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March-2021.Rmd
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March-2021.Rmd
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# March 2021 {-}
## March 1 {-}
<blockquote class="twitter-tweet"><p lang="en" dir="ltr">This one is an oldie but a goodie:<br>The {switch} function from {base} 📦 helps you select from a list of alternative actions depending on a condition of interest 🗂<a href="https://t.co/IYYI1dIvpm">https://t.co/IYYI1dIvpm</a><br><br>Note how, if unspecified, values can trickle down.<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/6iqBh85XMY">pic.twitter.com/6iqBh85XMY</a></p>— R Function A Day (@rfunctionaday) <a href="https://twitter.com/rfunctionaday/status/1366285026510458882?ref_src=twsrc%5Etfw">March 1, 2021</a></blockquote> <script async src="https://platform.twitter.com/widgets.js" charset="utf-8"></script>
## March 2 {-}
<blockquote class="twitter-tweet"><p lang="en" dir="ltr">In case you want to create a new variable conditional on checking whether values for a different variable lie inside an interval, the {between} function in {dplyr} can be a big help 👌<a href="https://t.co/JrEHPo5oDv">https://t.co/JrEHPo5oDv</a><br><br>Works with date-time objects as well! 🙌<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/J5TtCwLBE3">pic.twitter.com/J5TtCwLBE3</a></p>— R Function A Day (@rfunctionaday) <a href="https://twitter.com/rfunctionaday/status/1366670986893004800?ref_src=twsrc%5Etfw">March 2, 2021</a></blockquote> <script async src="https://platform.twitter.com/widgets.js" charset="utf-8"></script>
## March 3 {-}
<blockquote class="twitter-tweet"><p lang="en" dir="ltr">Sometimes you might wish to know which 📦 some of the unfamiliar functions are from, or where some of the objects in your session are located. <br><br>The {find} function in {base} 📦 can be helpful here 🔍<a href="https://t.co/vTvhBnFogF">https://t.co/vTvhBnFogF</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/BG9E8cnS9w">pic.twitter.com/BG9E8cnS9w</a></p>— R Function A Day (@rfunctionaday) <a href="https://twitter.com/rfunctionaday/status/1367016016153296896?ref_src=twsrc%5Etfw">March 3, 2021</a></blockquote> <script async src="https://platform.twitter.com/widgets.js" charset="utf-8"></script>
## March 4 {-}
<blockquote class="twitter-tweet"><p lang="en" dir="ltr">No matter the programming language I code in, I rarely wish to leave the comfort zone of <a href="https://twitter.com/hashtag/rmarkdown?src=hash&ref_src=twsrc%5Etfw">#rmarkdown</a> 🏡 <br><br>But how does one check details about the languages currently supported? Using the {knit_engine} function from {knitr} 🧶 <a href="https://t.co/bVEzn990dE">https://t.co/bVEzn990dE</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/LCHtsb1b1T">pic.twitter.com/LCHtsb1b1T</a></p>— R Function A Day (@rfunctionaday) <a href="https://twitter.com/rfunctionaday/status/1367376552636395520?ref_src=twsrc%5Etfw">March 4, 2021</a></blockquote> <script async src="https://platform.twitter.com/widgets.js" charset="utf-8"></script>
## March 5 {-}
<blockquote class="twitter-tweet"><p lang="en" dir="ltr">If you are used to creating tibble columns sequentially, you might think a similar procedure works while creating lists, but it doesn’t, at least not with {base::list}.<br><br>You can instead use {lst} function from {tibble} 📦! 🛠<a href="https://t.co/K97EBCEsYz">https://t.co/K97EBCEsYz</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/p152AVXFDb">pic.twitter.com/p152AVXFDb</a></p>— R Function A Day (@rfunctionaday) <a href="https://twitter.com/rfunctionaday/status/1367726742127972353?ref_src=twsrc%5Etfw">March 5, 2021</a></blockquote> <script async src="https://platform.twitter.com/widgets.js" charset="utf-8"></script>
