i’ve always wondered about this but not until i had to use it in my code did i bother to find out the difference. apparently, it’s just a spelling thing: “grey” is the preferred British way; while some Americans use “gray”.

i was originally from the Philippines and the educational system there is heavily influenced by the Americans, and have migrated to Australia awhile back – hence the “worsening” of my confusion.

it took me awhile to resolve the “s” and “z” (pronounced here as “zed”.

my speech therapist says it’s another “obstacle” for me in learning to speak again as my accent is somewhat “Americanised” and most words are produced differently in Australian-English.

i was so hung up on words that i “overlooked” visualisations can deceive audiences. i’ve been recently exposed to the works of Edward Tufte and Alberto Cairo on Information Graphics (commonly known by its portmanteau, Infographics). Aside from the important role it can play in emphasising statistics, it also has the power to mislead “consumers” of the information (whether intentional or not). The main point is that they need to be designed carefully and not simply thrown in to break the “monotony” of words or “pretty” things up – they must only be included to serve a particular purpose.

here are a few guidelines to help make the figure you generate “better”:


i’m currently taking: Applied Plotting, Charting & Data Representation in Python and have been introduced to a “relevant” model.

as validated by my years of professional experience in ICT, communication is a major part. as technologist, we almost only always focus on the processing and analyses of information. i’m glad that Data Science “explicitly emphasises” the importance of also communication of results. most people just refer to it as IT (but that IMHO is an “antiquated” form of thinking}. not just because it was “recently” rebranded as ICT by some governments and agencies, but because it highlights the other part of the equation and is a much more holistic approach to technology.

for your reference, here’s the Visualization Whee/ by Alberto Cairo:


i also added it to my GitHub repository:


i’ve “shared” something a bit unusual as this Jupyter notebook is comprised of all “Markdown” (and no Python Code) cells as it mainly talks about the initial step required referred to as data “cleaning”. some “transformations” are warranted after importing datasets before working with them or performing Exploratory Data Analyses.

as it is mainly words it may be “ambiguous” ( as everything seems “obvious” to me ) to some. kindly let me know if there are things that aren’t “clear” or can be explained much better so i can post these. or if you know of supplementary (hyper)links or other resources “freely” available online, please let me know so i can make sure to include them.

my updated GitHub repository is at:


yesterday there was a typo in my post’s title. it read: “”sing: on the “apptopriation” of St. Augustine’s singing quote and false claims by others.” the word should have been “appropriation” and not “apptopriation”.

i’ve rectified the post.

our parish priest of several years celebrated his farewell mass earlier because he’s been reassigned to PNG. this post isn’t about him but him ending his homily with a few quotes triggered my “tangentially-associative” memory.

i’m not terribly religious but had Augustinian priests for my primary and high school education. one of his quotes was deeply ingrained in me: “To sing is to pray twice”. i didn’t think i would be disturbed but a while back a contemporary personality effectively claimed that the quote was theirs and originated from them.

that was the first time i knew that a person “blatantly” appropriated someone else’s work – the interviewer didn’t challenge them. perhaps it was ignorance. perhaps they didn’t want the interviewee to be embarrassed.

my intent isn’t to shame anybody – in any case, i encourage everyone to share and spread individual’s words, works, ideas, or the like so that they are properly attributed. that said, let me qualify, some times somebody from another time or from a different part of the world may come up with a similar “thing” – the point is that their intent was never meant to “plaigarise”, it’s claiming something is theirs when they clearly know it’s not.

publicising something appears to be an “effective” remedy in dealing with or preventing its occurrence.

i looked into it (but i forgot to note where i got it from) as i was drafting a document and wanted to know the prescription when to fully spell out a number. as a “rule of thumb”, anything less than 10 (or less than multiple digits) merit using the whole word (although some style guides dictate that ten is still a “small” number but i don’t subscribe to this as it’s more cumbersome to generalise). for example, using one instead of the numerical symbol 1.

that said, you may decide to “break” this rule depending on your actual or planned readership. sometimes you need to know when it’s appropriate to break certain rules: just as when abstract painters eschew fundamental or standard techniques.

i’m not sure of “large” negative numbers though – my hunch is that maybe a “modified” rule applies depending on the number of digits. that is the “rule” for writing but, in my experience, different audiences have different expectations: case in point, writing for the web might require a different mandate. what about those containing decimal points? is there an exception for numbers in tables? variances can lead to strife. if you are aware of these (and other) guidelines, kindly share your knowledge…