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May-2021.Rmd
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# May 2021 {-}
## May 1 {-}
<blockquote class="twitter-tweet"><p lang="en" dir="ltr">In {ggplot2}, the missing values are removed by default, but sometimes we may wish to visualize them to see if there is a pattern in missingness.<br><br>The {geom_miss_point} function from {naniar} 📦 offers exactly this functionality 🔍<a href="https://t.co/zJrYSMhnX4">https://t.co/zJrYSMhnX4</a><a href="https://twitter.com/hashtag/rstats?src=hash&ref_src=twsrc%5Etfw">#rstats</a> <a href="https://twitter.com/hashtag/DataScience?src=hash&ref_src=twsrc%5Etfw">#DataScience</a> <a href="https://t.co/IrXFHoLVG1">pic.twitter.com/IrXFHoLVG1</a></p>— R Function A Day (@rfunctionaday) <a href="https://twitter.com/rfunctionaday/status/1388375125242822656?ref_src=twsrc%5Etfw">May 1, 2021</a></blockquote> <script async src="https://platform.twitter.com/widgets.js" charset="utf-8"></script>
## May 2 {-}
<blockquote class="twitter-tweet"><p lang="en" dir="ltr">While exploring data, one often needs a quick and easy way to create dot-and-whisker plots of coefficient estimates (or other quantities) for regression models.<br><br>The {ggcoefstats} function from {ggstatsplot} 📦 offers one such option<a href="https://t.co/e4iZpPoNIC">https://t.co/e4iZpPoNIC</a><a href="https://twitter.com/hashtag/rstats?src=hash&ref_src=twsrc%5Etfw">#rstats</a> <a href="https://twitter.com/hashtag/DataScience?src=hash&ref_src=twsrc%5Etfw">#DataScience</a> <a href="https://t.co/suxiOKjuLo">pic.twitter.com/suxiOKjuLo</a></p>— R Function A Day (@rfunctionaday) <a href="https://twitter.com/rfunctionaday/status/1388731155336384512?ref_src=twsrc%5Etfw">May 2, 2021</a></blockquote> <script async src="https://platform.twitter.com/widgets.js" charset="utf-8"></script>
## May 3 {-}
<blockquote class="twitter-tweet"><p lang="en" dir="ltr">Not all functions can properly deal with labelled data, which can cause problems for data analysis. So often one may wish to just remove all labels.<br><br>The {remove_all_labels} function from {sjlabelled} 📦 does exactly this ✂️<a href="https://t.co/9mJHPTRlVD">https://t.co/9mJHPTRlVD</a><a href="https://twitter.com/hashtag/rstats?src=hash&ref_src=twsrc%5Etfw">#rstats</a> <a href="https://twitter.com/hashtag/DataScience?src=hash&ref_src=twsrc%5Etfw">#DataScience</a> <a href="https://t.co/dt6Pbfkn58">pic.twitter.com/dt6Pbfkn58</a></p>— R Function A Day (@rfunctionaday) <a href="https://twitter.com/rfunctionaday/status/1389105836111376384?ref_src=twsrc%5Etfw">May 3, 2021</a></blockquote> <script async src="https://platform.twitter.com/widgets.js" charset="utf-8"></script>
## May 4 {-}
<blockquote class="twitter-tweet"><p lang="en" dir="ltr">The {ggplot2} syntax to carry out few common routines (e.g, changing legend position, axes, etc.) can be surprisingly hard to remember.<br><br>The {easy_} function family from {ggeasy} 📦 provides memorable shortcuts for such routines 🙌<a href="https://t.co/vqFYzcvxKZ">https://t.co/vqFYzcvxKZ</a><a href="https://twitter.com/hashtag/rstats?src=hash&ref_src=twsrc%5Etfw">#rstats</a> <a href="https://twitter.com/hashtag/DataScience?src=hash&ref_src=twsrc%5Etfw">#DataScience</a> <a href="https://t.co/eZvdrDwmNf">pic.twitter.com/eZvdrDwmNf</a></p>— R Function A Day (@rfunctionaday) <a href="https://twitter.com/rfunctionaday/status/1389449996081188868?ref_src=twsrc%5Etfw">May 4, 2021</a></blockquote> <script async src="https://platform.twitter.com/widgets.js" charset="utf-8"></script>