## March 6 {-}
<blockquote class="twitter-tweet"><p lang="en" dir="ltr">Most R packages are standing on the shoulders of other packages. <br><br>In case you are curious to find out which ones, you can use the {plot_dependencies} function from {deepdep} 📦 for visualizing the said dependence:<a href="https://t.co/3tl1A7aMW3">https://t.co/3tl1A7aMW3</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/dUeHWz3MBA">pic.twitter.com/dUeHWz3MBA</a></p>— R Function A Day (@rfunctionaday) <a href="https://twitter.com/rfunctionaday/status/1368106068497285120?ref_src=twsrc%5Etfw">March 6, 2021</a></blockquote> <script async src="https://platform.twitter.com/widgets.js" charset="utf-8"></script>
## March 7 {-}
<blockquote class="twitter-tweet"><p lang="en" dir="ltr">Missing values can be troublesome for some statistical analysis and need to be attended to during the data exploration phase.<br><br>The {vis_dat} function from {visdat} 📦 makes it effortless to glean the structure of missing values 🔍<a href="https://t.co/ciff6eE06w">https://t.co/ciff6eE06w</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/eM4uJgWApO">pic.twitter.com/eM4uJgWApO</a></p>— R Function A Day (@rfunctionaday) <a href="https://twitter.com/rfunctionaday/status/1368524036351868929?ref_src=twsrc%5Etfw">March 7, 2021</a></blockquote> <script async src="https://platform.twitter.com/widgets.js" charset="utf-8"></script>
## March 8 {-}
<blockquote class="twitter-tweet"><p lang="en" dir="ltr">In case you want to access statistics about your system memory without leaving R, you can use the {ps_system_memory} function from the {ps} 📦<a href="https://t.co/hSVUebKkIG">https://t.co/hSVUebKkIG</a><br><br>The measure to watch out for is the available memory.<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/D4YoWLNsku">pic.twitter.com/D4YoWLNsku</a></p>— R Function A Day (@rfunctionaday) <a href="https://twitter.com/rfunctionaday/status/1368952137112227840?ref_src=twsrc%5Etfw">March 8, 2021</a></blockquote> <script async src="https://platform.twitter.com/widgets.js" charset="utf-8"></script>
## March 9 {-}
<blockquote class="twitter-tweet"><p lang="en" dir="ltr">Sometimes your data is tabled, i.e. a single row corresponds to multiple observations, not one.<br><br>To convert it to tidy data, you can untable it using the {uncount} function from {tidyr} 📦<a href="https://t.co/LVXog4CWVM">https://t.co/LVXog4CWVM</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/r7tcMVkIFL">pic.twitter.com/r7tcMVkIFL</a></p>— R Function A Day (@rfunctionaday) <a href="https://twitter.com/rfunctionaday/status/1369174610877513728?ref_src=twsrc%5Etfw">March 9, 2021</a></blockquote> <script async src="https://platform.twitter.com/widgets.js" charset="utf-8"></script>
## March 10 {-}
<blockquote class="twitter-tweet"><p lang="en" dir="ltr">Sometimes you have multiple functions that you always use in conjunction and wish you can compose them into a single function.<br><br>Thanks to {compose} function from {purrr} 📦, you can do exactly that! 🎼<a href="https://t.co/zdydXfEM35">https://t.co/zdydXfEM35</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/teZ5w65uHS">pic.twitter.com/teZ5w65uHS</a></p>— R Function A Day (@rfunctionaday) <a href="https://twitter.com/rfunctionaday/status/1369635944652038146?ref_src=twsrc%5Etfw">March 10, 2021</a></blockquote> <script async src="https://platform.twitter.com/widgets.js" charset="utf-8"></script>
