Change Data Type in Python

4 Key excerpts on "Change Data Type in Python"

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  eBook - ePub

  Python for Beginners

  • Kuldeep Singh Kaswan, Jagjit Singh Dhatterwal, B Balamurugan(Authors)
  • 2023(Publication Date)
  • Chapman and Hall/CRC

    (Publisher)

  The second output line uses commas as separators. The third line runs the items together with an empty string separator. The fifth line shows that the separating string may consist of multiple characters. 2.9 Conclusion Data type in Python is a crucial term in programming. Variables can store a variety of data, and different data types can perform different tasks. A data type, also referred to as type, is a property of data that informs the interpreter or compiler about how the programmer intends to use the available information. The categorization or grouping of data objects is known as data forms. This denotes the type of value that determines which operations can be performed on a given collection of data. Data types are simply classes, and variables are instances (objects) of these classes, since everything in Python programming is an entity.

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  eBook - ePub

  Teach Yourself VISUALLY Python

  • Guy Hart-Davis, Ted Hart-Davis(Authors)
  • 2022(Publication Date)
  • Wiley

    (Publisher)

  price variable:

  type(price)

  This command returns the value’s class, such as <class 'int'> for the int data type or <class 'str'> for the str data type.

  Understanding Python’s Data Types

  Python includes various built-in data types designed for handling different types of data efficiently. For example, Python’s bool data type is designed for storing Boolean data, data that can be either True or False but no other possible value. Similarly, Python’s str data type is designed for storing strings of text.

  Python’s built-in data types mostly fall into six categories: numerics for numbers; sequences for data such as lists; mappings for dictionaries, where one item maps to another; classes for creating custom objects; instances for the objects created with those classes; and exceptions for handling errors.

  Understanding How Python Builds on the C Programming Language

  The Python programming language is primarily implemented using C, a long-standing and robust programming language that is still widely used across many industries. C is called a low-level programming language, which means that it can interface directly with hardware features, lending itself to software and operating-system development. C is relatively easy to understand but extremely hard to master.

  Python is a high-level programming language and includes many built-in features that C does not natively support, giving you an easier way to harness some of the power of C to develop solutions rather than using C directly. Python’s extensive feature set and capability to run well on many platforms contributes to its great versatility.

  Because Python is built on C, Python’s data types are constructed using combinations of C’s data types. For example, Python includes a data type called set

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  eBook - PDF

  Python Programming for Biology

  Bioinformatics and Beyond

  • Tim J. Stevens, Wayne Boucher(Authors)
  • 2015(Publication Date)
  • Cambridge University Press

    (Publisher)

  We can use as many different variable names as we like and assign their value based on other variables. For example, in the following we assign a value to x and then assign a value for y based on x: >>> x = 17 >>> y = x * 13 >>> print(y) 221 23 Introducing the fundamentals Unlike many computing languages, Python is not a language where you must initially specify, and then stick to, a given kind or type of data for a given variable. You could initially allocate a numeric value to ‘x’, without advance warning, and then later on change ‘x’ to some text. This differs from languages like C and Java, for example, where you would have to declare up front what type of data ‘x’ was to contain. In Python, the type of variable is specified by the type of whatever its value is set to. So if you redefine a variable its type may change. Although variables can change type, it is usually best to avoid that practice. >>> x = 4 # x is set to the integer 4 >>> 3*x 12 >>> x = 7.1 # x now set to the floating point number 7.1 >>> 3*x 21.299999999999997 The above example reminds us that floating point calculations are not always precise. The answer could also depend on the Python implementation and version. Simple data types As with other computer languages, Python has various simple, inbuilt types of data. These are Boolean values, integers, floating point numbers, complex numbers, text strings and the null object. Boolean values represent truth or falsehood, as used in logic operations. Not surpris- ingly, there are only two values, and in Python they are called True and False. 3 Example usage: a = True b = False Integers represent whole numbers, as you would use when counting items, and can be positive or negative. In Python 2 there are two types of integers, plain integers and long integers. 4 Plain integers have a maximum size dependent on the specific Python implementa- tion you are using.

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  eBook - PDF

  Readings from Python Fundamentals

  • Cengage, Cengage Cengage(Authors)
  • 2020(Publication Date)
  • Cengage Learning EMEA

    (Publisher)

  INTRODUCTION This module introduces the data types available to us. We look at integers, strings, lists, and Booleans. In Module 1, we learned about variables and looked at a few of the values/types of data that can be assigned to them. Specifically, we dealt with data of the string and integer types. In this module, we will look at the other data types that Python supports. Data types classify data, to tell the interpreter how the program intends to utilize that data. Data types define the different operations that can be performed on the data, how the data is stored, and the meaning of the data. LESSON 2.1 NUMERICAL DATA Let’s begin with numerical data types. MODULE OBJECTIVES BY THE END OF THIS MODULE, YOU WILL BE ABLE TO: 1. Explain the different numerical data types 2. Use operators on numerical data types 3. Explain strings and implement string operations, such as indexing, slicing, and string formatting 4. Describe escape sequences 5. Explain lists and perform simple operations on them 6. Use Boolean expressions and Boolean operators DATA TYPES MODULE 2 Copyright 2020 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s). Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it. PYTHON FUNDAMENTALS 20 Additionally, Python integers have unlimited precision. This means that there are no limits to how large they can be (save for the amount of available memory), as shown in Snippet 2.2. Lesson 2.1.1 Types of Numbers INTEGERS Integers, as we saw in Module 1 - Introducing Python, are numerical data types that are comprised of whole numbers.

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