Explore showcase demonstrations and community-contributed examples of AI workflows and automations.
20250902_182311_fi...
csv
As a sales manager, I used to rely on gut feel to judge how healthy the pipeline was—and that didn’t always end well. This tool breaks it all down for me: how long deals sit in each stage, what our win/loss ratios look like, and how much revenue we can realistically expect. It’s like finally having a dashboard that tells me what’s stalling, what’s working, and where to focus to hit targets.
20250901_171542_fi...
md
I can’t tell you how many times a “quick” CSV export turned into a headache because the rows were misaligned or cells shifted out of place. Instead of spending half a day manually repairing the file, this tool rebuilds the rows for you and snaps every column back where it belongs. Now I can get straight to analyzing the data instead of wrestling with broken spreadsheets.
This candlestick chart shows Apple’s stock price movement over time using open, high, low, and close data from a real financial dataset. I used historical data from https://raw.githubusercontent.com/plotly/datasets/master/finance-charts-apple.csv to visualize daily market trends and highlight price volatility. It’s a simple way to see where the stock opened, how it moved throughout the day, and where it closed—perfect for anyone analyzing trading patterns or financial behavior.
This annotated heatmap gives a side-by-side comparison of universities from around the world based on their scores in Teaching, Research, and Citations. Each cell shows not just color intensity but also the actual score, making it easy to spot strengths and weaknesses by category. Great for anyone exploring how different institutions stack up across key academic performance metrics.
20250826_130303_fi...
If you’ve ever pulled a lead list from your CRM, you know it’s rarely clean — duplicates, messy names, weird phone numbers. I used to waste hours cleaning that up before I could even upload it to our tools. This script fixes all of that: it deduplicates leads, standardizes names and emails, formats phone numbers properly, and gives you a clean list that’s ready to go.
20250901_182143_fi...
I used to struggle to see how my marketing campaigns were doing because all the data lived in different places and the metrics were all over the place. This dashboard changes that. It pulls everything together, uses consistent definitions for key numbers, and shows you things like how much you’re spending, how many clicks and conversions you’re getting, and your ROAS. Now it’s easy to see what’s working and where you should focus your energy.
20250901_100818_fi...
Hey everyone, if you're part of a CX or Research team like me, you know how messy clean surveys can get. Incomplete answers, inconsistent wording, and tiny variations—like “Yes,” “yes,” or just “Y”—can totally mess up your results. This tool automatically cleans all that up. It filters out half-filled responses, standardizes text, and normalizes those little answer differences so everything’s uniform (so all your “yes” variations just become “Yes”). What you end up with is a solid, consistent dataset that’s ready for real analysis—no extra elbow grease required.
This heatmap explores the relationship between different Netflix content attributes, like release year, content type (movie or TV show), and various content ratings. It’s a quick way to spot patterns—for example, how certain ratings are more common in either movies or TV shows, or how the release year correlates with content types. The color gradient helps highlight stronger or weaker correlations at a glance.
I used the Berkeley Earth surface-temperature dataset to map out how a single location’s average temperatures swing through the year. Each bar radiating from the center represents a month—longer bars mean hotter months, shorter ones mean cooler months—so you can see the full seasonal cycle at a glance. It’s an intuitive way to spot how sharply (or gently) a place moves from winter chill to summer heat.