EARL workshop.

Hi Xinye, thanks for joining me today. Could you tell me about your career and what you do at Mango currently?

I joined the Mango/Ascent 3 months ago as Head of Data Science, before that I had been a full-time Data Scientist with pretty hands-on responsibility – in coding, delivering results for both client-side business as well as agency. That means I have gained quite a wide range of experience with problems businesses can face – and dealing with the different stages of data maturity and how businesses go from coming up with questions and using data to solve those problems. At the core, I am a passionate Data Scientist who is always happy to write code and will always be fascinated by new developments in Data Science.

You are teaching the ‘Functional programming with Purrr‘ workshop at EARL online – could you let us know a bit more about the workshop and what people could expect to learn?

Talking of new developments, in the R language especially, I think the functional programming aspect of R is being talked about a lot more now. It has always been its core strength – for example, many base R maths symbols are actually sugar coating of functional implementations in the back end without people realising it.

Some of the latest best practices in coding in R such as Shiny Modules have surfaced the need to understand functional programming. With companies such as RStudio and their open-source contributions, this has been made a lot more fun and easier to practice functional programming. So the aim of the workshop is to introduce the idea of functional programming, demonstrate how to implement that with R, and provide some useful tips to write good functions. As an example, purrr is a package designed to work with the functional programming paradigm in R – the code is much easier to manage and it’s easy to convert the code to massively parallel processing with minimal effort.

Thanks, Xinye! We can’t wait for your workshop.

The Enterprise Applications of the R Language Conference is back online in 2021 from the 6th-10th of September. Tickets are now on sale for the four workshops and the final day of presentations on using R in enterprise.

Every year we train thousands of people worldwide from a range of backgrounds and industries, in face-to-face and virtual classrooms. Our instructors have extensive subject matter experience and real-world application knowledge. Please get in touch if you’d like to find out more about our training services.



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The next edition of LondonR online will take place on Tuesday the 27th of July from 4pm (BST). Tickets are free for attendees and you can register here for a place!

This next LondonR will have three presenters all sharing their work on using R stats in the real world.

The first presenter joining us is Paulito Palmes from the IBM Dublin Research Lab, he will be presenting on ‘JuliaR for data science and machine learning workflow’. Paulito is a research scientist at the IBM Research Europe (Dublin Research Lab) working in the areas of analytics, datamining, machine learning, reinforcement learning, automated decisions, and AI.

Next on the agenda at LondonR will be one of the Mango Solutions team, Elizabeth Brown. Elizabeth joined Mango as a professional placement student, with a key interest in Data Science and Shiny app development. Elizabeth will be presenting on ‘Creating a Shiny Dashboard as a Tool for Learning Git’. A best practice in Data Science is using Git for version control, something which isn’t introduced until working in industry. Thus, Elizabeth has developed a Shiny dashboard as a tool for beginners to learn how to use Git. In her presentation, she will give a demo of the app and how she has used {golem} and {shinyjs} in its development.

The final presenter place at LondonR will be announced shortly. We hope to see you there!


RStudio Managed Service
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Author: Rich Adams, RStudio Partner Manager

Free webinar: How to successfully manage your R environment – the RStudio managed service platform (22nd July @ 4PM BST)

In a free session on Thursday 22nd July, we’ll be discussing how data science teams can confidently and securely collaborate with large data sets in R, supported  with the right expertise where capacity or skills may otherwise be lacking internally.

With guest speakers Lou Bajuk, Director of Product Marketing, RStudio and Will Yuill, Principal Public Health Analyst, Hertfordshire County Council, we’ll explore how data science teams can develop a best practice managed service production environment and achieve maximum return on investment from their data science cloud platform. Register here

What’s the webinar about?

 As a language, R can come with restrictions when it comes to the implementation and necessary technical know-how of installing, configuring, and supporting a centralised platform for maximum adoption.

Many teams lack the required support from IT or the necessary knowledge that makes an environment suitable for future scalability. This can impact a team in their ability to manage large data sets, collaborate with ease and often mean a duplication of effort.

This webinar focuses on how to develop a best practice production environment, ensuring technical excellence and maximum return on investment from your data science platform.

