Blog Archives

Creating bar charts with baselines using customised shapes in Plotly

November 24, 2019
By
Creating bar charts with baselines using customised shapes in Plotly

Bar charts are an effective and popular visual to use in reports and dashboard to reveal patterns in the data and difference in groups. In predictive modelling, bar charts can be used to visualise the predicted value such as choice. For example, when given the right data, we will be able to build models to predict which product customers...

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Creating bar charts with baselines using customised shapes in Plotly

November 24, 2019
By
Creating bar charts with baselines using customised shapes in Plotly

Bar charts are an effective and popular visual to use in reports and dashboard to reveal patterns in the data and difference in groups. In predictive modelling, bar charts can be used to visualise the predicted value such as choice. For example, when given the right data, we will be able to build models to predict which product customers...

Read more »

Deploying R Shiny apps using ShinyProxy on Windows 10

November 5, 2019
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Deploying R Shiny apps using ShinyProxy on Windows 10

Background R Shiny is a powerful tool for building data products, from data visualisations to predictive models. Built by RStudio, this package is highly integrated with the RStudio IDE, making it the primary choice for production. Although it is relatively easy to build a Shiny app and make it run on our local machines, deploying the app on the cloud...

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Deploying R Shiny apps using ShinyProxy on Windows 10

November 5, 2019
By
Deploying R Shiny apps using ShinyProxy on Windows 10

Background R Shiny is a powerful tool for building data products, from data visualisations to predictive models. Built by RStudio, this package is highly integrated with the RStudio IDE, making it the primary choice for production. Although it is relatively easy to build a Shiny app and make it run on our local machines, deploying the app on the cloud...

Read more »

Dplyr functions with string

November 1, 2019
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Let’s say we have a simple data frame as below and we want to select the female rows only. df % filter(., gender == "female") ## id gender ## 1 2 female ## 2 4 female ## 3 5 female The filter() function in dplyr (and other similar functions from the package) use something called non-standard evaluation (NSE). In NSE, names are treated as string literals. So just using...

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Dplyr functions with string

November 1, 2019
By

Let’s say we have a simple data frame as below and we want to select the female rows only. df % filter(., gender == "female") ## id gender ## 1 2 female ## 2 4 female ## 3 5 female The filter() function in dplyr (and other similar functions from the package) use something called non-standard evaluation (NSE). In NSE, names are treated as string literals. So just using...

Read more »

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