## May 5 {-}
<blockquote class="twitter-tweet"><p lang="en" dir="ltr">Google Scholar is an essential platform to organize one's scholarly research output.<br><br>The {get_} function family from {scholar} 📦 provides various helpers to extract information about the scholar, publications, citations, etc. 🧪<a href="https://t.co/ndoPs9Yy8S">https://t.co/ndoPs9Yy8S</a><a href="https://twitter.com/hashtag/rstats?src=hash&ref_src=twsrc%5Etfw">#rstats</a> <a href="https://twitter.com/hashtag/DataScience?src=hash&ref_src=twsrc%5Etfw">#DataScience</a> <a href="https://t.co/lAMo79rZu3">pic.twitter.com/lAMo79rZu3</a></p>— R Function A Day (@rfunctionaday) <a href="https://twitter.com/rfunctionaday/status/1389826005523746816?ref_src=twsrc%5Etfw">May 5, 2021</a></blockquote> <script async src="https://platform.twitter.com/widgets.js" charset="utf-8"></script>
## May 6 {-}
<blockquote class="twitter-tweet"><p lang="en" dir="ltr">Linear and linear mixed-effects models assume normally distributed residuals and random effects.<br><br>The validity of the assumption can be statistically and visually checked using the {check_normality} function from {performance} 📦! 🔍<a href="https://t.co/7XbOrSrYxq">https://t.co/7XbOrSrYxq</a><a href="https://twitter.com/hashtag/rstats?src=hash&ref_src=twsrc%5Etfw">#rstats</a> <a href="https://twitter.com/hashtag/DataScience?src=hash&ref_src=twsrc%5Etfw">#DataScience</a> <a href="https://t.co/AK7AX7iF6o">pic.twitter.com/AK7AX7iF6o</a></p>— R Function A Day (@rfunctionaday) <a href="https://twitter.com/rfunctionaday/status/1390190305014648834?ref_src=twsrc%5Etfw">May 6, 2021</a></blockquote> <script async src="https://platform.twitter.com/widgets.js" charset="utf-8"></script>
## May 7 {-}
<blockquote class="twitter-tweet"><p lang="en" dir="ltr">Often we wish to append visualizations of regression model estimates with a tabular summary of inferential statistics.<br><br>The {forest_model} function from {forestmodel} 📦 satisfies these requirements via an informative forest plot 🌳<a href="https://t.co/YYD6dEJXSM">https://t.co/YYD6dEJXSM</a><a href="https://twitter.com/hashtag/rstats?src=hash&ref_src=twsrc%5Etfw">#rstats</a> <a href="https://twitter.com/hashtag/DataScience?src=hash&ref_src=twsrc%5Etfw">#DataScience</a> <a href="https://t.co/rSEodymQx4">pic.twitter.com/rSEodymQx4</a></p>— R Function A Day (@rfunctionaday) <a href="https://twitter.com/rfunctionaday/status/1390535357301723139?ref_src=twsrc%5Etfw">May 7, 2021</a></blockquote> <script async src="https://platform.twitter.com/widgets.js" charset="utf-8"></script>
## May 8 {-}
<blockquote class="twitter-tweet"><p lang="en" dir="ltr">Post reproducibility crisis news, replications are on the rise across disciplines. This has led to a need to compare multiple studies.<br><br>To this end, the function {sci_figure} from {scifigure} 📦 proves to be a helpful visual tool ⚖️<a href="https://t.co/GnwtwoUcar">https://t.co/GnwtwoUcar</a><a href="https://twitter.com/hashtag/rstats?src=hash&ref_src=twsrc%5Etfw">#rstats</a> <a href="https://twitter.com/hashtag/DataScience?src=hash&ref_src=twsrc%5Etfw">#DataScience</a> <a href="https://t.co/TXbndnA0Bu">pic.twitter.com/TXbndnA0Bu</a></p>— R Function A Day (@rfunctionaday) <a href="https://twitter.com/rfunctionaday/status/1390924250165481483?ref_src=twsrc%5Etfw">May 8, 2021</a></blockquote> <script async src="https://platform.twitter.com/widgets.js" charset="utf-8"></script>
