Naya dataset = nayi kahani 📊🔥 Data analysis feels like solving a thriller puzzle 🤯✨ #DataScience #FunWithData

2021 to Today: Biggest shift from LPC to CPC has been among economic progressives/cultural conservatives. More to come exploring this exciting new dataset I just got. #datalab #chefinhiskitchen #funwithdata #cdnpoli

This morning's #FunWithData inspired by the G-man. I took all lactate test data and all time in zone data for athletes that I have both for and built a linear model that describes the relationship between 3 month zone 1 volume leading up to the test (in seconds) and lactate level at 250 watts. *On a group level* for every additional 50,000s of zone 1/3mo, i.e. ~5hrs per month, lactate at 250W will decrease by ~0.4mmol/L. This value starts to approach AeT at 500,000 seconds of zone 1 (139 hours) in the 3mo leading up to the test. Interestingly, zone 2 volume did not have the same effect.

#Nairobi : final day of our media training series on #AirPollution ! Today we are learning from @JudyNguta how to use data in #airquality reporting. Later, we will do #spcialmedia and story idea development. Loving the energy in the room! #training #mediadevelopment #funwithdata #ejnat20 #ejnattwenty @CleanAirCAC @earthjournalism

Data analysis is like solving a puzzle - but instead of a 'pretty picture', you get actionable insights! 🧩 At HiveDT, we're piecing together the data puzzle to reveal the big picture for your business. Who's up for the challenge? #DataPuzzle #FunWithData #Apple

Excited about the new @kaggle prediction interval competition 'Prediction interval competition I: Birth weight'! 🎉 It's all about reliably predicting interval of a baby's weight based on various factors. Great opportunity to practice and hone your skills in conformal and probabilistic prediction. A great opportunity for honing data cleaning and preprocessing skills too. 🧑‍💻 And here's a quirky one - Father's age listed as 99. Mick Jagger vibes, or is it something else? What's your take? #DataScience #FunWithData #uncertainty #conformalprediction kaggle.com/competitions/pred…

A little #FunWithData today playing around with some of OpenAIs new function... well... functions 😊 Pretty cool... - Get natural language qu from user (me) - Translate natural language to function parameters - Feed parameters to function to pull stats for the user from database. - Build model from that data - Answer the user's question. Looks pretty accurate to me 😊 #SoYoureSayingTheresAChance

Today's #FunWithData Pulling all tests from the database... Even if all other markers of fitness remain the same, the average athlete will lose 0.03 kcal/min of #FatBurning power every year! i.e. the average 60 yo will be burning ~25% less fat than the average 20 yo at a given power, even if they keep the same aerobic fitness! Beyond general fitness, it's critical as we age, to our #MetabolicHealth, that we keep that fat oxidation strong!

A little #FunWithData today... Looking at how much of an influence different factors have on #TrainingResponse (Banister's k1) using a Decision Tree model.... 1/CTL (negative) CTL has the largest influence on training response for most athletes. This is just the nature of diminishing returns, i.e. novices respond more/faster than athletes with a long training history because they're starting from zero. 2/HRV (positive) A high HRV is a good sign that the athlete will get good fitness benefit from a high training load that day. Particularly when paired with the below... 3/TSB (positive) The higher the TSB, the more training response an athlete is likely to get from a given amount of load )of course, it must be <0 to qualify as load, but not too much <0) 4/RHR (negative) When resting heart rate is higher than normal, the athlete's training response is likely to be compromised. 5/Soreness (negative) When soreness is higher than normal, the athlete's training response is likely compromised. For this reason, we should consider each of the above when deciding to load an athlete.

A little #FunWithData this morning taking a deeper look at Nils' training in the lead-up to his 2 Olympic Gold medals for my upcoming chapter... alancouzens.substack.com/ Despite some insane individual sessions, the overall proportion of time working threshold or above was a measly 6%. 90 % of the work was Eazzzy at 60-75% MHR

Subsidence is the sinking or settling of the Earth's surface. When subsidence occurs, the ground level drops, which can have a range of negative effects on infrastructure, buildings, and the environment. In the United Kingdom, most subsidence is caused by the shrinking and swelling of clay-rich soils, which compress when dry and swell up when wet. You might not know this, but subsidence is the second most costly environmental hazard in the UK after flooding. As the ground sinks or swells, the foundations of buildings can shift and crack, leading to structural damage. We can monitor subsidence from satellites with a technique called “Differential Interferometric Synthetic Aperture Radar” (DInSAR). As the satellite passes overhead, it sends out a beam of light towards the Earth's surface and records how long it takes for the beam to bounce back. This tells the satellite how far away the ground is, and can be used to create a 3D map of the Earth's surface. DInSAR takes this a step further by comparing two different measurements of the same location taken at different times. We’ve included some images of subsidence rates over London monitored by DInSAR using Sentinel 1 for 2018 and 2019. A dry summer in 2018 caused considerable subsidence in areas of London, shown in red in the image, whereas a wetter summer in 2019 resulted in lower levels of subsidence. If you want to see how your property/assets/portfolio/business might be at risk from subsidence, get in touch: climate-x.com/spectra. #climatechange #climatescience #finance #science #funwithdata #subsidence #realestate #london

This morning's #FunWithData... The "J" pattern of #TrainingZones Change in #VO2max per hour/mth spent in each zone 3mths before the test. While the bottom of the "J" varies, greatest benefit consistently comes from going very easy or quite hard. #AvoidTheMiddle #Polarized

Friday is here, so let’s have #funwithdata! Fathomer Rhianwen Davies used Fathom’s Global Terrain Data - FABDEM to create this beautiful render of the Welsh landscape in honor of #StDavid’s Day this week. Can you spot your favorite Welsh mountains? 🏴󠁧󠁢󠁷󠁬󠁳󠁿

Global roads data helps better model the role of humans in contributing to global fire risk. Knowing the location of roads helps us predict where fires could start. Full context 👉 bit.ly/3Xid5oZ #climatescience #climatetech #climaterisk #coolstuff #funwithdata

@GaughanSurfing @MikeFirstAlert @wxgarret @NWSJacksonville mild mid-weeks since Dec 16.. cool weekends. #funwithdata

Bubble survivorship lab today. One of my favorites! #FunWithData

Imagine replacing the name of your city with the name of its most “notable people”. Bellow is a screenshot of an interactive database that just do that for a part of Morocco. The database : lnkd.in/e82D-rHD #FunWithData lnkd.in/e56Z2i4u

nytimes.com/interactive/2014… #funwithData

If you fancy some #funwithdata you can check out our interactive map to see how productive your local area is compared to the national average... datawrapper.de/_/OsmEv/