#R Data Visualization Examples

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#R Data Visualization Examples Reel by @chartosaur (verified account) - Just because you can make your chart look unique, doesn't mean you should. A good data visualization is about clarity, not just creativity. When every
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@chartosaur
Just because you can make your chart look unique, doesn't mean you should. A good data visualization is about clarity, not just creativity. When every element - color, font, and shape - works against readability, you're not improving the story, you're burying it. Radial bar charts, for example, may look visually compelling, but they aren't always the best tool. While they do okay in displaying cyclical data, such as seasonal trends or annual sales patterns, their complexity can make your point harder to understand in other contexts. #Charts #Presentation #Viz #PPT #Excel #Graph #Consulting #Mckinsey #Bain #BCG #Vizualization #Slides #Chart #Graphs #Deck #GoogleSlides #StackedBarChart #BarChart #Education #Data #Anchoring #Likert #RadialChart
#R Data Visualization Examples Reel by @thephdstudent (verified account) - Data visualisation book recommendation for anyone who wants to turn data into interactive stories, not just static charts 📊🌍💻 ✨ Teaches you how to
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@thephdstudent
Data visualisation book recommendation for anyone who wants to turn data into interactive stories, not just static charts 📊🌍💻 ✨ Teaches you how to move from spreadsheets to web-based visualisations ✨ Covers tools like Google Sheets, Datawrapper, Tableau Public, Chart.js & Leaflet ✨ Perfect if you want to communicate data clearly — even without heavy coding ✨Open-source so freely available online 📌 Hands-On Data Visualization: Interactive Storytelling from Spreadsheets to Code — Jack Dougherty & Ilya Ilyankou 💭 Summary: This book shows you how to clean, analyse, and visualise data using practical tools — starting with spreadsheets and moving into customisable web-based charts and maps. It’s especially useful if you want to share your work online and make your data interactive, not just informative. If you’re learning data science, bioinformatics, or just want to present your work better, this is a great place to start 🤍 📌 Save this for later — I’ll be sharing more recommendations soon. #womeninstem #datavisualization #datascience #bioinformatics #tech
#R Data Visualization Examples Reel by @jessramosdata (verified account) - Comment "project" for my full video that breaks each of these projects down in detail with examples from my own work. If you're using the Titanic, Ir
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@jessramosdata
Comment “project” for my full video that breaks each of these projects down in detail with examples from my own work. If you’re using the Titanic, Iris, or COVID-19 dataset for data analytics projects, STOP NOW! These are so boring and over used and scream “newbie”. You can find way more interesting datasets for FREE on public data sites and you can even make your own using ChatGPT or Claude! Here are the 3 types of projects you need: ↳Exploratory Data Analysis (EDA): Exploring a dataset to uncover insights through descriptive statistics (averages, ranges, distributions) and data visualization, including analyzing relationships between variables ↳Full Stack Data Analytics Project: An end-to-end project that covers the entire data pipeline: wrangling data from a database, cleaning and transforming it. It demonstrates proficiency across multiple tools, not just one. ↳Funnel Analysis: Tracking users or items move from point A to point B, and how many make it through each step in between. This demonstrates a deeper level of business thinking by analyzing the process from beginning to end and providing actionable recommendations to improve it Save this video for later + send to a data friend!
#R Data Visualization Examples Reel by @excel_booster - 📊 Data Visualization Cheat Sheet | Complete Guide to Charts & Graphs In this guide, you'll learn about: ✔️ Gantt Chart - Track project timelines and
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@excel_booster
📊 Data Visualization Cheat Sheet | Complete Guide to Charts & Graphs In this guide, you’ll learn about: ✔️ Gantt Chart – Track project timelines and scheduling ✔️ Bar Chart – Compare categories easily ✔️ Highlight Table – Identify highs and lows quickly ✔️ Bubble Chart – Compare multiple variables visually ✔️ Line Chart – Show trends over time ✔️ Tree Map – Display hierarchical data ✔️ Scatter Plot – Find relationships and correlations ✔️ Pie Chart – Show proportions and percentages ✔️ Box & Whisker Plot – Understand distribution and outliers ✔️ Maps – Visualize geographic data ✔️ Waterfall Chart – Track cumulative values ✔️ Bullet Chart – Measure performance vs targets This cheat sheet is perfect for: 🎯 Data Analysts 🎯 Business Analysts 🎯 Excel & Power BI Users 🎯 Tableau Beginners 🎯 Students & Professionals #DataVisualization #DataAnalytics #ChartsAndGraphs #BusinessAnalytics #ExcelTips PowerBI Tableau DataAnalyst DashboardDesign AnalyticsLearning ExcelBooster
#R Data Visualization Examples Reel by @datapatashala_official - R vs Python: Key Differences R: - Focuses on data analysis and statistics - Used primarily by academics and researchers - Powerful data visualization
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@datapatashala_official
R vs Python: Key Differences R: - Focuses on data analysis and statistics - Used primarily by academics and researchers - Powerful data visualization with libraries like ggplot2 - Runs on the RStudio IDE - Steeper learning curve initially Python: - Versatile language used for deployment and production - Favored by programmers and developers - Strong data manipulation capabilities with pandas - Integrates with machine learning libraries like TensorFlow - Smoother, more linear learning curve Both are robust data analysis tools, but have different strengths and user bases. Choosing between R and Python depends on your specific needs and background. #DataScience #Programming #RvsPython #DataAnalysis #Statistics #AcademicResearch #Developers #MachineLearning #DataVisualization #RStudio #Python #DataManipulation
