Python3.9有什么新的变化

Across a breadth of industries, the world’smost successful companies, from Facebook to Amazon to Netflix, cite data as the mostprized asset in their portfolios. United Nations Secretary-General António Guterrescalled accurate data “the lifeblood of good policy and decision-making.” Data powerseverything from movie recommendations to medical treatments, from supply chainlogistics to poverty-reduction initiatives. The success of communities, companies, andeven countries in the 21st century will depend on their ability to acquire, aggregate,and analyze data.

Across a breadth of industries, the world’smost successful companies, from Facebook to Amazon to Netflix, cite data as the mostprized asset in their portfolios. United Nations Secretary-General António Guterrescalled accurate data “the lifeblood of good policy and decision-making.” Data powerseverything from movie recommendations to medical treatments, from supply chainlogistics to poverty-reduction initiatives. The success of communities, companies, andeven countries in the 21st century will depend on their ability to acquire, aggregate,and analyze data.

Across a breadth of industries, the world’smost successful companies, from Facebook to Amazon to Netflix, cite data as the mostprized asset in their portfolios. United Nations Secretary-General António Guterrescalled accurate data “the lifeblood of good policy and decision-making.” Data powerseverything from movie recommendations to medical treatments, from supply chainlogistics to poverty-reduction initiatives. The success of communities, companies, andeven countries in the 21st century will depend on their ability to acquire, aggregate,and analyze data.

A helpful way to think of objects is as digital building blocks. Consider a spreadsheet software like Excel. As users, we can discern the differences among a workbook, a worksheet, and a cell. A workbook holds worksheets, a worksheet holds
cells, and cells hold values. We view these three entities as three distinct containers
of business logic, each with a designated responsibility, and we interact with them
in different ways. When building object-oriented computer programs, developers
think in the same manner, identifying and building the “blocks” that need to exist
for a program to run.

As a data analyst turned software engineer, I’ve witnessed the Python proficiency
requirements for many roles in the industry. I can state from experience that you do
not need to be an advanced programmer to be productive with pandas. Basic understanding of Python’s core mechanics, however, will significantly accelerate the speed
at which you can pick up the library. This appendix highlights the key language essentials you need to know to be successful.

  Suppose that we decide to measure our town’s daily temperature for a week but
forget to take a reading on Friday. The temperatures for six of the seven days would be
integers. How could we log the temperature for the missing day? We might enter
something like “missing” or “unknown” or “null”. The None object models the same
idea in Python. The language needs something to communicate the absence of a
value. It requires an object that stands in and announces that a value is missing, does
not exist, or is not needed. Jupyter Notebook outputs nothing when we execute a cell
with None:

Operators
An operator is a symbol that performs an operation. One classic example from elementary school is the addition operator: the plus sign (+). The values that an operator
works on are called operands. In the expression 3 + 5,
 + is the operator.
 3 and 5 are the operands.
In this section, we’ll explore the various mathematical and logical operators built into
Python.