Also under discussion is:

  • How to effectively reduce barriers to scaling your R environment through a ‘RStudio Managed service’
  • How Hertfordshire County Council overcame their barriers through the extra pressure of Covid-19 through a managed Services platform

Why is it important?

As we have seen from this year, scaling of data science teams and investment in data-driven strategies is even more crucial than ever.

If like Hertfordshire County Council your team has seen a rapid development, yet you lack the internal expertise and resources to support an RStudio environment – a managed services platform maybe the secure, compliant and effective cloud environment that can be up and running effectively almost immediately.  This expert Managed Service removes the need for specialist in-house IT expertise and guarantees a service level agreement to meet your requirements in terms of configuration, maintenance, and system updates.

Can you join us on 22th July, 4pm to learn more?

The Public Health Evidence & Intelligence Team at Hertfordshire Country Council will discuss why this is already providing an effective solution for them.

Register for the webinar here 

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This week I (Laura Swales, Community and Events Manager) spoke with Beth Ashlee and Owen Jones ahead of their EARL workshop – Package Development in R, which will take place on 7th September 2pm BST.

Hi Beth and Owen! Before we talk about what people can learn from the workshop, could you tell me a bit about yourselves?

Owen – As a Data Science Consultant,  I work on wide range of projects from a broad spectrum of industries. Most recently I’ve been working with the UK Government as part of the UK’s response to the Covid pandemic. I’m also the ValidR tech lead, which means that I do a lot of automated package testing too.

Beth – I’m a Senior Data Scientist and a Team Lead at Mango, so my role is very similar to Owen’s in that I work on a range of consultant projects. My most recent project was with a large retailer, working with them to upskill their Data Science team. Along with the consultancy work, I manage a team of Data Scientists at Mango.

You are both teaching the Package Development in R workshop at EARL – can you tell us a bit more about the workshop and what people can expect to learn?

Beth – They’re going to learn how to build a package in R (!), but more importantly, the reasons why that’s useful to do. We’ll talk about how it can make your code easier to maintain for others to use it and how to write good documentation…

Owen – There’s a lot of best practice incorporated in this workshop, in terms of how you are structuring the code you are writing and how you make it easy for yourself and others to contribute and maintain. Above all else, it’s about good practice, consistency, and code which other people can both use and look after.

Beth – All using the RStudio dev tools package!

How many EARL Conferences have you been to,  if you can remember?!

Owen- I think it’s 5 for me! Starting in 2017 with London, shortly followed by Boston EARL.

Beth – All of those for me as well, plus a San Fransico EARL in 2017 and two in Boston, so maybe 7 or 8 EARL’s!

I believe I’ve been to 8 now – the US Roadshow helped push up my EARL number quite quickly! Do you have any particularly fond memories or highlights?

Owen – I enjoyed the Shiny testing workshop that Beth and I collaborated on a few years back. We’ve both delivered workshops in the past that have always been really fun to work on.

Beth – Agreed! Other than those, I always enjoy the keynote talk because the talks are usually approachable to everyone – Jenny Bryant in Boston jumps out at me as being a great example of a keynote we’ve had. Outside of the actual conference, I and another colleague got booed off stage doing karaoke in America – which was definitely memorable!

Thank you both for talking to me – we are really looking forward to your workshop.

Beth and Owen’s workshop will run on the 7th of September and will be £90 for a half day. For more information on their workshop and to get your tickets, click here.


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EARL 2021 will start with a week of afternoon workshops, hosted by our expert Mango Solutions Data Scientists.

This morning I (Laura Swales, Community and Events Manager) caught up with Alejandro Rico who is hosting the ‘Introduction to Shiny’ workshop to find out more about him and what people can learn from his workshop.

Hi Alejandro! Could you tell us some background information about yourself and what you do at Ascent?

I started with maths and statistics and trying to use that knowledge somewhere in business. More often than not, the decisions I made for businesses were automated – normally when you are a Data Scientist you just process a lot of information and interpret this in some way. But often those decisions are quite simple – for example, if X number is higher than X threshold, then green light. You then normally end up automating all of that, once you automate that information then you end up probably building a nice looking UI – so the product team can already check those numbers and say: ‘ok, we’ve got the green light from the maths shenanigans!’ – so I specialised doing that, not so much on the statistics part of things, but on the automation and nice-looking UI part. This eventually became Shiny development, so I joined Ascent (Mango Solutions) exclusively as a Shiny developer.

