Introduction to Python Variable Types
The following article, Python Variable Types provides an outline for the types in python. Perform an essential part in many programming languages, and Python is not an exception. A variable enables you to store value by simply assigning this to the identity, which may be utilized to label the value afterward inside the program. A Python handles type is different from a number of other programming languages. In many programming languages, including Java or C#, you have declared a variable type before you declare the variable itself.
That variable type can be an int, float, string, char, bool and many others.
In Python, it is not necessary to declare a type anywhere. In fact, you would declare variables like this.
Explain Different Python Variable Types
Below are the types of Different Variable types:
1. Python Integers and Floats
Integers are numbers and floats are decimal numbers. Defining integer or any other type in Python for it is very easy. Simply the type variable name and assign its numerical value.
Example #1
Integers are a number that can be positive or negative or 0, but they cannot have a decimal point. They have unlimited precision and support all kinds of mathematical and arithmetical operations such as addition, subtraction getting remainder, the absolute value of the number and more. Floats are decimal. They support the same operation as integers.
Example #2
Python is not going to complain about you adding two different types and whatnot. It will produce the desired result. The integer type is int, and the floating number type is afloat. These types names to convert or cast a variable to an integer or to afloat. Simply surround your variable with int or float to convert it.
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Example #3
2. Strings
We make use of strings to symbolize text. Automatically, it is Unicode text in Python 3 yet ASCII text through Python 2. Strings can be defined using single quotes, double quotes, or three times the quotes, either single or double. You cannot find any main difference in what type you utilize.
Example #1
Python support many methods including many useful utility methods. Some of them capitalize, which will make the first character a capital letter. replace() method takes two arguments, the first one being the character to be replaced and the second one is the character to replace it with. Then we have alpha() or isdigit() which will return true if all characters are letters or digits respectively.
Example #2
3. Boolean and None
Boolean indicates a True or a False value. You can assign any variable to be true or false, and declaring a variable as a Boolean.
Example #1
Simply type the variable name and assign it True or False. Boolean in Python compared to most other programming languages. They both start with a capital letter T and F for True and False. You can convert a Boolean to an integer, and it will give you a value of 1 if True or 0 if False. However, converting True or False to a string will simply give you a textual representation, so a string with value True or False.
Example #2
None is similar to null in other languages. It denotes that a variable has been defined so that we, the developers, have typed the name of the variable somewhere, but that is not associated with any value.
We found no aliens so far,
Example #3
4. Lists
To define a List in Python, write a variable name and assign it empty square brackets. There, you have just created an empty Python List.
Example #1
We replace our empty brackets with John, Sam, and Michal. Now our List has three string elements.
Example #2
In order to access an element in a List, we use something called an index. An index is an integer value starting from 0, which corresponds to 1 and just one element in the List. For our List, if we wrote code such as person_names[0], we would get John. If we wrote code names such as person_names[2], we would get Michal.
Example #3
The important note here is that the List indices in Python start with 0. So even though we have John as our first element, the index is 0. The next element, Sam, which is our second element in the List, has an index of 1, and so on. Replacing an element in the List is also as easy as checking for a specific List element. So let’s say person_names[0] = Dennis. If we now print person_names, we see that John is gone and that Dennis took his place.
Example #4
We can’t do person_names[3] = Patrick, but we can add in a built method in our List called append(). We can pass any object we want to the append method as its argument. Once we do that, the object we have passed through the append is added at the end of our existing List.
Example #5
Lists in Python are very similar to arrays in many other languages, but they come with some added benefits. Having multiple data types in a single List is just fine. If you delete any person_names[2] just put the del keyword.
Example #6
5. Dictionaries
We wanted to add more details other than just the name to a single person like a person id, but we still want the person id to be associated with the name. We can use a dictionary in that case. In the Python dictionary, we have keys and values. In our case, the keys are name, person_id, and feedback, and the values are Dennis, 25467, and None.
Example #1
A key and a value make a pair or more precisely a key-value pair. Each key is going to correspond to one value. Now the value can be of any type. Just like with Lists, we can just add any type we want. Dictionaries are very useful when it comes to storing some kind of structured data.
- List of Dictionaries
- If we want to group multiple dictionaries together, we simply create a List of Dictionaries.
- Notice that we do have square brackets here defining a List.
- Then we can iterate through the list and use the data each dictionary contains.
6. Top 4 Other Data Types
1. Complex: We also have a type called complex, which denotes complex numbers. And Python 2 had a type called long, which doesn’t exist in Python 3 anymore.
2. Bytes and Bytearray: It was replaced by the integer. Then in Python 3 at least, we have bytes, which are essentially a sequence of integers in the range of 0 to 255
3. Tuples: Which are similar to Lists but are immutable. You cannot change their values.
4. Set and Frozenset: Finally, we also have sets and frozen sets, which are again similar to Lists, but they only have unique objects.
Conclusion
Python is among the effectively typed languages, which usually imply it does not have to declare a variable prior to utilize it. The data types are often like different programming languages. Rather than their strengths, there exist a few weaknesses that may trigger issues in the long term.
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