It's time for another challenge!
Andy Kriebel is again inspiring us - we're recreating his #MakeoverMonday challenge using the line chart core visual in #PowerBI. Join us for a fun challenge that includes #PBICoreVisuals, #DAX, and a hack!
https://t.co/4LDV6uOahy

Each day should have a #hastag so the catless can join. Here are some suggestions, which can be improved upon!!
#Sinday (focused on the 7 deadly, like Grumpy, Sleepy…Dasher Dancer … oops)
#makeovermonday (self-explanatory),
#TodoTuesday (reveal your ToDo list)
#WackyWednesday (anything goes),
#ThrowbackThursday (if it’s good enough for FB…)
#FryDay (Yup—anything that can be fried), and of course
#caturday retains it’s anchor position (if it ain’t broke don’t fix it).
Who’s in??????

#WoW2023 friends - this week's challenge is one everyone can enjoy! We took inspiration from #MakeoverMonday to create a bar chart and a what-if parameter in #PowerBI. Check out the report to see if you, too, are overcaffeinated!

https://workout-wednesday.com/pbi-2023-w15/

A dot plot for this week's #MakeoverMonday

How much caffeine does your coffee contain?

Data - Which?

Tableau Public -> https://tabsoft.co/3Za7Nhi
#Tableau #dotplot

Updated my #MakeoverMonday #dataviz for week 5 to use a full-page map.

https://data.stefanbohacek.dev/projects/makeover-monday/2023w5

Looks much better.

#nyc #food #map #mapbox

I haven't participated in #MakeoverMonday in a while, so this was a great opportunity to finally use Mapbox on a project.

https://data.stefanbohacek.dev/projects/makeover-monday/2023w5

#data #dataviz #nyc #food #pizza #map #mapbox

#birdhouse on #birdhousemonday needed a #makeover on #makeovermonday :blobbybara:

Hope the Birds will like it

Hi #datafam, here a personal project that I made with data from #makeovermonday (2022).
"Which country gets the most paid vacation days?"

Thanks!

https://www.behance.net/gallery/162024039/Which-country-gets-the-most-paid-vacation-days
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#dataviz #datavisualization #DataAnalytics #vacations #data #worldwide #informationdesign

According to *absolutely watertight, irrefutable #data*, I know Americans better than they know themselves.

I played around with a #MakeoverMonday data set from a couple of weeks ago (plus some self-generated data) this morning, and this is what came out.

#datadon #tableau

https://hotcrossjoin.substack.com/p/do-i-know-americans-better-than-they

Well, my first attempt at a #MakeOverMonday as I continue to learn/play #Tableau

Current thoughts, compared to #QlikView, I like Tableau's simplicity to create a simple visualisation and the Story elements look cool, but need to figure out (learn) calculated fields and its version of Set Analysis.

Also, feels less free than QlikView, but that is probably a lack of knowledge on my part.

Link: https://public.tableau.com/views/MakeOverMonday2022W47/RailroadInfrastructurebyCountry?:language=en-GB&publish=yes&:display_count=n&:origin=viz_share_link

<<RT @sybil_dias: Hurrying my #MakeoverMonday 2019/W6 attempt (#Superbowl /#HalftimeShow ). Simple dataset for this week.
Feedback welcome. Thank you @VizWizBI /@TriMyData

https://t.co/TTtlqatypB https://t.co/KQ1us5lap1>>

<<RT @sybil_dias: #MakeoverMonday '19/W4: slow to post; Corrections welcome; Used defra 2017 (scope 2) conversion CO2e. 2 Charts in 1 viz. Hover over details in chart, and use highlight/scrollbar to see variations in readings by day/time. Thnx @VizWizBI @TriMyData / https://t.co/ICdOB1ecn3 https://t.co/DiHIN5WvDI>>