During my time at Mango, I’ve been developing Shiny – for different companies and different Shiny applications, but all Shiny! This is still a broad term because sometimes you spend a lot of time on the UI part – like designing the UX flow and how the user should interact with the tool, and on some other occasions, you spend time on the data processing part – which is closer to what a pure Data Scientist would do, but it’s part of the job still. I also deliver training on Shiny as well.

You’re hosting the Introduction to Shiny workshop at EARL online this year – what can attendees expect to learn?

I want to explain some basics with this workshops – getting people up and started on Shiny. I also want to sell Shiny! By that I mean, showcasing what you can do with Shiny and what the applications can be used for. I hope that once people are convinced of the advantages of Shiny, then the chapter on how to build your first Shiny app will be even more exciting. So there are two parts – selling Shiny and getting started with simple applications using Shiny.

Why do you think people should use Shiny over other tools?

The main reasons are when you look at what tools or framework you want for developing stuff you usually have to choose between something that’s easy to use or something that is powerful. I believe Shiny is an interesting framework as it’s extremely simple and easy to use for those who might not know about web app development. You only need a basic knowledge of R to use it and to get started pretty quickly. For anyone who wants to get started on web application development, Shiny works because you can start quickly but know that you can invest more and build more complex apps over time.

What is your favourite thing about Shiny?

Really what I said before – it’s flexibility! You can just use R and not ever realise behind the scenes it is using HTML and CSS, but if you really want to (and I do) you can be specific and flex your javascript knowledge. Shiny can have lots of small widgets where you can embed your javascript code – and I think that’s really cool. It has helped me to do unique things in the web app development world.

Thank you Alejandro!

To find out more about Alejandro’s Introduction to Shiny workshop – please view here. The workshop will take place on Monday 6th September from 2 pm-5 pm UK time and will be £90. Profits from EARL online will be donated to DataKind UK.

EARL logo
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The final day of the Enterprise Applications of the R Language Conference will be a day full of presentations from speakers who use R at work. It will be a great opportunity to hear from a variety of industries and how R is helping them in enterprise.

This closing day of EARL will take place on Friday 10th September and will run all day on UK time. The tickets will be priced at £9.99 – as the event is online we have far fewer overheads, and we will be able to donate our profits to DataKind UK.

We are pleased to also announce that EARL has been DICE (Diversity and Inclusion at Conferences and Events) certified and approved. The DICE organisation aims to encourage event organisers to think more about who they put on stage and to improve representation at events.

Agenda highlights

Of course, we are excited about all the talks at this year’s EARL, but we’ve selected just a few to highlight on this blog.

Dr Jacqueline Nolis, Saturn Cloud – Keynote
Jacqueline will be our first announced keynote speaker – she is a data science leader with over 15 years of experience in managing data science teams and projects at companies including DSW and Airbnb. She is currently the Head of Data Science at Saturn Cloud, where she helps design products for data scientists. We can’t wait to hear from Jacqueline’s vast experience of being in the data science field.

Avision Ho, Mettle – Meeting citizens where they R
Avision’s talk sounds like an excellent example of using open-source software to improve citizen access to meaningful information. He will cover specific technical elements of building a robust CRAN package and a mobile-centric Shiny app, as well as good DevOps practices that facilitate standardised and easy collaboration.

Daniel Durling, Bank of England – We are not start-ups!
Daniel’s talk touches on a host of oft-experienced cultural/operational barriers to doing data science in larger organisations, such as making the switch to open-source software and dealing with legacy code. We are looking forward to hearing how Daniel navigated this in the Bank of England.

Adithi Upadhya, ILK Labs – Shiny apps for air quality data analysis – Introduction to network analysis
Adithi is a co-founder and co-organiser of R-Ladies Bangalore and currently works as a Geospatial Analyst at ILK Labs Bangalore. Adithi’s talk will focus on creating Shiny applications to analyse and visualise air-pollution data. With pollution and air quality as hugely topical subjects, it will be fascinating to hear how Adithi and her team are managing the vast amount of data and creating meaningful Shiny apps.

