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Data types in 1-1 Python

I. Integer number

Python can handle integers of any size, including negative integers, of course.

① ordinary integers: written in the same way, for example: 1 meme 100 meme pi 8080 pi 0.

② hexadecimal: denoted by the 0x prefix and 0-9 memarelf, for example: 0xff00rect 0xa5b4c3d2, etc.

2. Floating point numbers

① ordinary floating-point numbers: write directly in mathematics, such as 1.23, 2.14, 1.14, and so on.

② scientific counting: replace 10 with e, that is, 1.23x10 ^ 9 as 1.23 billion or 12.3e80.000012 as 1.2e-5

Note: integers and floating-point numbers are stored in different ways inside the computer, and integer operations are always accurate (is division also accurate? Right! While floating-point operations may have rounding errors

III. String

The ① string is any text enclosed in''or''.

For example, 'abc', "xyz and so on. The string 'abc' has only three characters: a _ line _ b _ menc.

4. Boolean value

① in Python, you can directly use True, False to represent Boolean values (please note case)

② is calculated by Boolean operations.

③ Boolean values can be calculated with and, or, and not.

The and operation is the and operation, and the result is True only if all operations are True,and.

The or operation is an OR operation, as long as one of them is True,or and the result is True.

The not operation is a non-operation. It is a unary operator that turns True into False,False and True.

5. Null value

A null value is a special value in Python, represented by None.

None cannot be understood as 0 because 0 is meaningful and None is a special null value.

1-2:print output

The ① print statement outputs the specified text to the screen. For example, output 'hello, world''

② print statements can also follow multiple strings, using commas, "separate, encounter commas," and "output a space so that you can concatenate a string of outputs:"

③ print can also print integers or calculate results

1-3 variable

① variables can be not only numbers, but also any data type.

② variable names must be a combination of uppercase and lowercase letters, numbers and underscores (_), and cannot start with a number

③ in Python, the equal sign = is an assignment statement that can assign any data type to a variable, the same variable can be assigned repeatedly, and it can be a different type of variable (dynamic language).

1-4 string

If the string contains ", we can enclose it in''.

"escape" some special characters of the string, and the Python string is escaped with\:

\ 'means'\ "represents"\ n means newline\ t represents a tab\\ represents the character itself.

1-5 output string

① if a string contains many characters that need to be escaped, add a prefix r to the string to indicate that it is a raw string, and the characters in it do not need to be escaped

② represents a multiline string, and you can use''...''. Express

③ uses the word "ritual". Turn a multiline string into a raw string

④ output Chinese: add a comment on the first line: #-*-coding: utf-8-* -, and then use uplink.. output, the rest as above

Operation of 1-6 integers and floating point numbers

The result of integer operation is still integer, the result of floating-point operation is still floating-point number, but the result of mixed operation of integer and floating-point number becomes floating-point number.

1-7 Boolean operation

An important rule of and and or operation: short circuit calculation.

When ① calculates an and b, if an is False, then according to the and algorithm, the whole result must be False, so it returns a; if an is True, the whole result must depend on b, so b is returned.

When ② calculates an or b, if an is True, then according to the OR algorithm, the whole result must be True, so it returns a; if an is False, the whole result must depend on b, so it returns b.

Chapter II List, tuple, dict, set

The search speed of dict is fast, but it takes up a lot of memory, while the search speed of list decreases gradually with the increase of elements, but takes up less memory.

List: orderly, variable

Tuple: ordered, immutable

Dict: unordered, key cannot be repeated and immutable (so list cannot be used as a key)

Set: unordered, elements are not duplicated and cannot be modified, but can be added and deleted

2-1 List

A list is an ordered collection of elements that can be added and removed at any time. The elements contained in list do not have to be of the same data type, and we can include all kinds of data in list.

Create L = ['Michael', 100, True].

Check: positive order access examples: l [0], L [1]. Because the list is an ordered collection, the specified elements in the list are accessed by index. When using an index, be careful not to cross the line.

