PCA stands for Principal Component Analysis. It is a statistical technique which primary goal is to identify the underlying structure in the data by creating a new coordinate system that emphasizes the most important features of the data.

It isoften used to reduce the dimensions of a large data set by transforming it into a smaller set of uncorrelated variables called principal components.

Lorenz curve and Gini coefficients are statistical tools generaly used to measure inequalities in the income distribution of a population.

When writing complex code, it almost never can be done in one unique sequence. Often some operations need to be repeated or executed conditionnaly. Control flow in python work like most languages, using a collection of statements introduced by specific key-word.

It is easier than it sounds and is best explained with example.

Context managers allow to manage external ressources. It usually works with ressources that need to be opened, managed and then closed. The with statement allow to work specific objects for which a context manager exists.

In any given language, errors are a feature that let you know that something that you might not have expected occured. It is important to know how to handle and use them correctly.

Collections in Python are containers that are used to store collections of data, for example, list, dict, set, tuple etc. These are built-in collections. Several modules have been developed that provide additional data structures to store collections of data.

Lists are mutable sequences, typically used to store collections of homogeneous items (where the precise degree of similarity will vary by application).

They are one of the most commonly used collection in python. They are extremely flexible, intuitive and easy to use.

So much so that other more specialized collections tend to be overlooked and lists drawbacks too easly forgotten.

Tuples are immutable sequences, typically used to store collections of heterogeneous data. Tuples are also used for cases where an immutable sequence of homogeneous data is needed.

A set object is an unordered collection of distinct hashable objects. Common uses include membership testing, removing duplicates from a sequence, and computing mathematical operations such as intersection, union, difference, and symmetric difference.

The set type is mutable — the contents can be changed using methods like set.add and set.remove. Since it is mutable, it has no hash value and cannot be used as either a dictionary key or as an element of another set.

A mapping object maps hashable values to arbitrary objects. Mappings are mutable objects. There is currently only one standard mapping type, the dictionary.

A dictionary’s keys are almost arbitrary values. Values that are not hashable, that is, values containing lists, dictionaries or other mutable types (that are compared by value rather than by object identity) may not be used as keys. Numeric types used for keys obey the normal rules for numeric comparison: if two numbers compare equal (such as 1 and 1.0) then they can be used interchangeably to index the same dictionary entry. (Note however, that since computers store floating-point numbers as approximations it is usually unwise to use them as dictionary keys.).