## May 9 {-}
<blockquote class="twitter-tweet"><p lang="en" dir="ltr">Sometimes the data contain implicitly missing values and one may wish to make them explicit by completing missing information.<br><br>The {complete} function from {tidyr} 📦 does exactly this! 👏<a href="https://t.co/tHbK4YAJlZ">https://t.co/tHbK4YAJlZ</a><a href="https://twitter.com/hashtag/rstats?src=hash&ref_src=twsrc%5Etfw">#rstats</a> <a href="https://twitter.com/hashtag/DataScience?src=hash&ref_src=twsrc%5Etfw">#DataScience</a> <a href="https://t.co/xbDCkW0kLG">pic.twitter.com/xbDCkW0kLG</a></p>— R Function A Day (@rfunctionaday) <a href="https://twitter.com/rfunctionaday/status/1391291298624180226?ref_src=twsrc%5Etfw">May 9, 2021</a></blockquote> <script async src="https://platform.twitter.com/widgets.js" charset="utf-8"></script>
## May 10 {-}
<blockquote class="twitter-tweet"><p lang="en" dir="ltr">Although {patchwork} 📦's arithmetic syntax (`+`, `*`, etc.) to combine plots together is extremely easy and intuitive, it can be difficult to use programmatically.<br><br>The {wrap_plots} function is the perfect alternative solution!💡<a href="https://t.co/AGLkfbPUja">https://t.co/AGLkfbPUja</a><a href="https://twitter.com/hashtag/rstats?src=hash&ref_src=twsrc%5Etfw">#rstats</a> <a href="https://twitter.com/hashtag/DataScience?src=hash&ref_src=twsrc%5Etfw">#DataScience</a> <a href="https://t.co/fJS5V9weJ3">pic.twitter.com/fJS5V9weJ3</a></p>— R Function A Day (@rfunctionaday) <a href="https://twitter.com/rfunctionaday/status/1391643259110412290?ref_src=twsrc%5Etfw">May 10, 2021</a></blockquote> <script async src="https://platform.twitter.com/widgets.js" charset="utf-8"></script>
## May 11 {-}
<blockquote class="twitter-tweet"><p lang="en" dir="ltr">Sometimes one may wish to include plots or visualizations in a table, e.g. to show the distribution of a variable.<br><br>The {spec_} function family from {kableExtra} 📦 make doing so effortless 🙌<a href="https://t.co/X4YY8Drm7C">https://t.co/X4YY8Drm7C</a><a href="https://twitter.com/hashtag/rstats?src=hash&ref_src=twsrc%5Etfw">#rstats</a> <a href="https://twitter.com/hashtag/DataScience?src=hash&ref_src=twsrc%5Etfw">#DataScience</a> <a href="https://t.co/9HRDTxEpB8">pic.twitter.com/9HRDTxEpB8</a></p>— R Function A Day (@rfunctionaday) <a href="https://twitter.com/rfunctionaday/status/1391990981248143364?ref_src=twsrc%5Etfw">May 11, 2021</a></blockquote> <script async src="https://platform.twitter.com/widgets.js" charset="utf-8"></script>
## May 12 {-}
<blockquote class="twitter-tweet"><p lang="en" dir="ltr">ROPE defines part of the posterior distribution practically equivalent to a null effect and is useful for hypothesis testing.<br><br>The {rope} function from {bayestestR} 📦 helps calculate and visualize it for Bayesian regression models:<a href="https://t.co/mfXACyKOfC">https://t.co/mfXACyKOfC</a><a href="https://twitter.com/hashtag/rstats?src=hash&ref_src=twsrc%5Etfw">#rstats</a> <a href="https://twitter.com/hashtag/DataScience?src=hash&ref_src=twsrc%5Etfw">#DataScience</a> <a href="https://t.co/W2iL072RP5">pic.twitter.com/W2iL072RP5</a></p>— R Function A Day (@rfunctionaday) <a href="https://twitter.com/rfunctionaday/status/1392312273989996544?ref_src=twsrc%5Etfw">May 12, 2021</a></blockquote> <script async src="https://platform.twitter.com/widgets.js" charset="utf-8"></script>