## March 11 {-}
<blockquote class="twitter-tweet"><p lang="en" dir="ltr">If you like a certain color from a palette and wish to use it in your plots, you need to find out what’s the hexadecimal code for that color.<br><br>You can use the {show_col} function from {scales} 📦 to achieve this 🎨<a href="https://t.co/vxlr8ff035">https://t.co/vxlr8ff035</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/UDN1IFMvO9">pic.twitter.com/UDN1IFMvO9</a></p>— R Function A Day (@rfunctionaday) <a href="https://twitter.com/rfunctionaday/status/1369896897914212352?ref_src=twsrc%5Etfw">March 11, 2021</a></blockquote> <script async src="https://platform.twitter.com/widgets.js" charset="utf-8"></script>
## March 12 {-}
<blockquote class="twitter-tweet"><p lang="en" dir="ltr">If you want to substitute a certain string pattern in data, you can use {gsub}. But what if you wish to do this across *files*?<br><br>You can use the {gsub_file} function from {xfun} 📦 to do such substitutions! 🔁<a href="https://t.co/1PFI7vdRn0">https://t.co/1PFI7vdRn0</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/09C9GNbKPi">pic.twitter.com/09C9GNbKPi</a></p>— R Function A Day (@rfunctionaday) <a href="https://twitter.com/rfunctionaday/status/1370263348017774592?ref_src=twsrc%5Etfw">March 12, 2021</a></blockquote> <script async src="https://platform.twitter.com/widgets.js" charset="utf-8"></script>
## March 13 {-}
<blockquote class="twitter-tweet"><p lang="en" dir="ltr">If you have tidy data and wish to carry out operations that require the data to be in wide format, the “spread-operate-retidy” pattern can be a bit cumbersome.<br><br>The {pairwise_} function family from {widyr} 📦 makes this less painful:<a href="https://t.co/sIcFOKSJSM">https://t.co/sIcFOKSJSM</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/iaQTtAmzPS">pic.twitter.com/iaQTtAmzPS</a></p>— R Function A Day (@rfunctionaday) <a href="https://twitter.com/rfunctionaday/status/1370680983029186562?ref_src=twsrc%5Etfw">March 13, 2021</a></blockquote> <script async src="https://platform.twitter.com/widgets.js" charset="utf-8"></script>
## March 14 {-}
<blockquote class="twitter-tweet"><p lang="en" dir="ltr">While working with text data, sometimes you can have a long running paragraph that needs to be wrapped so that it is more readable (and pretty). 📖<br><br>The {str_wrap} function from {stringr} does the trick! 💡<a href="https://t.co/OF9drlXHl0">https://t.co/OF9drlXHl0</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/8QVlPZ0vTW">pic.twitter.com/8QVlPZ0vTW</a></p>— R Function A Day (@rfunctionaday) <a href="https://twitter.com/rfunctionaday/status/1371000068380237830?ref_src=twsrc%5Etfw">March 14, 2021</a></blockquote> <script async src="https://platform.twitter.com/widgets.js" charset="utf-8"></script>
## March 15 {-}
<blockquote class="twitter-tweet"><p lang="en" dir="ltr">If you have regression model with interaction effect, it can be tricky to visualize the interaction in a statistically informative way.<br><br>Thankfully, {interplot} 📦 has already done that thinking for you in its eponymous function 🙏<a href="https://t.co/DhhrVrUxyG">https://t.co/DhhrVrUxyG</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/rWYxVqnpVV">pic.twitter.com/rWYxVqnpVV</a></p>— R Function A Day (@rfunctionaday) <a href="https://twitter.com/rfunctionaday/status/1371386977623408640?ref_src=twsrc%5Etfw">March 15, 2021</a></blockquote> <script async src="https://platform.twitter.com/widgets.js" charset="utf-8"></script>
