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The first important step of a data analysis workflow is to make sure that everything about your data “makes sense”. The {diagnose} function from {dlookr} 📦 provides a detailed data diagnosis report that makes this step easy! 🔍 https://t.co/UoUEdrfUTU #rstats #DataScience https://t.co/eVxrpd0rjc
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Pie charts provide an informative but imperfect way to visualize categorical data, but squared pie (or waffle) charts overcome some of these imperfections. The {waffle} function from the eponymous 📦 easily produces them 🧇 https://t.co/OxtCuCMhHF #rstats #DataScience https://t.co/1ui2OqHJ8k
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#rstats tip of the day: The tayloRswift package from @adastephenson now offers a ggplot2 palette for Red (Taylor's Version) https://t.co/WhDH5dcfvA https://t.co/NPRehrUlxg
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My new map shows the % of female researchers in Europe, according to UNESCO data. Link to the data source is in the map just below the legend. 👩🔬 #women #science #womenintech #rstats #maps #dataviz #DataScience https://t.co/HB9ThI0SoV
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📚 R for Data Science 👤 Hadley Wickham @hadleywickham, Garrett Grolemund @StatGarrett 🔗 https://t.co/o8y97kSYR5 #rstats #datascience https://t.co/DEjUpcnQiT
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A population density map of long, slinky Chile. Took a bit of time to find an angle I like. #rayshader adventures, an #rstats tale https://t.co/ulU36V34tw
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📚📊 Data Visualization with R 👤 Robert Kabacoff @kabacoff 🔗 https://t.co/XjomFm3k4g #rstats #datascience
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Sometimes you may wish to sample only a portion of the data. The {slice} function family from {dplyr} 📦 provides helpers to do so ✂️ https://t.co/4tt17FnvnM #rstats #DataScience https://t.co/9e8pS7KjFn
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The most beautiful Table 1 I've ever made 😍 Thanks to modelsummary by @VincentAB #dataviz #rstats https://t.co/6uJsVEmHiI
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I mapped forest cover in Europe on the municipality level using Copernicus satellite data 🌳🌲. Enjoy the greenery and freshness from afar! #forests #nature #dataviz #DataScience #BigData #rstats #maps https://t.co/m73ivLL8Ub