Thread by @paolodonorio

Are you a data scientist?

.

You most likely estimated or felt that coding in #Python
is harder than it really is

.

see #thread 👇🏼

Let me guess.

You may be a novice programmer,
or have no coding experience at all.

That's all right,
but it turns out you need to do #data #analysis.

Maybe you’ve been already using Excel for that.

You have a chaotic group of folders,
where you keep stacking all statistics that you've managed to complete so far.

But you can't, for the life of you, find a sheet tab
where you already plotted that pie chart you need again.

Excel does allow you to code, somewhat.

If you go down that path you would have to learn all the tricks
to squeeze the best out of the tool,

without realising that at the end of the road
there's a wall built on Excel's limitations.

And then you’ve been hearing about Python
or some other scripting language.

You’re not sure what “scripting” is, though.

As anyone new to something, you don't really know where to start.

How do you get #Python in your laptop?

And even if you accomplish that task,
how can you learn the basics of writing code?

You may start searching for cheap video course offers
or look for tutorials.

You can't believe the huge amount of time
it takes you to find one that looks at least promising.

Most of the times they are either too simple, or too complex

You have now some bookmarks with things to read on Python.

If you read two different sites they give you different explanations for the same functionalities.

Things are a matter of perspective and this undermine coherence.

And at this point it should be clear enough

that you can't possibly jump into a new science
(programming)

with no directions, no experience,
and pushed by a (close) deadline.

Good news is that #Python has proven to be
(at least in my 20+y exp)
one of the best languages for beginners.

It comes bundled with:
- simplicity
- forced best practices (e.g. indentation for blocks of code)
- keywords as close as possible to natural english
- its own "zen"!

Here are my few suggestions to start thinking differently of the problem:

1. ALWASY dedicate a fixed amount of time (e.g. 1h per day) to learn something new. Have a reachable goal and take a fair deadline to reach it (e.g. 1 month).

2. Things take time to learn.

The less shortcuts you take (e.g. copy/paste from stackoverflow) in the beginning, the better.

That's how you really get to slowly master the tools you use.

3. Whatever you do for learning, it has to be fun.

You learn faster if you enjoy the time while you practice.

The goal/project you decide to pursue is the key here. The wrong one may stop you from growing now and in the future, because of the frustration.

4. If you want to learn Python, do not even install anything.
There are different way you can test it for free in the cloud.

Recommended way is to head to jupyter.org/try
and click “Try classic notebook”.

You would get access to a web page that interprets python code.

If the above one does not work,
the most notable alternative to @ProjectJupyter notebooks
is the @GoogleColab service,
where you get the magic notebooks inside google cloud.

5. if all of this sounds interesting to you,
you may want to follow me and my datanote.me blog
(proudly powered by @Ghost)

or subscribe to ol'good RSS feed:
datanote.me/rss/