## May 13 {-}
<blockquote class="twitter-tweet"><p lang="en" dir="ltr">Sometimes we might need to convert numbers into English words (e.g., for assistant systems to read them out loud). 📢<br><br>The {numbers_to_words} function from {xfun} 📦 makes this routine effortless and customizable 🔢<a href="https://t.co/l2mYGmQGnx">https://t.co/l2mYGmQGnx</a><a href="https://twitter.com/hashtag/rstats?src=hash&ref_src=twsrc%5Etfw">#rstats</a> <a href="https://twitter.com/hashtag/DataScience?src=hash&ref_src=twsrc%5Etfw">#DataScience</a> <a href="https://t.co/B9atDLK3nQ">pic.twitter.com/B9atDLK3nQ</a></p>— R Function A Day (@rfunctionaday) <a href="https://twitter.com/rfunctionaday/status/1392722522651639808?ref_src=twsrc%5Etfw">May 13, 2021</a></blockquote> <script async src="https://platform.twitter.com/widgets.js" charset="utf-8"></script>
## May 14 {-}
<blockquote class="twitter-tweet"><p lang="en" dir="ltr">The Gardner–Altman mean difference plot simultaneously displays the raw data and highlights the group difference estimate 📊<br><br>The {mean_diff} function from {dabestr} 📦 creates such plots for two or multiple groups easily ⚖️<a href="https://t.co/dhtg2Nh62r">https://t.co/dhtg2Nh62r</a><a href="https://twitter.com/hashtag/rstats?src=hash&ref_src=twsrc%5Etfw">#rstats</a> <a href="https://twitter.com/hashtag/DataScience?src=hash&ref_src=twsrc%5Etfw">#DataScience</a> <a href="https://t.co/fjv2Vkpi19">pic.twitter.com/fjv2Vkpi19</a></p>— R Function A Day (@rfunctionaday) <a href="https://twitter.com/rfunctionaday/status/1393077508925440004?ref_src=twsrc%5Etfw">May 14, 2021</a></blockquote> <script async src="https://platform.twitter.com/widgets.js" charset="utf-8"></script>
## May 15 {-}
<blockquote class="twitter-tweet"><p lang="en" dir="ltr">For regression analysis with big datasets, we may at times wish to reduce memory assigned to model objects.<br><br>The {axe_} function family from {butcher} 📦 offer ways to remove different parts of the model object to make it leaner 🏋️<a href="https://t.co/ayY86U0zOy">https://t.co/ayY86U0zOy</a><a href="https://twitter.com/hashtag/rstats?src=hash&ref_src=twsrc%5Etfw">#rstats</a> <a href="https://twitter.com/hashtag/DataScience?src=hash&ref_src=twsrc%5Etfw">#DataScience</a> <a href="https://t.co/9CIU1NSqKU">pic.twitter.com/9CIU1NSqKU</a></p>— R Function A Day (@rfunctionaday) <a href="https://twitter.com/rfunctionaday/status/1393435542390456323?ref_src=twsrc%5Etfw">May 15, 2021</a></blockquote> <script async src="https://platform.twitter.com/widgets.js" charset="utf-8"></script>
