tesla | Tesla client API | REST library

There are two problems:

• the values need to be numeric, now they are strings
• the individual values shouldn't be put into lists, they need to be just one number, e.g. taking the sum of all values belonging to the same category

As the original data only has one entry per category, the following example adds an extra 'Tech'.

TL;DR - the best solution is in the end.

The most straightforward way would be to go over your data and append rows one by one:

If I understand you correctly, one way to get the company's US GAAP taxonomy concept extensions (there may be others) is to do the following. Note that the data is in xml format, not json, so you will need to use an xml parser.

If you look at the company's 10-K filing for 2020, for example, you will notice that, at the bottom, there is a list of data files, the first one described as "XBRL TAXONOMY EXTENSION SCHEMA" and named "tsla-20201231.xsd". That's the file you're looking for. Copy the url and get started. BTW, it's probably possible to automate all this, but that's a different topic.

Well, having (let use named tuple to demo):

If original ordering is not important, use DataFrame.stack:

As you can see in the documentation, you can use the Reads typeclass to define the way to decode types from JSON.

Your first solution is incorrect given that you required a non editable BRAND for an electric car.

Your second solution just doesn't work at all excepted if you override both getter and setter of brand field to use your static field, which is not "elegant and mantainable"

Your third solution doesn't make use of object oriented concept.

A simple solution I would use is to let the field brand and its getter in Car superclass, but I'd only define the setter in the CombustionCar class. Alternatively, if you extend your model, you could create an intermediate abstract superclass "FreeBrandCar" which implements the setter.

Solution with the setter in CombustionCar

Provided you only want to "merge" company names one could do that in a linear time with pure Python.

Skipping the beginning of sentence token [CLS] for brevity:

Query

• lookup with it self, join only with the type that the id=3 has.
• empty join results => different type so they are filtered out

Test code here