The stm package has a
summary()method for trained topic models like these that will print out some details to your screen, but I want to get back to a tidy data frame so I can use dplyr and ggplot2 for data manipulation and data visualization. I can use
tidy()on the output of an stm model, and then I will get the probabilities that each word is generated from each topic.
I haven’t watched the video yet, but that’s on my to-do list for today.
Instead, we will start with Wickham’s paper on ggplot2. This gives us the basic motivation behind the grammar of graphics by covering what a grammar does for us: “A grammar provides a strong foundation for understanding a diverse range of graphics. A grammar may also help guide us on what a well-formed or correct graphic looks like, but there will still be many grammatically correct but nonsensical graphics. This is easy to see by analogy to the English language: good grammar is just the first step in creating a good sentence” (3).
With a language, we have different language components like nouns (which can be subjects, direct objects, or indirect objects), verbs, adjectives, adverbs, etc. We put together combinations of those individual components to form complete sentences and transmit ideas. Our particular word choice and language component usage will affect the likelihood of success in idea transmission, but to an extent, we can work iteratively on a sentence, switching words or adding phrases to get the point across the way we desire.
With graphics, we can do the same thing. Instead of thinking of “a graph” as something which exists in and of itself, we should think of different objects that we combine into its final product: a graph.
I call this first post the poor man’s literature review. The rest of the series is code- and visual-heavy.
However, as of this week, if you have a company or work in the UK, things just got a whole lot more interesting. The UK government officially released a statement on January 28 which affects “critical industries”. Long story short: if you fall under the classification which seems to be limited right now to energy, transport, water, and health firms, you could be fined up to £17 million ($24 million in US Dollars at today’s exchange rate) in the event of a cyber attack taking you down. It was the WannaCry outages that precipitated the response (as an example, FedEx says WannaCry cost them about $300 million US Dollars). Remember this doozie from British Airways? Also covered under this new Network and Information Systems (NIS) Directive; it’s not just about security, but includes other things like power outages, hardware failure, and environmental hazards.
Read the whole thing.
While all of these error messages point me in the right direction, I’m too lazyto try and remember how each version of SSMS refers to the error location. This becomes particularly problematic when jumping around environments and not being able to use a consistent version of SSMS.
There is one feature that works consistently though that makes navigating to the specific error lines easily.
Click through for that answer. It doesn’t work for dynamic SQL, but it can be quite helpful when it does work.
I was working on a demo for my upcoming Pluralsight course, and I noticed something odd. It used to be that a empty PBIX file was 123 KB, but some point since May 2017, the file size has become 10 (!) KB. So what’s the cause of the difference?
If you rename a .pbix file to .zip, you can crack it open. If we look at two nearly empty files side by side, we can see the difference comes from the data model. In this example, each data model has a single value that I manually entered.
Yet another reason why it pays to keep up to date on Power BI versions.
In this blog post, I’m going to walk you through modifying a Power BI Desktop file with an imported data model to use an external data model hosted in Azure Analysis Services or SQL Server Analysis Services 2017. This isn’t supported by any stretch of the imagination but if you’re in a pinch and have to convert a Power BI Desktop file from an imported data model to Live Query then this may be helpful to you. Also, this method works as of the January 2018 release of Power BI Desktop but there’s no guarantee that this method will work in future releases of Power BI Desktop.
I was inspired to write this blog post after reading this post in the Power BI community forums by odegarun. It’s a great post with some good instructions, but I wanted to provide a clearer walk through as well as validate a couple other things with the process for my customers and anyone else that might be interested.
Check it out with the understanding that this is not a supported operation.
This post is, for the most part, a continuation of Server Audit Mystery 1: Filtering class_type gets Error Msg 25713. In that post I was trying to filter on the
class_typefield / predicate source (i.e. the object, or whatever, that the event is on). The tricky part was that
class_typeis supposed to be filterable on string values such as
Ufor “User Table”,
Pfor “Stored Procedure”, etc. But, the reality is that it has to be filtered using numbers, and that list does not seem to be documented anywhere. Fortunately, I was able to find the list of possible numbers, so all is well with regards to
When it comes to the
action_idfield, however, we are not so lucky. It, too, should be filterable on the string codes that are returned by
sys.fn_get_audit_file. But, just like
class_type, only numbers can be used for filtering. And, like
class_type, that list of numbers does not seem to be documented anywhere. But, unlike
class_type, I cannot find any list of numbers (in SQL Server) that corresponds to the available actions. I did find a list of statements by looking at Extended Events info (since Audits use Extended Events):SELECT * FROM sys.dm_xe_map_values WHERE [name] = N'statement_type';
but it wasn’t the correct list. So, this means that I have to go hunting for these values the even-harder way
Read on for some fun with binary tree search.
In this module you will learn how to use the Pulse Chart Custom Visual. The Pulse Chart can easily display trends in your data and any events that could have causes those trends to occur.
It looks like an interesting way of annotating a data series. Click through for a video demonstration.