To see the rest of the agenda, please visit our EARL page here. Alongside the presentation day, we are also hosting four workshops from Monday-Thursday (6-9th September 2021): Introduction to Shiny, Package Development in R, Functional Programming with Purrr and Web Scraping and Text Mining Lyrics in R.

EARL logo
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We are pleased to announce that we have selected DataKind  as the chosen charity that the Enterprise Applications of the R Language Conference (EARL) will support in 2021.

Last year when EARL needed to move online, we decided that as our overheads were lower we could donate our profits to charity. As we are online again, we are pleased to be able to do the same this year. We interviewed Suzy East, DataKind’s Community Project Manager, to find out more about the great work they do.

Tell us about DataKind’s mission?

Our mission is to transform the impact of social change organisations by building their capacity to use data science through:

  • Changing attitudes

We want to increase understanding of and trust in data science within the social sector, by showing what’s possible and how data can be used responsibly

  • Providing a safe space to test ideas

We work with organisations to explore what might help them, and introducing them to new approaches and tools

  • Supporting data practitioners

We provide access to peer support networks for data experts in the social sector, and we’re working to ensure the number of data scientists in social change organisations continues to grow

In order to achieve this, we run a number of programmes ranging from our monthly Office Hours, where any social change organisation can receive an hour of free advice on any data-related topic, to our DataDives, a high-energy weekend of exploratory analysis for one to three carefully selected charity partners, to our DataCorps, projects of up to one year where we can build and operationalise a data science tool to help an organisation work smarter.

Since we were founded in 2013, we have worked to understand the social sector’s needs and how we can harness the power of pro bono data scientists to deliver social impact. All of DataKind’s projects are undertaken by pro bono data scientists; we have a core community of around 50 active volunteers and work with several hundred over the course of every year. We are powered by this community of passionate data scientists – including statisticians, data engineers, visualisation experts, developers, designers and project managers – who have contributed over £3 million in pro bono data services through DataDives and DataCorps projects to more than 80 charities. We are now, by far, the most experienced provider of charity data science support in the UK.

Can you give us some examples of the kind of work you have done with social change orgs?

Example: Centrepoint

Centrepoint, a youth homelessness charity, came to their DataDive with a mound of messy local authority data. After much data cleaning, the volunteers created models to show that official government numbers underestimate the number of homeless people by a factor of 10. At that time, official government figures showed that there were 16,000 young homeless people in England. Our volunteers found that figure was more like 140,000. This project was the start of a two-year Centrepoint programme to develop a robust and accurate Youth Homelessness Databank for the entire sector, building on data contributed by charities and local authorities all across the UK.

Example: The Welcome Centre

We worked with the Welcome Centre, a food bank in Huddersfield, to identify those most likely to need extra support, over and above food packages. Four DataKind UK volunteer data scientists and a Welcome Centre trustee embedded a machine learning model in the food bank’s referral system. The model enables advisors to fast-track support to high-need cases. It identifies clients who were likely to become dependent early in their journey, enabling them to get extra support and advice to prevent temporary crises from becoming more permanent. This project was a finalist in the European Data Science Awards 2019 for Best use of Data to achieve Social Impact.

Has Covid affected the type of projects you have worked on?

Covid hasn’t necessarily affected the types of projects we work on, but it has massively impacted how we work. We used to run in-person DataDive weekends of up to 100 people, as well as in-person monthly office hours, volunteer committee meetings and training sessions, and much more! We’ve translated all our events and activities online, and while we miss seeing our wonderful volunteers and charity partners ‘IRL’, it has opened our events up to a new audience that couldn’t attend previously due to the distance, caring commitments or other factors. As a result, we definitely plan to keep holding regular online events in future.

As for our charity partners, it’s made it much more difficult for them to find the time and energy to engage in data projects with us, as many people have been furloughed, and many charities have had to prioritise delivering direct support to their beneficiaries. 

What are your main aims for 2021?

We are about to hold Data4Good festival on May 10-12, an online conference about data in the social sector. We are also currently working on developing an updated strategy for the next three years, with the help of our board of trustees. In terms of projects, we’re looking to deliver three DataCorps projects, along with our regular DataDives. 

If someone is reading this and wants to find out more and ways they can help, where can they go?

If you’re a data scientist or data analyst that wants to get involved, we recommend you start by taking part in one of our DataDive weekends. Take a look at our website where you can read more about volunteering with us, and sign up to our mailing list to hear about future events.