## May 16 {-}
<blockquote class="twitter-tweet"><p lang="en" dir="ltr">During exploratory phase, we may wish to visualize and model data quickly, thoroughly, and iteratively ➿<br><br>The {ggbetweenstats} function from {ggstatsplot} 📦 facilitates this for one-way design via plots with statistical details 📊<a href="https://t.co/fQkmmLSOh3">https://t.co/fQkmmLSOh3</a><a href="https://twitter.com/hashtag/rstats?src=hash&ref_src=twsrc%5Etfw">#rstats</a> <a href="https://twitter.com/hashtag/DataScience?src=hash&ref_src=twsrc%5Etfw">#DataScience</a> <a href="https://t.co/uxsJ8Odv5b">pic.twitter.com/uxsJ8Odv5b</a></p>— R Function A Day (@rfunctionaday) <a href="https://twitter.com/rfunctionaday/status/1393794657436454916?ref_src=twsrc%5Etfw">May 16, 2021</a></blockquote> <script async src="https://platform.twitter.com/widgets.js" charset="utf-8"></script>
## May 17 {-}
<blockquote class="twitter-tweet"><p lang="en" dir="ltr">One often needs to compare two values on the same axis (e.g. pre-and post-treatment scores) and a dumbbell chart is an efficient way to visualize such comparison.<br><br>The {dumbbell_chart} function from {ggcharts} 📦 creates them easily:<a href="https://t.co/Y6YGS0h0DS">https://t.co/Y6YGS0h0DS</a><a href="https://twitter.com/hashtag/rstats?src=hash&ref_src=twsrc%5Etfw">#rstats</a> <a href="https://twitter.com/hashtag/DataScience?src=hash&ref_src=twsrc%5Etfw">#DataScience</a> <a href="https://t.co/Wpwey00gGV">pic.twitter.com/Wpwey00gGV</a></p>— R Function A Day (@rfunctionaday) <a href="https://twitter.com/rfunctionaday/status/1394166561964019713?ref_src=twsrc%5Etfw">May 17, 2021</a></blockquote> <script async src="https://platform.twitter.com/widgets.js" charset="utf-8"></script>
## May 18 {-}
<blockquote class="twitter-tweet"><p lang="en" dir="ltr">Programming is a challenging task and we - as a teacher, a collaborator, a developer, etc. - might wish to add a touch of encouragement to this activity sometimes.<br><br>The {praise} function from the eponymous 📦 can be of help here 💌<a href="https://t.co/wImExbbaT7">https://t.co/wImExbbaT7</a><a href="https://twitter.com/hashtag/rstats?src=hash&ref_src=twsrc%5Etfw">#rstats</a> <a href="https://twitter.com/hashtag/DataScience?src=hash&ref_src=twsrc%5Etfw">#DataScience</a> <a href="https://t.co/1SnLZ7ctS7">pic.twitter.com/1SnLZ7ctS7</a></p>— R Function A Day (@rfunctionaday) <a href="https://twitter.com/rfunctionaday/status/1394539154835447809?ref_src=twsrc%5Etfw">May 18, 2021</a></blockquote> <script async src="https://platform.twitter.com/widgets.js" charset="utf-8"></script>
## May 19 {-}
<blockquote class="twitter-tweet"><p lang="en" dir="ltr">After model-fitting, we often need to convert model objects into a dataframe, either for reporting or for visualizations. 📜<br><br>The {model_parameters} function from the {parameters} 📦 does this for many regression model objects 🌟<a href="https://t.co/4jOHsZDCaz">https://t.co/4jOHsZDCaz</a><a href="https://twitter.com/hashtag/rstats?src=hash&ref_src=twsrc%5Etfw">#rstats</a> <a href="https://twitter.com/hashtag/DataScience?src=hash&ref_src=twsrc%5Etfw">#DataScience</a> <a href="https://t.co/uI7sUSF0bz">pic.twitter.com/uI7sUSF0bz</a></p>— R Function A Day (@rfunctionaday) <a href="https://twitter.com/rfunctionaday/status/1394892948068880384?ref_src=twsrc%5Etfw">May 19, 2021</a></blockquote> <script async src="https://platform.twitter.com/widgets.js" charset="utf-8"></script>
