R Function A Day @rfunctionaday
R function a day keeps the madness away š§āāļø ā If youāre a new follower, check out older posts as well š ā From 24.01.2021 to 24.01.2022 ā by @patilindrajeets Joined January 2021-
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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.
Today concludes this 1-year hobby project. There wonāt be new posts, so feel free to unfollow, but do keep revisiting! š With > 22K followers in 365 posts, I guess you enjoyed reading them as I much as Iād preparing them. š Best luck with your jouRneys! š¤ @patilindrajeets
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} š¦ provides a summary of data types to check this! šš sfirke.github.io/janitor/refere⦠#rstats #DataScience
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} š¦ provides a more readable syntax to this end! š dplyr.tidyverse.org/reference/pull⦠#rstats #DataScience
Visualizing data along an Archimedean spiral can efficiently reveal periodic patterns in time series data. The {spiral_*} function family from {spiralize} š¦ draws such spiral plots flexibly! š jokergoo.github.io/spiralize_vign⦠#rstats #DataScience
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} š¦ provides a performant way to serialize or deserialize any R object! ā”ļø rdrr.io/cran/qs/man/ #rstats #DataScience
Sometimes you may wish to include some patterns or images in plots for enhanced storytelling. The {image*} or {pattern*} function family from {patternplot} š¦ provides a way to do so! āļø rdrr.io/cran/patternpl⦠#rstats #DataScience
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} š¦ gives you access to this data type in R! š rstudio.github.io/reticulate/ref⦠#rstats #DataScience
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} š¦ does exactly this! ā¾ strengejacke.github.io/sjmisc/referen⦠#rstats #DataScience
A horizon plot is a compact time-series data visualization to plot and compare different moving values. The {geom_horizon} function from {ggHoriPlot} š¦ provides just the geometric layer! ā¬ļøā¬ļø rivasiker.github.io/ggHoriPlot/art⦠#rstats #DataScience
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} š¦ makes this conversion easy! šø davidchall.github.io/ipaddress/refe⦠#rstats #DataScience
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} š¦ provides an easy syntax to do so! š readxl.tidyverse.org/reference/read⦠#rstats #DataScience
Sometimes you want to quickly compute and visualize frequencies for all categorical variables in the data. The {inspect_cat} function from {inspectdf} š¦ does so, while labeling most frequent levels and highlighting missing data! š alastairrushworth.github.io/inspectdf/arti⦠#rstats #DataScience
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} š¦ provides helpers to do so! š rdrr.io/cran/xfun/man/⦠#rstats #DataScience
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} š¦ offers just the geometric layer! šŖ pkg.mitchelloharawild.com/ggquiver/refer⦠#rstats #DataScience
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} š¦ provides helpers to do this with type stability! š purrr.tidyverse.org/reference/flat⦠#rstats #DataScience
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} š¦ produces publication-ready HTML table for PCA with elegant defaults! š strengejacke.github.io/sjPlot/referen⦠#rstats #DataScience

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