Reverse order access examples: l [- 1], L [- 2]. The penultimate is represented by-1 and the penultimate second by-2. When using inverted indexes, you should also be careful not to cross the line.

Add: ① L.append (element) method to append new students to the end of list

The ② L.insert (n, element) method, which takes two parameters, the first is the index number, and the second is the new element to be added. The element with the original index n, and all subsequent elements, automatically moves one bit backward.

Delete: the ① L.pop () method always deletes the last element of list, and it also returns this element

The ② L.pop (n) method deletes the element with the index n of list, and it also returns this element

Change: assign a value to an index in list, you can directly replace the original element with a new element, and the number of elements contained in list remains the same.

2-2 Tuple

Tuple is another kind of ordered list, and tuple is very similar to list, but once tuple is created, it cannot be modified. The only difference between creating a tuple and creating a list is that [] is replaced with ().

Create: t = ('Adam',' Lisa', 'Bart')

Check: t [0], t [- 1] index to access elements

Cannot add, delete or change.

Variable tuple:

T = ('axed,' baked, ['Agar,' B']) L = t [2 L [0] = 'XeroL [1] =' Y' output t: ('averse,' baked, ['Xerox,' Y'])

2-3 dict

Curly braces {} indicate that this is a dict, then follow key: value and write it out with a comma. The comma for the last key: value can be omitted.

The first feature of dict is its fast search speed, regardless of whether dict has 10 elements or 100000 elements. The disadvantage of dict is that it takes up a lot of memory and wastes a lot of content. On the contrary, list takes up a small amount of memory, but the search speed is slow.

In a dict, key cannot be repeated; key-value pairs are out of order, and elements as key must be immutable

Create: {key: value,}

D = {'123 key: [1, 2, 3], # key is str,value is list 123: # key is int,value is str (' await,'b'): True # key is tuple, and every element of tuple is an immutable object, value is boolean}

Check: ① dict uses d [key] to find value. But to determine whether key exists first, use if 'Paul' in d:

② uses a get method provided by dict itself. If Key does not exist, it returns None with print d.get ('Paul').

None

The ③ dict object has a values () method, which converts the dict into a list that contains all the value, so we iterate over each value:d.values () of the dict.

In addition to the values () method, ④ dict also has an itervalues () method, which replaces the values () method with the itervalues () method, and the iterative effect is exactly the same, but the itervalues () method does not convert the dict into a list that contains all the value. It fetches the value from the dict in turn during the iteration, so the itervalues () method saves the memory needed to generate list than the values () method.

⑤ iterates through both key and value:

D = {'Adam': 95,' Lisa': 85, 'Bart': 59,' Paul': 74} print d.items () outputs: [('Lisa', 85), (' Adam', 95), ('Bart', 59)]

As you can see, the items () method converts the dict object into a list containing tuple, and we iterate over this list to get both key and value. Similar to values () has an itervalues (), items () also has a corresponding iteritems (), iteritems () does not convert dict into list, but keeps giving tuple during the iteration, so iteritems () does not take up extra memory. So we can:

For k, v in d.iteritems (): print k recorder

The output is:

Lisa: 85Adam: 95Bart: 59 add: d [key] = value traversal: for key in d: print key,d [key]

2-4 set

Set holds a series of elements, much like list, but the elements of set are not repeated, are unordered, and cannot be modified. This is very similar to dict's key. When we pass in a list that contains repeating elements, it automatically removes the repeating elements.

Create: the element that calls set () and passes in a list,list will be the element of set

Example: s = set (['A','B','C'])

Check: because set stores unordered collections, we cannot access them by index. Accessing an element in set is actually determining whether an element is in set or not. Example: print 'A'in 's output: True

Traversing: for name in s: print name

Added: s.add (element). If the element is already in set, it will not report an error.

Delete: s.remove (element). An error will be reported if the element is not in set, so you need to judge the if element in s first:

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