## May 20 {-}
<blockquote class="twitter-tweet"><p lang="en" dir="ltr">In modern scientific work, the traditional credit assignment systems seem outmoded, and a contributions table is better suited.<br><br>The {generate} function from {contribution} 📦 can easily generate such tables in ggplot2-framework 🔢<a href="https://t.co/FCTli0Ht1f">https://t.co/FCTli0Ht1f</a><a href="https://twitter.com/hashtag/rstats?src=hash&ref_src=twsrc%5Etfw">#rstats</a> <a href="https://twitter.com/hashtag/DataScience?src=hash&ref_src=twsrc%5Etfw">#DataScience</a> <a href="https://t.co/IqcLPMFxOa">pic.twitter.com/IqcLPMFxOa</a></p>— R Function A Day (@rfunctionaday) <a href="https://twitter.com/rfunctionaday/status/1395257479626375168?ref_src=twsrc%5Etfw">May 20, 2021</a></blockquote> <script async src="https://platform.twitter.com/widgets.js" charset="utf-8"></script>
## May 21 {-}
<blockquote class="twitter-tweet"><p lang="en" dir="ltr">If you are fluent in {dplyr} and wish to learn how to write SQL queries, it can be nifty to have a function that can provide a syntax translation between the two.<br><br>The {show_query} function from {dbplyr} 📦 does just that! 🔄<a href="https://t.co/GAjWk5qfVC">https://t.co/GAjWk5qfVC</a><a href="https://twitter.com/hashtag/rstats?src=hash&ref_src=twsrc%5Etfw">#rstats</a> <a href="https://twitter.com/hashtag/DataScience?src=hash&ref_src=twsrc%5Etfw">#DataScience</a> <a href="https://t.co/qxOAPD4PAX">pic.twitter.com/qxOAPD4PAX</a></p>— R Function A Day (@rfunctionaday) <a href="https://twitter.com/rfunctionaday/status/1395608352017854465?ref_src=twsrc%5Etfw">May 21, 2021</a></blockquote> <script async src="https://platform.twitter.com/widgets.js" charset="utf-8"></script>
## May 22 {-}
<blockquote class="twitter-tweet"><p lang="en" dir="ltr">While working with a directory, we sometimes need to get more information about its contents.<br><br>Instead of using the terminal, one can simply use the {dir_ls} function from {fs} 📦 to return a richly informative summary 🗂<a href="https://t.co/s0UxLxPykG">https://t.co/s0UxLxPykG</a><a href="https://twitter.com/hashtag/rstats?src=hash&ref_src=twsrc%5Etfw">#rstats</a> <a href="https://twitter.com/hashtag/DataScience?src=hash&ref_src=twsrc%5Etfw">#DataScience</a> <a href="https://t.co/kAzYf2jPfB">pic.twitter.com/kAzYf2jPfB</a></p>— R Function A Day (@rfunctionaday) <a href="https://twitter.com/rfunctionaday/status/1395969857003429893?ref_src=twsrc%5Etfw">May 22, 2021</a></blockquote> <script async src="https://platform.twitter.com/widgets.js" charset="utf-8"></script>
## May 23 {-}
<blockquote class="twitter-tweet"><p lang="en" dir="ltr">During analysis, model selection may involve specification and comparison of multiple models.<br><br>The {compare_performance} function from {performance} 📦 creates tabular + graphical summaries comparing performance indices for models 🥇<a href="https://t.co/6cAI5ZbNkl">https://t.co/6cAI5ZbNkl</a><a href="https://twitter.com/hashtag/rstats?src=hash&ref_src=twsrc%5Etfw">#rstats</a> <a href="https://twitter.com/hashtag/DataScience?src=hash&ref_src=twsrc%5Etfw">#DataScience</a> <a href="https://t.co/CxyfyRCCHY">pic.twitter.com/CxyfyRCCHY</a></p>— R Function A Day (@rfunctionaday) <a href="https://twitter.com/rfunctionaday/status/1396374242724356101?ref_src=twsrc%5Etfw">May 23, 2021</a></blockquote> <script async src="https://platform.twitter.com/widgets.js" charset="utf-8"></script>
