A Fine Slice Of SQL Server
Martin Schoombee needs a calendar:
It’s pretty sad that we don’t have a built-in calendar visualization in Power BI, and the custom visuals in the marketplace don’t have everything I need/want for my own internal reporting…so I decided to experiment a little and see how close I could get with the standard graphs that are available.
Read on to see how close Martin could get. It’s actually more calendar-looking than I would have expected, though also frustratingly limited.
Comments closedDian M. Fay has an update to pdot:
A couple years ago, I wrote about exploring a running database by plotting relevant subsets of the foreign key relationship graph in dot and piping the resulting images directly to the terminal. Things have progressed since then:
Read on to see what’s changed, including support for displaying trigger relationships.
Comments closedErik Svensen gets things organized:
This might be the default way of doing it but if you always want the chart to be sorted by a particular measure even though you are showing another measure then you can use this workaround. You should of course inform the user about the chosen sort order for instance in the subtitle or similar.
Click through to see what Erik has in mind.
Comments closedSteven Sanderson switches up a visual:
When it comes to data visualization in R, the
par()function is an indispensable tool that often goes overlooked. This function allows you to control various graphical parameters, unleashing a world of customization possibilities for your plots. In this blog post, we’ll demystify thepar()function, break down its syntax, and provide you with hands-on examples to help you create stunning visualizations.
Click through to check it out. My loyalties definitely lie with ggplot2 for static visual development in R but it’s definitely not the only way to get images to look the way you want them.
Comments closedSteven Sanderson texts up a plot:
As a programmer, you’re well aware of the importance of data visualization. A well-crafted plot can convey complex information with clarity and impact. In R, creating stunning plots is a breeze, especially when you’re armed with the versatile
text()function. This little gem allows you to add custom text to your plots, enabling you to annotate and highlight essential details. Let’s dive into the world oftext()and uncover its syntax and potential through some hands-on examples.
I’m also a big fan of geom_text_repel() in ggplot2’s ggrepel library. It is by no means perfect but it does do a good job of not overlapping important visual features like plotted lines.
Stephane Laurent writes some code:
I implemented the framed closed curves exposed in this blog post, in Julia and R. In fact it is useless with R, because the rgl function
cylinder3dis faster and better.Here is the Julia implementation:
Click through for that code, as well as equivalent R code. H/T R-Bloggers
Comments closedRebecca O’Connor builds a map:
Power BI can leverage Geospatial data from snowflake with my favourite map visual – Iconmap – https://www.icon-map.com/ . Icon map can render points, polygons and linestrings using ‘Well Known Text’ format (WKT).
Snowflake supports converting geospatial datatypes to WKT. Not only this, Snowflake has the capabilities to perform the Engineering and analytical needs for Geospatial analysis without using any other tool. And the results can be visualised in a variety of medias such as Tableau, Hex, Carto or even a Custom built Streamlit application. I have written a Streamlit blog on this very recently.
Click through for information on how to get the data shaped in a way that Power BI likes.
Comments closedLine charts are another common chart type in reporting. They show time series or continuous data along an x-axis (typically). Like bar charts, they are easy to read and understand for most people. There are different variants and formatting for line charts to use them effectively.
Click through for templates and plenty of great examples.
Comments closedKurt Buhler builds a series of charts from the Power BI bar chart visual:
These are only a few examples; there are many more. Knowing how to create these different bar chart variants is important to address these use-cases. While many of these visuals can be created custom in Deneb or from SVGs, you can also create them in the core visuals. However, it’s important to know the limitations of the core visuals in Power BI, and when this “Macguyvering” of the core visual formatting settings goes too far.
Kurt gives us a template (in pbib format) and explains various options we have around customizing visuals, not just taking what’s built in.
Comments closedMike Cisneros goes bar-hopping:
Let’s take a closer look at that extra-tall bar chart. I came across a graph like this one when working with a recent client. They created a visual to compare the quarterly sales revenues for each of 25 different sales associates against their individual sales targets.
Mike then gives us two routes to improving the quality of this visual, one which maintains the bar chart style and one which replaces it with a Cleveland dot plot.
Comments closed