#R Data Visualization Examples Reel by @kertutenso (verified account) - 1️⃣ "R for Data Science" by Wickham et al. is widely recommended across stats forums as one of the best books to learn hands on R programming. The is
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@kertutenso
1️⃣ “R for Data Science” by Wickham et al. is widely recommended across stats forums as one of the best books to learn hands on R programming. The is available online for free at www.r4ds.hadley.nz 2️⃣ HarvardX Data Science R Basics is free to audit assumes no prior knowledge and teaches you foundational programming concepts and operations (it doesn’t get into statistical modeling yet). 3️⃣ “An Introduction to Statistical Learning with Applications in R” by James et al. can be a little bit more technical and advanced (as it actually covers statistical topics), but comes with great real-life R coding examples.The PDF of the book is available online for free at www.statlearning.com 4️⃣ www.rscreencasts.com has a long list of screencast videos by data scientist David Robinson where he shares real-world examples of live data analyses in R, including how to approach analysis, what packages and methods he uses, as well as general R tricks and tips. 5️⃣ If you prefer more interactive learning, you might enjoy swirl (swirlstats.com) that teaches you R programming interactively inside the R console, no reading books or watching courses required. ❓Any other good recs? Drop them in the comments! #rprogramming #rstudio #datascientist #womenintech #womeninstem
#R Data Visualization Examples Reel by @softwarewithnick (verified account) - Top 3 data visualization packages 🤔 1️⃣ https://matplotlib.org 2️⃣ https://seaborn.pydata.org 3️⃣ https://ggplot2.tidyverse.org Being able to vis
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@softwarewithnick
Top 3 data visualization packages 🤔 1️⃣ https://matplotlib.org 2️⃣ https://seaborn.pydata.org 3️⃣ https://ggplot2.tidyverse.org Being able to visualize and tell the story is a key component of being a data scientist. With these 3 packages you can pretty much create any plot you can think of! Not only that, but these packages aren’t actually that bad to learn! There are many other packages out there for data visualization as well, but these are my 3 favorites! Drop a follow for more coding tips 🎯 #code #coding #datascience #tech #python
#R Data Visualization Examples Reel by @thedataevangelist (verified account) - Dive into the captivating world of data visualization with 'Seeing Theory.' 🌐 Explore the art and science of visualizing data, making numbers come
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@thedataevangelist
Dive into the captivating world of data visualization with ‘Seeing Theory.’ 🌐 Explore the art and science of visualizing data, making numbers come alive! 📈✨ Follow @thedataevangelist for more such content #dataanalyst #datascience #datavisualization #visualizations
#R Data Visualization Examples Reel by @priyal.py - rag evaluation #datascience #machinelearning #learningtogether #womeninstem #progresseveryday #tech #generativeai #ai #consistency
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@priyal.py
rag evaluation #datascience #machinelearning #learningtogether #womeninstem #progresseveryday #tech #generativeai #ai #consistency
#R Data Visualization Examples Reel by @equationsinmotion - The Secret to Understanding Correlation Coefficients #statistics #math #datascience #correlation #Manim Master the Pearson Correlation Coefficient in
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@equationsinmotion
The Secret to Understanding Correlation Coefficients #statistics #math #datascience #correlation #Manim Master the Pearson Correlation Coefficient in seconds! This video breaks down the complex world of statistics by visualizing how 'r' values change across different scatter plots. From strong positive correlations (+0.95) to strong negative correlations (-0.95), you will see exactly how data points align with the line of best fit.
#R Data Visualization Examples Reel by @alinethesoybean - Learn how to use RStudio and analyze data for free online with the University of Toronto's free online course! 🔗Link for the course is in my bio! ⚠️
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@alinethesoybean
Learn how to use RStudio and analyze data for free online with the University of Toronto’s free online course! 🔗Link for the course is in my bio! ⚠️I don’t know if you get a certificate #Rstudio #GIS #geospatial #dataanalysis #environmentalhealth #publichealth
#R Data Visualization Examples Reel by @statcsmemes - staying true to my username . . . Statistics is the foundation of data analysis and inference across many disciplines. In hypothesis testing, statist
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@statcsmemes
staying true to my username . . . Statistics is the foundation of data analysis and inference across many disciplines. In hypothesis testing, statistics provides the rigorous framework for using sample data to make objective decisions about a population. This involves formulating a null hypothesis (H_0) and an alternative hypothesis (H_a), calculating a test statistic (like t-score or Z-score), and determining a p-value to assess the statistical significance of the evidence against H_0. In Machine Learning (ML), statistics is essential for tasks like Exploratory Data Analysis (understanding data distribution and variability), feature selection, and especially model evaluation (using metrics, confidence intervals, and hypothesis tests to compare models and validate predictions). For Time Series Analysis, statistical methods like ARIMA (Autoregressive Integrated Moving Average), moving averages, and autocorrelation are used to decompose data into components like trend, seasonality, and residual, enabling the identification of underlying patterns and robust forecasting of future values. Beyond these, statistics plays a crucial role in areas like experimental design, quality control, and risk assessment by quantifying uncertainty and providing reliable, data-driven conclusions. This is not my content. All credits to the owner. Dm for credit / removal . #math #statistics #computerscience #stats #cs #mathmemes #mathedits #statsandcs

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