## May 24 {-}
<blockquote class="twitter-tweet"><p lang="en" dir="ltr">While writing functions that print text to the user's terminal or console, we may wish to construct a pleasant command-line interface.<br><br>The {cli_} function family from {cli} 📦 provides a collection of tools to make it pretty 💅<a href="https://t.co/HJeQ6MBgue">https://t.co/HJeQ6MBgue</a><a href="https://twitter.com/hashtag/rstats?src=hash&ref_src=twsrc%5Etfw">#rstats</a> <a href="https://twitter.com/hashtag/DataScience?src=hash&ref_src=twsrc%5Etfw">#DataScience</a> <a href="https://t.co/ZJZNBP5SAa">pic.twitter.com/ZJZNBP5SAa</a></p>— R Function A Day (@rfunctionaday) <a href="https://twitter.com/rfunctionaday/status/1396723054647119872?ref_src=twsrc%5Etfw">May 24, 2021</a></blockquote> <script async src="https://platform.twitter.com/widgets.js" charset="utf-8"></script>
## May 25 {-}
<blockquote class="twitter-tweet"><p lang="en" dir="ltr">While teaching or reporting methods, we may sometimes wish to report LaTeX equations for regression models, which can be frustrating and time-consuming.<br><br>The {extract_eq} function from {equatiomatic} 📦 makes this really easy! 🙌<a href="https://t.co/LyQ9bMxal0">https://t.co/LyQ9bMxal0</a><a href="https://twitter.com/hashtag/rstats?src=hash&ref_src=twsrc%5Etfw">#rstats</a> <a href="https://twitter.com/hashtag/DataScience?src=hash&ref_src=twsrc%5Etfw">#DataScience</a> <a href="https://t.co/mlghSLFeGJ">pic.twitter.com/mlghSLFeGJ</a></p>— R Function A Day (@rfunctionaday) <a href="https://twitter.com/rfunctionaday/status/1397068746129387522?ref_src=twsrc%5Etfw">May 25, 2021</a></blockquote> <script async src="https://platform.twitter.com/widgets.js" charset="utf-8"></script>
## May 26 {-}
<blockquote class="twitter-tweet"><p lang="en" dir="ltr">Either due to reading or formatting errors, sometimes data entries that belong together in a cell might break off across rows.<br> <br>The {unbreak_vals} function from {unheadr} 📦 makes it easy to join them using regular expressions 🩹<a href="https://t.co/gouxjvPows">https://t.co/gouxjvPows</a><a href="https://twitter.com/hashtag/rstats?src=hash&ref_src=twsrc%5Etfw">#rstats</a> <a href="https://twitter.com/hashtag/DataScience?src=hash&ref_src=twsrc%5Etfw">#DataScience</a> <a href="https://t.co/3a4ZA73xxP">pic.twitter.com/3a4ZA73xxP</a></p>— R Function A Day (@rfunctionaday) <a href="https://twitter.com/rfunctionaday/status/1397418154465366018?ref_src=twsrc%5Etfw">May 26, 2021</a></blockquote> <script async src="https://platform.twitter.com/widgets.js" charset="utf-8"></script>
## May 27 {-}
<blockquote class="twitter-tweet"><p lang="en" dir="ltr">Bar charts are a good way to visualize categorical data but making a well-labeled bar chart can be time-consuming.<br><br>The {ggbarstats} function from {ggstatsplot} 📦 easily produces such a chart (with additional statistical details) 📊<a href="https://t.co/dNl2IJAJX3">https://t.co/dNl2IJAJX3</a><a href="https://twitter.com/hashtag/rstats?src=hash&ref_src=twsrc%5Etfw">#rstats</a> <a href="https://twitter.com/hashtag/DataScience?src=hash&ref_src=twsrc%5Etfw">#DataScience</a> <a href="https://t.co/0UySWaMxei">pic.twitter.com/0UySWaMxei</a></p>— R Function A Day (@rfunctionaday) <a href="https://twitter.com/rfunctionaday/status/1397780681783193602?ref_src=twsrc%5Etfw">May 27, 2021</a></blockquote> <script async src="https://platform.twitter.com/widgets.js" charset="utf-8"></script>
