First, this quote:
"All your suggestions were great if I had wanted to do a systematic study and truly understand. The goal is to understand and learn as little as possible to be able to undertake the code challenge for [a specific job opportunity]."The subject of systematic study is Python. The focus of learn as little as possible is Pandas.
The goal is more-or-less impossible. Focus on a specific code challenge will devolve into other aspects of the language. Or. It will lead nowhere.
Also. I'm not sure what a "systematic study" is. From the omitted back-story, I'm seems clear to me that the advice to "read a tutorial" is restated here as "systematic study." And is unacceptable. I guess because of time constraints.
It gets better.
"For now, I am just going to follow the pattern and get stuff to work."This is the ideal way to be defeated by technology. The "pattern" is defined to a large degree by the programming language. The two are inextricably linked. Trying to identify a pattern in programming that's magically not part of the implementation language seems deranged.
Learning Pandas isn't simple. There's no royal road.
The real crux are several questions that are difficult to reproduce, so I'm forced to summarize.
- What does name.name().name().name() mean? How can you call multiple methods "simultaneously"?
- What is the range of values for some parameter?
And the capper.
- I understand object.method().method(). I cannot understand object.name -- how can a method have no ()'s?
I'm sorry, but, the advice still stands. These are not questions that can be answered in a vacuum. This is serious -- and foundational -- object-oriented programming. Each of these small things was a total show-stopper, leading to four emails merely to clarify the question. Then more when the answer was rejected as not consistent with something, or astonishing, or
For the name.name().name(), the answer "Google Fluent Interface" was too complex. Code examples were requested to show how it was possible for an object to return another object that had methods.
Advice to use Python's >>> prompt and the dir() function were apparently part of "systematic study" and not part of "learn as little as possible."
For the range of values of a parameter, the answer "read the source" was a non-starter. Reading the source was flat-out rejected as not making any sense. I finally had to actually provide the link to the source repo for Pandas before it became clear what "open source" even meant. This was found to be nothing short of astonishing. The side-bar conversation on "how is this even possible?" was confusing to me because -- sadly -- I assumed people knew that the words "open" and "source" together meant that the source was open for inspection. My assumption was wrong. At least one person did not know this. That means there are others.
Finally. For the "capper" question. The exchange really did include this: "The dot notation I thought was Object.Method.Method."
A great deal of the back-and-forth amounted to "I reject anything other than fluent methods because that's the only thing I've decided to understand." Words like "property" and "attribute" were ignored as noise, AFAIK.
I say "amounted to" because a lot of the back-and-forth was restating the question. Other parts were exchanging links to the Pandas documentation in an effort to follow the "learn as little as possible" strategy. Any link to a tutorial would be "systematic study". Any link to Pandas, however, was acceptable. But (of course) confusing because the Pandas documentation assumes a modicum of language knowledge.
Here's what appears to be the problem: it's impossible to learn a complex tool like Pandas without starting with a basic understanding of Python.
I don't think I've ever seen it suggested that one can leap into a package without knowing the language. I'm not sure how one can develop the idea of learning as little as possible in the first place. But, there it is.
There's at least one person who thinks they can learn as little as possible and still get Pandas code to work. That likely means there are others.
It appears there's a market for books like
Learn as little Python as possible to be able to use Pandas
Learn the least Java necessary to make Spark work
The Royal Road to Data Science
I'm not sure I'm capable of writing books like these, but for someone who does, it might be a really lucrative line of books.