to “complete” “slicing” DataFrames, i discuss loc and iloc. i think this enough to cover the “basics” of Python. as you know, i will start trying to delve into statistics to a.) further my skills, and b.) see if i can be “useful” to my wife.

i was always planning to tackle “advanced” topics -it was just “accelerated” sooner rather later.

here’s something i “shared” so i can “move on” to statistics :

https://github.com/LinsAbadia/Python/blob/master/DataFrames/LocVIloc.ipynb

That said, i can consider revisiting “past” topics based on feedback.

i did a lot of coding in my time and was introduced to neural networks at school so it wasn’i really a stretch learning Python. i only knew aspects of statistics so it became obvious to me that it was something i had to strengthen to upgrade my data science skills because i had a lot of exposure to programming and a little background on artificial intelligence – let me preface it by saying, it’s been awhile since i’ve “actively” done both and technology has advanced, that said, i’ve been developing a GitHub repository because i believe the expression that says you teach best what you need to learn.

to brush on the basics and truly understand Descriptive Statistics i’m perusing version 2 of the ebook Think Stats: Exploratory Data Analysis by Allen B. Downey. it’s supposedly framed for programmers and better suited for them in learning statistics.

aside from personal growth, my wife (although she’s well versed in machine learning and teaching programming) and her work team are looking at doing some research that may require this. so there’s a greater incentive to study this.

since i mainly use a Jupyter notebook for Python coding, i use the print() function a lot to help with “debugging”. Error “detection” has a lot to be desired (that’s one of my only complaints. i lean towards it being used to introduce programming).

here are a “few debugging tips” that would have handy to know in learning how to code in Python:

https://github.com/LinsAbadia/Python/blob/master/DataFrames/Debug.ipynb

in “major” databases there is sometimes an ETL (Extract,Transform, Load) tool. as DataFrames are the “commonly” used data structure in Python for similar operations (and analysis), you can perform all three functions. That said, i prefer to only do the ‘E’ and ‘L’ as they are “simply” accomplished by built-in functions. The ‘T’ require me to use a for loop and read each row using a file handler, so it’s more “convenient” for me to manipulate the data once it’s imported.

it’s important to note that determining which dataset to use can involve unconscious/implicit bias. therefore in analysis (and offering insights), you need to consider the source: no matter the prevailing “wisdom”, one needs to distinguish between fact and opinion.

here is the updated GitHub repository:

https://github.com/LinsAbadia/Python/tree/master/DataFrames

there are many ways to instantiate a DataFrame but here’a a primer on typical ways to create one.

the DataFrame is the primary data structure in Python for data science. it acts like a spreadsheet or database – it kind of reminds me of the Data Window object in PowerBuilder (it was very convenient for me). And unlike most high-level programming computer languages it didn’t need a “connector” (or driver) like ODBC (Open DataBase Connectivity) or JDBC (Java DataBase Connectivity) – you were lucky if there was a “native” one because it performed quicker as there was no need to “translate” stuff – to interact with external databases.

here is my updated GitHub repository:

https://github.com/LinsAbadia/Python/tree/master/DataFrames

when i started preparing stuff for DataFrames, it seemed sensible to introduce the Python Dictionary.

in it, i use the NATO alphabet, which as we all know is an acronym. Another form of an abbreviation is an initialism. Both utilise the first letter of words to form a “new” word but the former pronounces it as a word, while the latter is voiced by each initial (like AI for Artificial Intelligence).

as part of forming the subheadings, (although often used interchangeably) i discovered if i should use duplicate or replicate.

here’s the updated repository:

https://github.com/LinsAbadia/Python/tree/master/DataStructures

CAVEAT:  you might have noticed that my title format has slightly changed.  i’m still starting it off with what ever comes to mind and after the colon i’ve appended what i think the post is about (you might interpret it differently or have an alternative understanding when you “read between the lines”).  it has been brought to my attention that some readers may not want to go through the entire thing for the title to make any sense.  this is not an egregious attempt to increase ‘likes’  or to act as ‘click-bait’ but shouldn’t it be part of ‘sharing’ to make stuff ‘more digest-able’ – looks like i still have a ways to go.

i underwent a medical procedure recently – recovery time is typically from one to two days –  because of my age it took me three days. so i temporarily stopped my daily exercise program for about two weeks – this affected me but i didn’t notice right away.  it became first obvious to me at a speech pathology session.  i used to get through them just fine even if they were during the afternoons – i didn’t feel winded afterwords but my sound production performance faltered occasionally.  Moreover when i went to my regular neurophysio appointment, she could physically feel the difference – i found out that apparently pain can also cause your muscles to “relax”.  At first i had done this to reduce my anxiety levels (but perhaps because i now take a natural supplement for it it’s less pronounced) but, also very importantly, getting my core strength up not only helps me avoid falls (and minimises potential injury) but also helps my speech.  Suffice it to say i’ve started up again and hoping to get back to the level i once was.

these aren’t directly related but are also from recent “trips” outside my house so…

i want to whinge about the three (let me be clear: not all or even a majority of them) taxi drivers driving skills were really bad:  the sudden stops-and- starts, not slowing down enough to take a round about, or abrupt jerking of the steering wheel.  These gave me a headache despite sitting in front and having the road visible – imagine how much worse i would have felt if i sat in the back.  i was going to complain about another thing but in hindsight one of my drivers was “self-obsessed’ that he would have acted that way to an “able-bodied” passenger.

Despite using my “letter board”, some drivers (not only taxi drivers but one support worker), still misunderstood me.  i suspect it’s either because they’re not patient enough to listen or having a preconceived notion of what i’m going to say (Ding!  Ding!  Ding!:  it’s usually wrong).  i understand that my speech can be hard to understand especially since this is probably the first time we’ve talked (on a few occasions i get the same drivers) but mistakes ca be avoided:  like going the wrong direction, it’s on the other side, that’s the wrong address, accidentally running me over,  etc.

we just want to feel listened to.  here’s a video by Purple Orange (it kind of reminds me of the You Can’t Ask That format on the ABC) about diverse communication shared on Darryl Selwood(Ph.D.)’s blog:  http://darrylsellwood.com/?p=998.  While i don’t  relate to everything said, i agree with the central premise of respect and the underlying theme of “not judging a book by its cover”.

it is very easy for me to accuse the drivers of not thinking: parking too close to the incline, the ramp, or curb so it’s “tricky” for me to get into or out of the car;  dropping me off by an entrance with only stairs ; driving “far” the door so need to cross the street, walk “some” distance, or negotiate a challenging surface (like inclines, uneven surfaces, pebbles, etc.); ask me directions or instruct them where to pass or stop; or turn the meter on while i’m still trying to get in the car (i believe the law states it should be only activated when i’m seated).  sometimes they can’t be bothered or are in a rush but sometimes i think it’s because they haven’t been exposed to or educated about disability – these are tasks they take for granted so there’s a need for more “training”.

FINAL WORD (let me know if these prompt helps with readability or i should go for more “traditional” headings – i know a poll is a more suitable for this but i probably won’t get enough respondents for a truly statistically valid result and, frankly, confronting my readership numbers scares me).  There’s a tension between keeping the post short-and-sweet and making it comprehensive enough to be informative – after all like they say, perfect is the enemy of good. Moreover timing is an issue, some thoughts have an ‘expiry date’ while others not so much.  While Twitter isn’t for me (trolls aside), it take me some time to type – this has the added bonus of letting me reflect and not simply reacting, All-in-all, i’m still struggling with the balance.  Furthermore, i feel the pressure to post frequently – as evidenced by the number of “self-corrections” right after i publish – when i should learn to recheck my drafts first.