## March 16 {-}
<blockquote class="twitter-tweet"><p lang="en" dir="ltr">In case you are used to the python-style tuple assignment, you can also do something similar in R using the infix operator from {tidytidbits} 📦!<a href="https://t.co/0g6LDoZfmq">https://t.co/0g6LDoZfmq</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/M14Qt9p1rg">pic.twitter.com/M14Qt9p1rg</a></p>— R Function A Day (@rfunctionaday) <a href="https://twitter.com/rfunctionaday/status/1371735571081609217?ref_src=twsrc%5Etfw">March 16, 2021</a></blockquote> <script async src="https://platform.twitter.com/widgets.js" charset="utf-8"></script>
## March 17 {-}
<blockquote class="twitter-tweet"><p lang="en" dir="ltr">To report posterior distribution of a Bayesian model, you might report a point estimate, uncertainty around it, and an index for importance of the effect.<br><br>You can do all this using {describe_posterior} function from {bayestestR} 📦<a href="https://t.co/OsEGXjo0Nr">https://t.co/OsEGXjo0Nr</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/68fHWiuOM1">pic.twitter.com/68fHWiuOM1</a></p>— R Function A Day (@rfunctionaday) <a href="https://twitter.com/rfunctionaday/status/1372102242149470212?ref_src=twsrc%5Etfw">March 17, 2021</a></blockquote> <script async src="https://platform.twitter.com/widgets.js" charset="utf-8"></script>
## March 18 {-}
<blockquote class="twitter-tweet"><p lang="en" dir="ltr">If you see a beautiful image and think to yourself: "I would really like to use that color palette in my plot!", you can do so! 🎨<br><br>You can extract the color palette from image using the {create_palette} function from {paletter} 📦<a href="https://t.co/uZsB1ovCsf">https://t.co/uZsB1ovCsf</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/vMIv9eZARJ">pic.twitter.com/vMIv9eZARJ</a></p>— R Function A Day (@rfunctionaday) <a href="https://twitter.com/rfunctionaday/status/1372450060756193280?ref_src=twsrc%5Etfw">March 18, 2021</a></blockquote> <script async src="https://platform.twitter.com/widgets.js" charset="utf-8"></script>
## March 19 {-}
<blockquote class="twitter-tweet"><p lang="en" dir="ltr">If you wish to include mathematical expressions in a plot/text, but you are more comfortable writing them in LaTeX than in R’s plotmath, you can use the {TeX} function from {latex2exp} 📦 for a translation! 👏<a href="https://t.co/cpyeNcFL1j">https://t.co/cpyeNcFL1j</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/gRPLIFljTa">pic.twitter.com/gRPLIFljTa</a></p>— R Function A Day (@rfunctionaday) <a href="https://twitter.com/rfunctionaday/status/1372810788918939650?ref_src=twsrc%5Etfw">March 19, 2021</a></blockquote> <script async src="https://platform.twitter.com/widgets.js" charset="utf-8"></script>
## March 20 {-}
<blockquote class="twitter-tweet"><p lang="en" dir="ltr">When you have to format or interpolate strings using piped data, you can do so easily using the {glue_data} function from {glue} 📦<a href="https://t.co/INusSE9k2u">https://t.co/INusSE9k2u</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/YGgl1ZAGNC">pic.twitter.com/YGgl1ZAGNC</a></p>— R Function A Day (@rfunctionaday) <a href="https://twitter.com/rfunctionaday/status/1373174822654607360?ref_src=twsrc%5Etfw">March 20, 2021</a></blockquote> <script async src="https://platform.twitter.com/widgets.js" charset="utf-8"></script>
## March 21 {-}
<blockquote class="twitter-tweet"><p lang="en" dir="ltr">If you wish to embed a well-formatted HTML table containing a summary of your regression model, the {tab_model} function from {sjPlot} 📦 can do so effortlessly:<a href="https://t.co/dtVUrfWVkB">https://t.co/dtVUrfWVkB</a><br><br>Supports simple, mixed-effects, Bayesian, etc. regression models.<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/8wZha5ohNi">pic.twitter.com/8wZha5ohNi</a></p>— R Function A Day (@rfunctionaday) <a href="https://twitter.com/rfunctionaday/status/1373538423722680322?ref_src=twsrc%5Etfw">March 21, 2021</a></blockquote> <script async src="https://platform.twitter.com/widgets.js" charset="utf-8"></script>
