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AKAmit Kumardswithamit.hashnode.devJun 6 · 9 min read

Seaborn — Beautiful Statistical Charts with Less Code

When I finished Matplotlib, I felt confident. I could build charts, customize them, and make them look decent. But writing 10-15 lines just to get a basic plot was getting repetitive. Then I discovere

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Ddanieljasmedanieljasme.hashnode.devMay 27 · 7 min read

Exploring TikTok Data with Python: My EDA Approach (Google Advanced DA Certificate Course 2)

This is the second post in my Google Advanced Data Analytics Certificate series. Part 1 covers the initial data inspection (Course 1). This post covers Exploratory Data Analysis (EDA) with Python and

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SBSaachi Badalsaachis-blog.hashnode.devDec 29, 2025 · 9 min read

Visualizing Data — Matplotlib vs. Seaborn

Why Stats Aren't Enough I thought .describe() was enough. It gave me the mean, the max, and the median. But then I learned about Anscombe's Quartet. This is a famous dataset where four different groups of data have the exact same statistical properti...

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PSPratip Sahoointelligenceunbound.hashnode.devDec 29, 2025 · 5 min read

📊 My Journey into Data Visualization with Seaborn— From Plots to Insights

Hey everyone! 👋 Welcome back to my learning journey 🚀This article is not just another Seaborn tutorial. It is a story of how I learned to see data, not just plot it. When I first started data analysis, charts felt like an extra step — something you...

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TSTanishka Singhtanishka-seaborn.hashnode.devOct 19, 2025 · 17 min read

Seaborn : A data Visualization Library

Introduction: Hi there! In this blog, we’ll explore one of the most popular Python libraries for data visualization — "Seaborn". If you’ve ever looked at raw data and thought, “How do I make this understandable?”, then Seaborn is your friend. What is...

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MGMunilakshmi G Jaidevops.hashnode.devOct 8, 2025 · 5 min read

🚀 Day 2: NumPy, Dice & Destiny 🎲

Hello beautiful people 👋I’m Muni — a DevOps engineer who’s been living in the world of pipelines, deployments, and YAML files.But lately, everywhere I look — AI, AI, AI! 😅Everyone’s either training a model, building an agent, or making machines thi...

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JPJidhun Puthuppattujidhun.hashnode.devAug 29, 2025 · 4 min read

Libraries for Data Science: The Building Blocks of Modern Analytics

Data Science may sound like magic, but behind the magic are powerful libraries—pre-built collections of functions, algorithms, and tools that make solving data problems faster and easier. Instead of reinventing the wheel, data scientists rely on thes...

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SDSagnik Devproject101.hashnode.devAug 21, 2025 · 3 min read

Netflix Content Explorer — My First Data Analytics Project

When I started my journey to become an AI Engineer, I knew I had to get comfortable with not just coding, but also understanding data, analyzing it, and communicating results. So, I picked something fun and familiar: Netflix’s global catalogue. It so...

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APAbhilash PSabhilashps.meJul 31, 2025 · 16 min read

Part 6: A Deep Dive into Linear Regression Assumptions

Before diving deeper into machine learning models, it’s critical to understand the assumptions that linear regression rests upon. These assumptions — linearity, independence, constant variance (homoscedasticity), and normality of residuals — form the...

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TTToluwalase Taiwo4c-nexus.hashnode.devJul 17, 2025 · 4 min read

Health Spending vs Life Expectancy: What the Data Really Shows

It started as a simple assignment. The task? Create a joint plot using Seaborn. I went hunting for the perfect dataset and stumbled on one about health expenditure and life expectancy for the year 1970 - 2020. Sounds serious, right? But something abo...