R Function A Day

R function a day keeps the madness away 🧘‍♀️ — If you’re a new follower, check out older posts as well 😊 — From 24.01.2021 to 24.01.2022 — by @patilindrajeets

[R Function A Day @rfunctionaday]

As requested by some of you, there is now a book of these posts! 📗

https://t.co/ziDsn8dFCR

Makes it easy to-

📑 read
🔍 search
🔗 share
etc.

It ain't pretty, but that's the best I'd do in a day 😅

PRs welcome if you notice that something is amiss 🙏

#rstats #DataScience

[R Function A Day @rfunctionaday]

Today concludes this 1-year hobby project.

There won’t be new posts, so feel free to unfollow, but do keep revisiting! 🙃

With > 22K followers in 365 posts, I guess you enjoyed reading them as I much as I’d preparing them. 😅

Best luck with your jouRneys! 🤞
@patilindrajeets

[R Function A Day @rfunctionaday]

This function no longer resides in {parameters} 📦.

It can now be found in {datawizard} 📦:

https://t.co/MtE9p6gXRg

[R Function A Day @rfunctionaday]

If you want to get a quick overview of descriptive statistics for a numeric variable, {describe_distribution} from {parameters} 📦 is your friend 🙌
https://t.co/KlhJNsdL90

Also works with a {grouped_} dataframe from {dplyr} 👏

#rstats #DataScience

[R Function A Day @rfunctionaday]

This function no longer resides in {parameters} 📦.

It can now be found in {performance} 📦:

https://t.co/cpKFArzfmk

[R Function A Day @rfunctionaday]

Factor analysis (FA) can help reduce many features to a few latent features. But one first needs to check if data is suitable for FA.

The {check_factorstructure} function from {parameters} provides an informative and verbose way 🔍

https://t.co/MNQZMkum30

#rstats #DataScience

[R Function A Day @rfunctionaday]

@IsmaelLCalandri @patilindrajeets

[R Function A Day @rfunctionaday]

Today concludes this 1-year hobby project.

There won’t be new posts, so feel free to unfollow, but do keep revisiting! 🙃

With > 22K followers in 365 posts, I guess you enjoyed reading them as I much as I’d preparing them. 😅

Best luck with your jouRneys! 🤞
@patilindrajeets

[R Function A Day @rfunctionaday]

@malte_grosser @patilindrajeets Ask and ye shall receive 😅

https://t.co/ziDsn8dFCR

Thanks a lot for the suggestion! 🙌

[R Function A Day @rfunctionaday]

@malte_grosser @patilindrajeets Good idea!

Might work on that soon, but until then this timeline widget should come in handy 🧵

https://t.co/rMckH9wIXP

[R Function A Day @rfunctionaday]

@Bishal_Bhardwaj @patilindrajeets The tweets from the past will always be accessible. They will neither be removed nor changed in any way.

[R Function A Day @rfunctionaday]

@GentForAnth @patilindrajeets

[R Function A Day @rfunctionaday]

@fedenichetti @patilindrajeets

[R Function A Day @rfunctionaday]

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} 📦 provides a summary of data types to check this! 🍎🍏

https://t.co/88zYQFdIWa

#rstats #DataScience

[R Function A Day @rfunctionaday]

@JonGretar @kiwiSteveTaylor @rstats4ds In real use cases, this routine will actually be used to access a variable - specified by the user - from a data frame.

Note that now `data$x` won’t work because we don’t know a priori what `x` is going to be.

[R Function A Day @rfunctionaday]

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} 📦 provides a more readable syntax to this end! 💄

https://t.co/rCT1vcMZzX

#rstats #DataScience

[R Function A Day @rfunctionaday]

@ThomVolker Yes, I have shared it in the past 👇

But, AFAIK, that operator is used for side effects. So you will be able to print that column but won’t be able to assign it to an object. I think.

[R Function A Day @rfunctionaday]

Although a number of functions tend to have a {data} argument, some don’t. For such functions, the pipe operator (%>%) from {magrittr} 📦 won’t work.

In such contexts, one can use the exposition pipe operator (%$%) 👏

https://t.co/1RODRqilaL

#rstats #DataScience

[R Function A Day @rfunctionaday]

Visualizing data along an Archimedean spiral can efficiently reveal periodic patterns in time series data.

The {spiral_*} function family from {spiralize} 📦 draws such spiral plots flexibly! 🌀

https://t.co/5vybsvWv2e

#rstats #DataScience

[R Function A Day @rfunctionaday]

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} 📦 provides a performant way to serialize or deserialize any R object! ⚡️

https://t.co/i8BNgtAQWw

#rstats #DataScience

[R Function A Day @rfunctionaday]

Sometimes you may wish to include some patterns or images in plots for enhanced storytelling.

The {image*} or {pattern*} function family from {patternplot} 📦 provides a way to do so! ⚜️

https://t.co/lRhdnmbQoQ

#rstats #DataScience

[R Function A Day @rfunctionaday]

@Fischuu None at all. In fact, AFAIK, the implementation of this data type in {reticulate} is based on names lists.

Dictionary just provides a familiar name for bilingual users to a data structure that is not native to R but can be easily implemented.

[R Function A Day @rfunctionaday]

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} 📦 gives you access to this data type in R! 📖

https://t.co/stxGhcedjI

#rstats #DataScience

[R Function A Day @rfunctionaday]

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} 📦 does exactly this! ♾

https://t.co/mrWehQheOi

#rstats #DataScience