## March 22 {-}
<blockquote class="twitter-tweet"><p lang="en" dir="ltr">It can be a daunting task to construct regular expressions, especially complex ones.<br><br>The {rx_} function family from {RVerbalExpressions} 📦 makes this more accessible by allowing one to construct regex using verbal expressions 🔡<a href="https://t.co/5G77171gYA">https://t.co/5G77171gYA</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/MbLmKSW0KX">pic.twitter.com/MbLmKSW0KX</a></p>— R Function A Day (@rfunctionaday) <a href="https://twitter.com/rfunctionaday/status/1373899707286704131?ref_src=twsrc%5Etfw">March 22, 2021</a></blockquote> <script async src="https://platform.twitter.com/widgets.js" charset="utf-8"></script>
## March 23 {-}
<blockquote class="twitter-tweet"><p lang="en" dir="ltr">If data has hierarchical categories, you may wish to see their breakdown into subcategories (e.g., to check if enough observations per cell for mixed-effects model).<br><br>You can easily do so using {sizetree} function from {plotrix} 📦!<a href="https://t.co/tH5hUetZ2A">https://t.co/tH5hUetZ2A</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/5d52tK8Mx7">pic.twitter.com/5d52tK8Mx7</a></p>— R Function A Day (@rfunctionaday) <a href="https://twitter.com/rfunctionaday/status/1374323484520759298?ref_src=twsrc%5Etfw">March 23, 2021</a></blockquote> <script async src="https://platform.twitter.com/widgets.js" charset="utf-8"></script>
## March 24 {-}
<blockquote class="twitter-tweet"><p lang="en" dir="ltr">If you have a list-of-lists, sometimes you may wish to turn it inside out, i.e. convert a pair of lists into a list of pairs. 🔀<br><br>The {transpose} function from {purrr} 📦 makes this easy:<a href="https://t.co/TBQHC2jw3r">https://t.co/TBQHC2jw3r</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/7wS8by9ysf">pic.twitter.com/7wS8by9ysf</a></p>— R Function A Day (@rfunctionaday) <a href="https://twitter.com/rfunctionaday/status/1374629805463908354?ref_src=twsrc%5Etfw">March 24, 2021</a></blockquote> <script async src="https://platform.twitter.com/widgets.js" charset="utf-8"></script>
## March 25 {-}
<blockquote class="twitter-tweet"><p lang="en" dir="ltr">While writing functions, either for a 📦 or for colleagues, you can construct an elegant user-interface (UI) using {ui_} function family from {usethis} 📦<a href="https://t.co/PxL3FRV8Qk">https://t.co/PxL3FRV8Qk</a><br><br>Such UI provides helpful info, esp. for functions that do multiple things.<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/kCgSLY9gMz">pic.twitter.com/kCgSLY9gMz</a></p>— R Function A Day (@rfunctionaday) <a href="https://twitter.com/rfunctionaday/status/1374988850418884609?ref_src=twsrc%5Etfw">March 25, 2021</a></blockquote> <script async src="https://platform.twitter.com/widgets.js" charset="utf-8"></script>
## March 26 {-}
<blockquote class="twitter-tweet"><p lang="en" dir="ltr">When you are visualizing data, in addition to plotting the full dataset, you may also wish to emphasize/zoom in on its subset for a special consideration.<br><br>You can do this easily with the {facet_zoom} function from {ggforce} 📦! 🙌<a href="https://t.co/Dm7Lbzv0Pt">https://t.co/Dm7Lbzv0Pt</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/3EKrTafXRi">pic.twitter.com/3EKrTafXRi</a></p>— R Function A Day (@rfunctionaday) <a href="https://twitter.com/rfunctionaday/status/1375337407013384194?ref_src=twsrc%5Etfw">March 26, 2021</a></blockquote> <script async src="https://platform.twitter.com/widgets.js" charset="utf-8"></script>