Thank you Suzy! We look forward to working on some events and partnerships with Data Kind UK in the lead up to EARL 2021.

Tickets are now on sale!

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We are excited to announce that the Enterprise Applications of the R Language Conference is online again for 2021.

We’re hopeful that we’ll be back ‘live’ in London for 2022, but for now, we’re delighted to share the agenda for this year’s EARL Conference. We are also pleased to be able to donate all profits to charity once again, and this year the Mango Solutions team have selected Data Kind UK to be our beneficiary.

We are pleased to also announce that EARL has been DICE (Diversity and Inclusion at Conferences and Events) certified and approved. The DICE organisation aims to encourage event organisers to think more about who they put on stage and to improve representation at events.


Four workshops will be hosted every afternoon from Monday 6th September to Thursday 9th September 2021. Each workshop will be hosted by experienced Mango Solutions Data Scientists, who will be able to give you new learnings to take back and action in the workplace.

The workshops will be competitively priced at £90 for each half-day workshop.

Conference day

The EARL week will end on a high with a full day of presentations on the use of R in enterprise – this is a great opportunity to hear from a range of industries and how they are using R to solve issues and to be more productive.

You can view the full presentation day agenda here. The tickets for the presentation day will be £9.99.

In the coming weeks, we will highlight and interview some of the speakers lined up.

EARL online 2021 tickets are now on sale.

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We are pleased to share that the next free and online LondonR meetup will take place on Wednesday 26th May from 4.25 pm (BST).

We will be joined by three presenters who will share their work in R stats, and we will also be hosting LondonR on a new platform!

  • Robert Hickman – Amateur Professional Football Analytics Using R
  • Gary Hutson, NHS – NHSDataDictionaRy – the joy and perils of R package development
  • Alejandro Rico, Mango Solutions – Encrypting with R. From protecting passwords to setting up a blockchain

To join us, register for a place here.







demand forecasting this easter
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Using data to accurately forecast demand for chocolate this Easter

Easter is a significant holiday for many businesses especially within the UK. The holiday period brings an increase to food and drink sales, with Easter being the second most popular period of the year for chocolate consumption. Many Britons book holiday trips in this period as well, making it an important time for the leisure industry.

Data science enables businesses to effectively plan for this busy period. Analysis of historical sales data can be used to predict future demand, allowing businesses to accurately plan stock levels; real-time analysis provides visibility of the state of a product, enabling businesses to quickly resolve issues regarding the manufacturing of products like chocolate bunnies.

Accurate forecasting to match demand

Demand forecasting is a commonly used approach which allows businesses to effectively predict future sales, plan and schedule production, improve budget planning, and develop efficient pricing strategies. Predictive analysis is used to understand and forecast demand over time, helping businesses make well-informed decisions.

Adapting in line with the coronavirus pandemic

The COVID-19 pandemic has brought great challenges within businesses. Easter brings challenges itself with the date of the holiday moving each year, however in 2020, businesses were simply not prepared for the impact of the pandemic. Easter egg sales fell by £36 million with many retailers having to sell lots of eggs at discounted prices. Some retailers were also unprepared for the boom in online sales and were not able to meet demand. On the upside, many businesses are better prepared for this year’s Easter period, with many focussing on online operations. Through demand forecasting techniques and last year’s data, businesses have been able to better prepare for this year’s demand. Many, for example Hotel Chocolat, are offering a limited range of Easter eggs this year.

As well as benefitting the retail and leisure industries, demand forecasting is used by other organisations over Easter. The NHS use forecasting techniques to predict demand and capacity for their services. This has been particularly important during the pandemic. In the January peak, NHS hospitals were caring for over 34,000 COVID-19 patients in England, approximately 80% higher than the first peak in 2020. Demand forecasting and mathematical models are being used to predict hospital bed demands frequently, tailored to specific hospitals, to help the NHS and government plan for future holiday periods such as Easter.

Demand forecasting is an effective approach that is being used by many businesses to plan for this year’s Easter holiday. Data-driven businesses can make well-informed decisions for the future, and as a result many will be better prepared this Easter.

Can we help with any aspect of your demand forecasting? Read our case study to find out how we have helped other companies with this.