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R Function A Day @rfunctionaday

R function a day keeps the madness away šŸ§˜ā€ā™€ļø ā€” If youā€™re a new follower, check out older posts as well šŸ˜Š ā€” From 24.01.2021 to 24.01.2022 ā€” by @patilindrajeets Joined January 2021
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Indrajeet Patil (ą¤‡ą¤‚ą¤¦ą„ą¤°ą¤œą„€ą¤¤ ą¤Ŗą¤¾ą¤Ÿą„€ą¤²) @patilindrajeets

2 years ago

If you are looking for a fun way to test your #JavaScript knowledge, I have built a simple game. The goal is not to *teach* you JavaScript, but to *test* if you've understood the language features and data structures. indrajeetpatil.github.io/save-indy/ Let me know if you've any feedback.

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R Function A Day @rfunctionaday

4 years ago

Today concludes this 1-year hobby project. There wonā€™t be new posts, so feel free to unfollow, but do keep revisiting! šŸ™ƒ With > 22K followers in 365 posts, I guess you enjoyed reading them as I much as Iā€™d preparing them. šŸ˜… Best luck with your jouRneys! šŸ¤ž @patilindrajeets

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R Function A Day @rfunctionaday

4 years ago

If we need to bind multiple dataframes by rows, we may first wish to check if this can be done successfully. The {compare_df_cols} function from {janitor} šŸ“¦ provides a summary of data types to check this! šŸŽšŸ sfirke.github.io/janitor/refereā€¦ #rstats #DataScience

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R Function A Day @rfunctionaday

4 years ago

While working in a piped workflow, if you need to extract a single column, the syntax to do so can be a bit cumbersome. The {pull} function from {dplyr} šŸ“¦ provides a more readable syntax to this end! šŸ’„ dplyr.tidyverse.org/reference/pullā€¦ #rstats #DataScience

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R Function A Day @rfunctionaday

4 years ago

Visualizing data along an Archimedean spiral can efficiently reveal periodic patterns in time series data. The {spiral_*} function family from {spiralize} šŸ“¦ draws such spiral plots flexibly! šŸŒ€ jokergoo.github.io/spiralize_vignā€¦ #rstats #DataScience

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R Function A Day @rfunctionaday

4 years ago

Serialization changes objects to a byte stream that can be saved to a binary file, while deserializing does the reverse. The {q*} function family from {qs} šŸ“¦ provides a performant way to serialize or deserialize any R object! āš”ļø rdrr.io/cran/qs/man/ #rstats #DataScience

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R Function A Day @rfunctionaday

4 years ago

Sometimes you may wish to include some patterns or images in plots for enhanced storytelling. The {image*} or {pattern*} function family from {patternplot} šŸ“¦ provides a way to do so! āšœļø rdrr.io/cran/patternplā€¦ #rstats #DataScience

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R Function A Day @rfunctionaday

4 years ago

Python dictionary is an unordered data type with key-value pairs that allows accessing values, not by indexing, but via unique keys. The {py_dict} function from {reticulate} šŸ“¦ gives you access to this data type in R! šŸ“– rstudio.github.io/reticulate/refā€¦ #rstats #DataScience

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R Function A Day @rfunctionaday

4 years ago

Sometimes, especially in the context of statistical modeling, there might be infinite or NaN's present in outputs that we may wish to replace with NAs. The {zap_inf} helper function from {sjmisc} šŸ“¦ does exactly this! ā™¾ strengejacke.github.io/sjmisc/referenā€¦ #rstats #DataScience

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R Function A Day @rfunctionaday

4 years ago

A horizon plot is a compact time-series data visualization to plot and compare different moving values. The {geom_horizon} function from {ggHoriPlot} šŸ“¦ provides just the geometric layer! ā¬†ļøā¬‡ļø rivasiker.github.io/ggHoriPlot/artā€¦ #rstats #DataScience

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R Function A Day @rfunctionaday

4 years ago

To save space, IP addresses are often stored as integers, and if we receive such data, we may wish to convert them to the familiar human-readable form. The {integer_to_ip} function from {ipaddress} šŸ“¦ makes this conversion easy! šŸ•ø davidchall.github.io/ipaddress/refeā€¦ #rstats #DataScience

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R Function A Day @rfunctionaday

4 years ago

Although often you can easily read data from a single CSV file, sometimes you have to read a dataset stored in one of the Excel spreadsheets. The {read_xlsx} function from {readxl} šŸ“¦ provides an easy syntax to do so! šŸ“ readxl.tidyverse.org/reference/readā€¦ #rstats #DataScience

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R Function A Day @rfunctionaday

4 years ago

Sometimes you want to quickly compute and visualize frequencies for all categorical variables in the data. The {inspect_cat} function from {inspectdf} šŸ“¦ does so, while labeling most frequent levels and highlighting missing data! šŸ“Š alastairrushworth.github.io/inspectdf/artiā€¦ #rstats #DataScience

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R Function A Day @rfunctionaday

4 years ago

Filename extensions (.py, .csv, .pdf, etc.) decide the characteristics and intended usage of files, and we may wish to work with them further in R. The {*_ext} function family in {xfun} šŸ“¦ provides helpers to do so! šŸ—‚ rdrr.io/cran/xfun/man/ā€¦ #rstats #DataScience

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R Function A Day @rfunctionaday

4 years ago

Across disciplines (physics, engineering, etc.), a quiver plot helps visualize vector fields as arrows, and we may need to create such a plot in R. The {geom_quiver} function from {ggquiver} šŸ“¦ offers just the geometric layer! šŸŒŖ pkg.mitchelloharawild.com/ggquiver/referā€¦ #rstats #DataScience

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R Function A Day @rfunctionaday

4 years ago

A list is a non-atomic vector, and sometimes you may wish to convert (or flatten) it to an atomic one. The {flatten} function family from {purrr} šŸ“¦ provides helpers to do this with type stability! šŸ—œ purrr.tidyverse.org/reference/flatā€¦ #rstats #DataScience

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R Function A Day @rfunctionaday

4 years ago

PCA is a popular dimensionality reduction technique and sometimes you may wish to reports its results in a report. The {tab_pca} function from {sjPlot} šŸ“¦ produces publication-ready HTML table for PCA with elegant defaults! šŸ“ strengejacke.github.io/sjPlot/referenā€¦ #rstats #DataScience

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