Python’s five data types
In the process of learning a language, you must first be exposed to the data types it has. Python has five main data types. Type, let me introduce my understanding and thoughts on these five data types.
1. Numbers
Numbers in Python are mainly divided into four types: int (integer), float (floating point number), long (long integer) and complex (plural number)
The main special thing is that there is a function round() for float type numbers that can be rounded: round(a,b): operates on the float type value a, retaining b digits after the decimal point Significant digits, rounded, default is 1.
The complex type is also quite special.
2. String
Direct example: s='string' s=''string'' s1='''string'' ', these three effects are the same. In Python, quotation marks, double quotation marks, and triple quotation marks are all correct usages to represent strings.
Strings in Python can be directly added: s+s1 #Return a new string 'stringstring'
Below we can perform a "slicing" operation on the string, so-called Slicing is equivalent to cutting off a slice of a long loaf of bread. For example, if we want to get the 2nd to 5th characters in the s string, it is more troublesome in other languages, but in Python, we can easily perform this operation.
Example: s[a:b:c] a represents the starting position of the slice. When it is 0 or a positive value, it is indexed from left to right (the default starts from 0). When it is a negative value, it is indexed from right to left. (Default starts from -1)
b indicates the end position of the slice, but does not include the end position. The mantra is "Look at the head but not the tail". The default is until the end of the index.
c represents the step size, the default is 1, and when it is a negative number, it is intercepted from right to left.
When there is no colon, it is a normal index operation: s[0] #s
cThe default is 1: s[1:5] #trin (note "Look at the head and ignore it" "Tail")
s[-3::]: Starting from the third character from the right (there is no 0th character!!!), intercept to the right until the end #ing
s[-3::-1]: Starting from the third character from the right, intercept to the left, b default: until the end #irts
Now that we have an understanding of simple slicing operations, we Let’s talk about a few commonly used functions (there are actually a lot of operating functions, but some are not used frequently, so you can learn more if necessary)
len(): Returns the length of the string. len(s) #pytnon is different from C. The length of the string does not need to be increased by 1. This is 6.
replace(a,b): Replace a string with b string.
3. List
Directly to the example: s=['string','python',2001,52.5], s1=[2002,5658 ]
In Python, the List type is enclosed in square brackets and can include string types and number types, separated by commas.
Access operations in List: s[1] # Return a python string. It can be compared to the string type
List also has update and delete operations: s[1]=2002 #The first element (starting from 0) of the 'python' string in list s is replaced with 2002.
del s[1] #The first element of list s is deleted
Briefly introduce the functions and methods of several operations:
1, append() #In Append elements after the list
2. extend() Example: a.extend(b) #Add the elements of list b to the end of list a
3.pop() #Add the elements of list b to the end of list a. An element pops up
1, sort() #Sort the list, but it seems that you need to specify the sorting rules.
2, count() #Count the number of times a certain element appears
3, index() #The element i at index
4. Tuple (Tuple)
Just go to the example: s=('string','python',2001) s1='string','python',2001
Tuples in python are more interesting. It is correct to add parentheses or not. Separated by commas, tuple by default.
Tuples have a special rule: the elements in the tuple are not allowed to be modified.
The access operation can also be similar to the string type.
The following are examples of tuples and lists:
1, (1,2,3)+(1,2,3) #(1,2,3,1, 2,3) Addition operation
2, [1]*3 #[1,1,1] Multiplication operation
3, 1 in [1,2,3] #true judgment Operation
4, for i in (1,2,3)
print i #1
#2
#3 Loop operation
5. Dictionary
The above example: dict={'abc': 123, 'ji': 'kp', (1,2):
5}
Typical key-value type data, please note a few points: the value of key must be unique, but the value of value may not be unique. Use curly braces to include. End with a semicolon after the curly braces.
Access: dict['abc'] #123
Modify: dict['abc']=153 #Modify the 123 corresponding to 'abc'
Delete: deldict[ 'abc']
Special points:
1. The same key cannot appear twice. If multiple assignments occur, the one that appears later shall prevail
2. The key must be immutable and can be used as a number, string, or tuple, but a list cannot!
Method introduction:
1. clear() #Clear dictionary
2.get() #Value example :get('abc') #Return 123 get('ashudya')#Return none
3, keys() #Return a list containing all key values in the dictionary.
4. value()# Returns a list containing all value values in the dictionary.
5. fromkeys() #Put a list into the dictionary as a key.
fromkeys([1,2,3],0) #0 is value
The dictionary can be expressed as: {1:[0],2:[0],3:[0]}
The five data types are the cornerstone of learning Python, and they are not very difficult to master. , start with the simple ones, and learn more if necessary!
Thank you for reading, I hope it can help you, thank you for your support of this site!
Articles you may be interested in:
A brief discussion on Python data type judgment and list script operations
In-depth understanding of Python data type lists
A brief discussion Conversion between Python data types
Detailed explanation of Python data types (4) Dictionary: dict
Detailed explanation of Python data types (3) Yuanzu: tuple
Detailed explanation of Python data types (2) List
Python data types Detailed explanation (1) String
Python data type study notes
A brief introduction to several data types in Python
The differences and usage of the built-in data types list, tuple, dict, and set in Python
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