## March 27 {-}
<blockquote class="twitter-tweet"><p lang="en" dir="ltr">If in the *middle* of your piped workflow, you wish to access a side effect (e.g., plot or print something) and then continue on with chained operations, you can do so using the tee pipe operator {%T>%} from {magrittr} 📦 ! <a href="https://t.co/ibga7yyf5X">https://t.co/ibga7yyf5X</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/5H0MoPOERY">pic.twitter.com/5H0MoPOERY</a></p>— R Function A Day (@rfunctionaday) <a href="https://twitter.com/rfunctionaday/status/1375690823862521865?ref_src=twsrc%5Etfw">March 27, 2021</a></blockquote> <script async src="https://platform.twitter.com/widgets.js" charset="utf-8"></script>
## March 28 {-}
<blockquote class="twitter-tweet"><p lang="en" dir="ltr">For correlation hypotheses, in addition to the joint distribution in a scatterplot, one may also wish to visualize the marginal distributions for each variable.<br><br>This is easy to do using the {ggMarginal} function from {ggExtra} 📦!<a href="https://t.co/OgS1XsmY1U">https://t.co/OgS1XsmY1U</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/wE8mmJwnIx">pic.twitter.com/wE8mmJwnIx</a></p>— R Function A Day (@rfunctionaday) <a href="https://twitter.com/rfunctionaday/status/1376076854591950850?ref_src=twsrc%5Etfw">March 28, 2021</a></blockquote> <script async src="https://platform.twitter.com/widgets.js" charset="utf-8"></script>
## March 29 {-}
<blockquote class="twitter-tweet"><p lang="en" dir="ltr">If you need to convert a vector or a list into a dataframe, you can use the {enframe} function from {tibble} 📦 to do this conveniently:<a href="https://t.co/dsjo0w5aYD">https://t.co/dsjo0w5aYD</a><br><br>Compare its behavior with that of {data.frame} function to see when you want to prefer it.<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/BxCBR64XF8">pic.twitter.com/BxCBR64XF8</a></p>— R Function A Day (@rfunctionaday) <a href="https://twitter.com/rfunctionaday/status/1376428395333095427?ref_src=twsrc%5Etfw">March 29, 2021</a></blockquote> <script async src="https://platform.twitter.com/widgets.js" charset="utf-8"></script>
## March 30 {-}
<blockquote class="twitter-tweet"><p lang="en" dir="ltr">Sometimes you need to display two plots, not in a grid, but one inside the other (aka "inset" plot).<br><br>Assuming you are using the grammar of graphics approach, this is easy to do using {annotation_custom} function from {ggplot2} 📦:<a href="https://t.co/GTV3UX2XV6">https://t.co/GTV3UX2XV6</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/cVH9J0dHTJ">pic.twitter.com/cVH9J0dHTJ</a></p>— R Function A Day (@rfunctionaday) <a href="https://twitter.com/rfunctionaday/status/1376782104479084545?ref_src=twsrc%5Etfw">March 30, 2021</a></blockquote> <script async src="https://platform.twitter.com/widgets.js" charset="utf-8"></script>
## March 31 {-}
<blockquote class="twitter-tweet"><p lang="en" dir="ltr">If you need to pad strings, the appropriately named {str_pad} function from {stringr} 📦 makes this effortless 🧵<a href="https://t.co/Ar7LehWFQl">https://t.co/Ar7LehWFQl</a><br><br>See examples below to see all the different ways in which you can do such padding.<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/TZpXJSWvwv">pic.twitter.com/TZpXJSWvwv</a></p>— R Function A Day (@rfunctionaday) <a href="https://twitter.com/rfunctionaday/status/1377150257780301825?ref_src=twsrc%5Etfw">March 31, 2021</a></blockquote> <script async src="https://platform.twitter.com/widgets.js" charset="utf-8"></script>