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Matt Dancho (Business Science)

Sep 17 • 10 tweets • 6 min read

Shiny is a powerful tool that data scientists can use for web apps & production.

But most data scientists struggle.

Here are 7 resources on shiny that helped me.

#rstats #shiny #excel #python

1. The Shiny website

The 1st place to go to learn shiny.

shiny.rstudio.com

2. Flexdashboard website

Flexdashboard combines Rmarkdown & Shiny to make quick apps.

pkgs.rstudio.com/flexdashboard/

3. Shiny Widgets gallery

See dozens of example reactive widget input / outputs for shiny

shiny.rstudio.com/gallery/widget…

4. shinyWidgets by dreamrs

Advanced & customizable reactive widgets that can really take your shiny apps to the next level

dreamrs.github.io/shinyWidgets/i…

5. HTML Widgets

Interactive visuals for shiny apps

htmlwidgets.org/showcase_leafl…

6. Shiny JS

Makes it easy to add JavaScript actions to your shiny apps.

deanattali.com/shinyjs/

7. Bslib

Upgrade shiny From Bootstrap 3 to 4 or 5 and makes it easy to make custom themes.

rstudio.github.io/bslib/

And if you want all of these 7 R packages plus 93 more in one consolidated #cheatsheet, download my ultimate #R cheat sheet.

business-science.io/r-cheatsheet.h…

One last resource.

If you've been struggling to learn R, I’d like to help.

I put together a free R webinar that consolidates the 10 secrets that helped me in my career.

learn.business-science.io/free-rtrack-ma…

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More from @mdancho84

Matt Dancho (Business Science)

@mdancho84

Sep 14

TODAY. I'm excited to share 2 years of research + 6 software packages that went into Time Series Analysis...

And it's not what you think... 🧵

#rstats #datascience #timeseries #python #excel

I won't be talking about ARIMA.

Or, focusing on stationarity.

And, I most certainly will NOT be talking about:

1. Prophet

2. Exponential smoothing

3. Holt winters

4. Time series decomposition

5. OR any other "common techniques"

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Matt Dancho (Business Science)

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Sep 14

When it comes to Time Series, colleges and universities have it all wrong.

A time series thread 🧵

#rstats #excel #python #timeseries

Universities are stuck in the past, teaching ARIMA.

But the cold reality is that ARIMA is NOT winning time series competitions & ARIMA is NOT helping companies solve BIG forecasting problems.

To be frank, ARIMA is too slow.

When you use ARIMA, you fall into a trap. You think, hey, this is what they're teaching me...

It must be good, right?

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Matt Dancho (Business Science)

@mdancho84

Sep 12

Time series analysis is getting...

EASIER!

Here's a quick thread. 🧵

#rstats #excel #python #timeseries

Time series analysis is getting EASIER!

New tools are being developed...

1. #Timetk for time series data wrangling + data viz

Think if this little gold nugget like dplyr + ggplot2 for time series.

Yep, you can slice & dice that time series.

And, get quick visuals that make your boss cry tears of joy 🥲

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Matt Dancho (Business Science)

@mdancho84

Sep 11

The most important skill in time series analysis isn’t forecasting.

It’s visualization.

Here's why in this thread. 🧵

#datascience #rstats #excel #timeseries

90% of data scientists will model a time series like it’s a machine learning problem.

Apply an algorithm. Tune it. Reduce RMSE.

But I’d argue that visualization will help even more.

Here's how visualization helps.

1. You’ll see the shape of the series.

2. You’ll gain context for the business scenario.

3. And you’ll be able to see whether or not a forecast makes sense.

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