When working with data which is a result of json-data converted to a list of lists of lists of lists … (you know what mean ;-)) I often want to convert it a data.frame.

Unfortunately there’s often a list in the source data which is unnamed. Or the list in one row is longer than the one in another row. So converting it straight forward into a data.frame or tibble fails with the error message Tibble columns must have compatible sizes.

So what to do? Just leave lists as values in the cells of the data.frame.

Snowflake is a well known cloud-based database. It’s used for Data Warehouses and other big data applications.

In this article and the following ones I want to show how to setup and access a snowflake database from various clients such as R, Tableau and PowerBI.

So let’s start using R.

The “grammar of tables” is used to build tables with the R-package gt. Thomas Mock published an extension package called gtExtras which is used all over in tweets about NFL and Fantasy Football such as win and loss history information in a table.

gt follows a similar philosophy such as ggplot2. On the one hand there is the data to be shown (in a table resp. a plot). On the other hand there is the description how to visualize the data: What is the table header, are there subheaders, how are the cells grouped and formated?

So it was time to check out gt. During my tryouts I came across one demand I haven’t found an in-built solution for: I wanted to format a column with respect to the value of another column. Here’s the way I solved it:

Last weekend I fixed some issues with my R-package piwikproR

The new version 0.3.1 is now available at CRAN

So let’s have a look at the changes:

Lately I tried to visualize an hierarchy with Tableau Desktop. The problem was that the hierarchy had a variable depth because it was tree-based. Each row had an id and a parent_id. Normally hierarchies in Tableau are defined by pulling some fields together, such as product category, product group and product id.

Handling tree-based hierarchies seems to be a lot more complex. I found a plugin at https://github.com/tableau/extension-hierarchy-navigator-sandboxed but this only works online.

So I asked myself how I can handle this using R. I found the R-package data.tree at https://github.com/gluc/data.tree. I want to describe how I use this package to preprocess my data.