Hey! This is TypeErrorDev 🚀 Self-taught software engineer on a mission! Addicted to data analysis and databases. 💻 Proficient in JavaScript, ReactJS, Python, and SQLite. Always exploring new tech and solving problems. Let’s dive into the world of code and data together! #CodeNewbie #DataDriven

This is the president, btw...This is who yall voted for

When the IT department responds to your ticket with “Hey, here’s the admin permissions you requested to get your App published to the SharePoint Tenant” Today’s a great day 💪🏾

What exactly has the Vice President actually done this term? 🤔

I’m sorry, but CarPlay for Apple/Android is just ugly af..clunky, laggy and just boring

It’s funny how the public thinks that the US military will be flying through the public airports to a combat zone if there’s a call for mass deployment of ground forces somewhere 😂

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Imagine being @carmeloanthony and being confused for Karmelo Anthony on social media 👀

One React concept that clicked for me. Components should do one job well. Instead of building one giant component, break your UI into smaller pieces: Components → Dashboard → UserCard → TransactionList Smaller components are easier to understand, reuse, test, and debug. If you're learning React, this concept makes a HUGE difference. What React concept finally “clicked” for you? #ReactJS #JavaScript #WebDevelopment #Coding

what happened to spaces?

whens the last time you built something with just HTML, CSS and JS?

anyone use @Plaid and able to share what their price point is per "item" connected?

Does anyone know what Plaid's paid tier pricing is per "item" connected?

I’m waiting for the first female to declare for the @NFL draft

All this slow playing with Iran…. Enough foreplay already

Might take a shot at a Kanban board aimed at parents/scheduling. Thinking a mix of like Trello calendar with the conflict analysis of the outlook scheduling assistant 🤔 Obv this will be used to just expand my knowledge, but I figure it could be useful to expand my knowledge on drag and drop

Is your Python script crashing on large datasets? 🛑 Stop letting default Pandas datatypes hog your RAM! Downcasting numeric types and using category for strings can instantly slash your memory footprint by 80%+. df['Age'] = df['Age'].astype('uint8') Have you checked your DataFrame memory usage lately? 👇 #Python #Pandas #DataAnalytics #DataScience #BigData

Summary statistics can lie. 🛑 Relying only on Mean, Variance, and Correlation without plotting your data is a huge mistake. Anscombe’s Quartet shows 4 datasets with identical stats but wildly different structures. The Datasaurus Dozen takes it even further! 🦖 Do you look at your plots before you analyze your stats? 👇 #Python #EDA #DataAnalytics #DataVisualization #StatsLie

Basic df.groupby().mean() is day one stuff. To level up, you need to master window functions and .transform(). Calculate running totals, moving averages, or group ranks without collapsing your DataFrame shape. 🚀 New Column (running total):df['Run_Total'] = df.groupby('Reg')['Sales'].transform('cumsum') Are you still aggregating when you should be transforming? #Python #Pandas #DataAnalytics #DataScience #CodingSkills

Most raw data is structural chaos. 🛑 If your DataFrame has columns named Q1_Sales, Q2_Sales, etc., it’s Wide format (Untidy). To analyze it, you must reshape it. 💡 pd.melt() converts Wide ➡️ Long (Tidy Data), making visualization libraries happy. Which format is easier for your charts?👇 #Python #Pandas #DataAnalytics #DataVisualization #TidyData