## May 28 {-}
<blockquote class="twitter-tweet"><p lang="en" dir="ltr">A common data wrangling routine involves checking for presence or absence of certain combinations when the data have combinatorial structure.<br><br>The {expand} function from {tidyr} 📦 does exactly this! 👏<a href="https://t.co/oj3THZs4RW">https://t.co/oj3THZs4RW</a><a href="https://twitter.com/hashtag/rstats?src=hash&ref_src=twsrc%5Etfw">#rstats</a> <a href="https://twitter.com/hashtag/DataScience?src=hash&ref_src=twsrc%5Etfw">#DataScience</a> <a href="https://t.co/SjHZo7bpxv">pic.twitter.com/SjHZo7bpxv</a></p>— R Function A Day (@rfunctionaday) <a href="https://twitter.com/rfunctionaday/status/1398145516010156033?ref_src=twsrc%5Etfw">May 28, 2021</a></blockquote> <script async src="https://platform.twitter.com/widgets.js" charset="utf-8"></script>
## May 29 {-}
<blockquote class="twitter-tweet"><p lang="en" dir="ltr">Although adding horizontal and vertical lines to {ggplot2} is easy, sometimes we need to add them both and with multiple intercepts.<br><br>The {geom_vhlines} function from {ggpp} 📦 provides a perfect geometric layer to do so quickly! ⚡️<a href="https://t.co/gNfzDhRdhu">https://t.co/gNfzDhRdhu</a><a href="https://twitter.com/hashtag/rstats?src=hash&ref_src=twsrc%5Etfw">#rstats</a> <a href="https://twitter.com/hashtag/DataScience?src=hash&ref_src=twsrc%5Etfw">#DataScience</a> <a href="https://t.co/1oA1ZMWDKI">pic.twitter.com/1oA1ZMWDKI</a></p>— R Function A Day (@rfunctionaday) <a href="https://twitter.com/rfunctionaday/status/1398475846810320897?ref_src=twsrc%5Etfw">May 29, 2021</a></blockquote> <script async src="https://platform.twitter.com/widgets.js" charset="utf-8"></script>
## May 30 {-}
<blockquote class="twitter-tweet"><p lang="en" dir="ltr">Across projects, we may have a similar directory structure and, therefore, we may prefer to create directories algorithmically over manually.<br><br>The {dir_create} function from {fs} 📦 is perfect for safely doing this! 🗃️<a href="https://t.co/SvS78Z0hIN">https://t.co/SvS78Z0hIN</a><a href="https://twitter.com/hashtag/rstats?src=hash&ref_src=twsrc%5Etfw">#rstats</a> <a href="https://twitter.com/hashtag/DataScience?src=hash&ref_src=twsrc%5Etfw">#DataScience</a> <a href="https://t.co/uHEXy3n1N6">pic.twitter.com/uHEXy3n1N6</a></p>— R Function A Day (@rfunctionaday) <a href="https://twitter.com/rfunctionaday/status/1398853015302516737?ref_src=twsrc%5Etfw">May 30, 2021</a></blockquote> <script async src="https://platform.twitter.com/widgets.js" charset="utf-8"></script>
## May 31 {-}
<blockquote class="twitter-tweet"><p lang="en" dir="ltr">The {latex2exp} 📦 is useful to convert LaTeX equations to R’s {plotmath}. But what if we instead want to do the opposite: convert {plotmath} expressions to LaTeX?<br><br>The {expr2latex} function from {simsalapar} 📦 does exactly this! 🔀<a href="https://t.co/MvVrIEOdwe">https://t.co/MvVrIEOdwe</a><a href="https://twitter.com/hashtag/rstats?src=hash&ref_src=twsrc%5Etfw">#rstats</a> <a href="https://twitter.com/hashtag/DataScience?src=hash&ref_src=twsrc%5Etfw">#DataScience</a> <a href="https://t.co/kSMSdp4gIC">pic.twitter.com/kSMSdp4gIC</a></p>— R Function A Day (@rfunctionaday) <a href="https://twitter.com/rfunctionaday/status/1399182278908157954?ref_src=twsrc%5Etfw">May 31, 2021</a></blockquote> <script async src="https://platform.twitter.com/widgets.js" charset="utf-8"></script>