One of the "purer" ways to measure hitter talent is probably looking at performance on in-zone fastballs, so here's a scatterplot of Z-Contact% and Swing . Elly, Caglianone, Adley, and Dingler are good standouts... Devers and Arozarena are bad standouts

Mau bikin visualisasi stats pemain kayak pizza chart, radar, scatterplot atau mau ngecompare pemain sekalipun juga bisa. Footys Lab udah bisa diakses secara gratis. Boleh minta kritik dan sarannya sekalian teman-teman. Thank you!🙏 footys13.github.io/FootysLab…

Liberatore: Acceptable for 60 pitches McGreevy: Cautiously optimistic May: Gone Pallante: Alright now, hurt me before Leahy: Not a starter, ~14 ERA after 3rd inning Dobbins: Scatterplot You cannot be a seriously competitive team when this is the state of your rotation #STLCards

Day 17, Today I Started Seaborn, and learnt about scatterplot which is used to visualise the relationship between 2 continuous values. And Distribution Plot that help visualise properties such as deviation and they are rugplot, displot and kdeplot

WTF are you even talking about? The scatterplot clearly shows Palestinians are genetically identical to Jordanians, Syrians and Saudis. 🤦🏻‍♀️

Ashkenazi and Sephardic Jews are not in the European cluster. If they were genetically European, they’d fall squarely in that cluster. They don’t. Do you understand how to read a genetic scatterplot? I think you don’t. In fact I know you don’t.

Where is the source for YOUR scatterplot? Not the one I posted because the one I posted shows Ashkenazis are genetically closer to other Jews than Eastern Europeans. I want the source for this.

No no no. I was asking for the source of the scatterplot posted by the person who responded to my scatterplot.

I just explained to you that I tried. There’s a little button in the corner of every post. I asked Grok what the source. Grok said that scatterplot doesn’t come from a single solitary source but rather is a composite of many different similar scatterplots. The person I responded to posted it. It’s not unreasonable to ask where he got it.

Last 15 appearances he’s been nails, 1.something era. No runs allowed in 7 outings. Suppose he was due 🙂‍↕️ Leahy had a 13.09 ERA after the 3rd inning coming into tonight and added to that tally. He has to be in the pen. “Taxed bullpen” with a long guy who can’t get through 4 innings but they just seem adamant that Leahy is a starter. Putting him in the pen fixes so many issues. At this rate just put Mautz, Matthews, or ride out Dobbins’ scatterplot starts and use Leahy/Fernandez in the pen.

Had the sudden urge to make a custom scatterplot, and what else could this lifelong New Yorker possibly make right now but this? 🤞🤞🤞 (p.s., 𝘳 = -0.16)

That's an excellent question. You could ask Claude in Excel using any model to perform a correlation analysis by generating a scatterplot across two datasets. You'd have to specify a column to join on, that may or not be able to be joined. For instance, figuring out how to line up monthly measurements against daily measurements would be very difficult, but in Correlation Studio you can simply specify your join keys in the Dataset Wizard's Column Editor and coerce them to Date. But researchers need more than that. They need to find & harvest datasets. They need scale. They need sample sizes, filtering rules and discovery capabilities. They need Correlation Studio for that. For instance, you wouldn't be able give Excel & Claude a hundred files with millions of rows & gigabytes of data & have them perform full-matrix correlation analysis across every column pair to discover previously unseen correlations, which is where we excel. Depending on your dataset sizes column counts that's potentially many gigabytes of output, most of it noise. Not something you can work with in Excel. For the Correlation Studio rollout, building Corrie's corpus, I took 20 commodity datasets and combined them with each other, but also dozens of other leading economic indicator datasets like S&P 500, GDP, price of oil, etc. It was around 50 files total. That generated 2.3K Experiments yielding 23K Discoveries that are all live on the website in just a few clicks. The Discoveries were also filtered by Experiment rules that specify an absolute r threshold, sample size and filtering requirements ensuring empty or invalid results are not included. Each one lives an interactive scatterplot or line-chart on the web, with dataset drill-down using a simple mouse lasso - even plotted on a map if there's geospatial data. Correlation Studio also adds best-fit regression formulas Lead/Lag analysis & Rolling Regression charts instantly. One more click gets you Granger Causality and AI Analysis that takes all of the column and other dataset attributes into consideration, as well as the time frame of the datasets, to produce analysis that Excel Claude cannot provide. I've added some images and a live link for reference. Correlation Studio provides for the acquisition of the data with its Remote Dataset Wizard, mapping of column metadata for datasets, Experiment creation & Discovery output. Building on top of that, it provides a mechanism to compile all of your work into a Portfolio that also lives on the site where users can Like, Rate and Comment on every part of it. It's like combining Excel Claude Powerpoint SQL Cloud Storage Python and Sharepoint into a web app for discovering correlations. That's what we did. Add our Remote Dataset Wizard on the front and Corrie our chatbot on the back and you have a unique value proposition. There's nothing else like it on the market. correlationstudio.com/welcom…

lo que los gordos nerd que tenemos que cambiar nuestro autito viejo necesitamos es un scatterplot con lasso filter para poder ver todos los avisos en una interfaz digna que no sea un adefesio inmoral diseñado por el ex argentino ahora uruguayo para engañarnos y esquilmarnos Digo

Still a work in progress. I have 20 years of calls. Continue to add to & refine my CIE🤡Show Ineptitude Scatterplot. 😏

3️⃣ Data visualization 📊 Converting that cleaned data into visual forms using Python library-Matplotlib. Like ? Line chart, bar graph, scatterplot, heat maps, pie plot 📈 This gives clear idea on how to increase customer retention or which series is performing on top 🎯

hello tej seth i have a question is there a specific reason why you stopped posting epa scatterplot graphs or is this merely coincidental thank you