- Python Basics
- Python - Home
- Python - Overview
- Python - History
- Python - Features
- Python vs C++
- Python - Hello World Program
- Python - Application Areas
- Python - Interpreter
- Python - Environment Setup
- Python - Virtual Environment
- Python - Basic Syntax
- Python - Variables
- Python - Data Types
- Python - Type Casting
- Python - Unicode System
- Python - Literals
- Python - Operators
- Python - Arithmetic Operators
- Python - Comparison Operators
- Python - Assignment Operators
- Python - Logical Operators
- Python - Bitwise Operators
- Python - Membership Operators
- Python - Identity Operators
- Python - Operator Precedence
- Python - Comments
- Python - User Input
- Python - Numbers
- Python - Booleans
- Python Control Statements
- Python - Control Flow
- Python - Decision Making
- Python - If Statement
- Python - If else
- Python - Nested If
- Python - Match-Case Statement
- Python - Loops
- Python - for Loops
- Python - for-else Loops
- Python - While Loops
- Python - break Statement
- Python - continue Statement
- Python - pass Statement
- Python - Nested Loops
- Python Functions & Modules
- Python - Functions
- Python - Default Arguments
- Python - Keyword Arguments
- Python - Keyword-Only Arguments
- Python - Positional Arguments
- Python - Positional-Only Arguments
- Python - Arbitrary Arguments
- Python - Variables Scope
- Python - Function Annotations
- Python - Modules
- Python - Built in Functions
- Python Strings
- Python - Strings
- Python - Slicing Strings
- Python - Modify Strings
- Python - String Concatenation
- Python - String Formatting
- Python - Escape Characters
- Python - String Methods
- Python - String Exercises
- Python Lists
- Python - Lists
- Python - Access List Items
- Python - Change List Items
- Python - Add List Items
- Python - Remove List Items
- Python - Loop Lists
- Python - List Comprehension
- Python - Sort Lists
- Python - Copy Lists
- Python - Join Lists
- Python - List Methods
- Python - List Exercises
- Python Tuples
- Python - Tuples
- Python - Access Tuple Items
- Python - Update Tuples
- Python - Unpack Tuples
- Python - Loop Tuples
- Python - Join Tuples
- Python - Tuple Methods
- Python - Tuple Exercises
- Python Sets
- Python - Sets
- Python - Access Set Items
- Python - Add Set Items
- Python - Remove Set Items
- Python - Loop Sets
- Python - Join Sets
- Python - Copy Sets
- Python - Set Operators
- Python - Set Methods
- Python - Set Exercises
- Python Dictionaries
- Python - Dictionaries
- Python - Access Dictionary Items
- Python - Change Dictionary Items
- Python - Add Dictionary Items
- Python - Remove Dictionary Items
- Python - Dictionary View Objects
- Python - Loop Dictionaries
- Python - Copy Dictionaries
- Python - Nested Dictionaries
- Python - Dictionary Methods
- Python - Dictionary Exercises
- Python Arrays
- Python - Arrays
- Python - Access Array Items
- Python - Add Array Items
- Python - Remove Array Items
- Python - Loop Arrays
- Python - Copy Arrays
- Python - Reverse Arrays
- Python - Sort Arrays
- Python - Join Arrays
- Python - Array Methods
- Python - Array Exercises
- Python File Handling
- Python - File Handling
- Python - Write to File
- Python - Read Files
- Python - Renaming and Deleting Files
- Python - Directories
- Python - File Methods
- Python - OS File/Directory Methods
- Object Oriented Programming
- Python - OOPs Concepts
- Python - Object & Classes
- Python - Class Attributes
- Python - Class Methods
- Python - Static Methods
- Python - Constructors
- Python - Access Modifiers
- Python - Inheritance
- Python - Polymorphism
- Python - Method Overriding
- Python - Method Overloading
- Python - Dynamic Binding
- Python - Dynamic Typing
- Python - Abstraction
- Python - Encapsulation
- Python - Interfaces
- Python - Packages
- Python - Inner Classes
- Python - Anonymous Class and Objects
- Python - Singleton Class
- Python - Wrapper Classes
- Python - Enums
- Python - Reflection
- Python Errors & Exceptions
- Python - Syntax Errors
- Python - Exceptions
- Python - try-except Block
- Python - try-finally Block
- Python - Raising Exceptions
- Python - Exception Chaining
- Python - Nested try Block
- Python - User-defined Exception
- Python - Logging
- Python - Assertions
- Python - Built-in Exceptions
- Python Multithreading
- Python - Multithreading
- Python - Thread Life Cycle
- Python - Creating a Thread
- Python - Starting a Thread
- Python - Joining Threads
- Python - Naming Thread
- Python - Thread Scheduling
- Python - Thread Pools
- Python - Main Thread
- Python - Thread Priority
- Python - Daemon Threads
- Python - Synchronizing Threads
- Python Synchronization
- Python - Inter-thread Communication
- Python - Thread Deadlock
- Python - Interrupting a Thread
- Python Networking
- Python - Networking
- Python - Socket Programming
- Python - URL Processing
- Python - Generics
- Python Libraries
- NumPy Tutorial
- Pandas Tutorial
- SciPy Tutorial
- Matplotlib Tutorial
- Django Tutorial
- OpenCV Tutorial
- Python Miscellenous
- Python - Date & Time
- Python - Maths
- Python - Iterators
- Python - Generators
- Python - Closures
- Python - Decorators
- Python - Recursion
- Python - Reg Expressions
- Python - PIP
- Python - Database Access
- Python - Weak References
- Python - Serialization
- Python - Templating
- Python - Output Formatting
- Python - Performance Measurement
- Python - Data Compression
- Python - CGI Programming
- Python - XML Processing
- Python - GUI Programming
- Python - Command-Line Arguments
- Python - Docstrings
- Python - JSON
- Python - Sending Email
- Python - Further Extensions
- Python - Tools/Utilities
- Python - GUIs
- Python Useful Resources
- Python Compiler
- NumPy Compiler
- Matplotlib Compiler
- SciPy Compiler
- Python - Programming Examples
- Python - Quick Guide
- Python - Useful Resources
- Python - Discussion
Python math.ceil() Method
The Python math.ceil() method is used to find the nearest greater integer of a numeric value. For example, the ceil value of the floating-point number 3.6 is 4.
The process involved is almost similar to the estimation or rounding off technique. The difference occurs when the ceil value of 3.6 is 4, but the ceil value of 3.2 will also be 4; unlike the estimation technique which rounds off 3.2 to 3 instead of 4.
Note − This function is not accessible directly, so we need to import math module and then we need to call this function using math static object.
Syntax
Following is the syntax for the Python math.ceil() method −
math.ceil(x)
Parameters
x − This is a numeric object.
Return Value
This method returns the smallest integer greater than argument x.
Example
The following example shows the usage of the Python math.ceil() method. In here, we are creating two numeric objects with positive and negative values, and ceil values for both these objects are calculated using this method.
import math # This will import math module # Create two numeric objects x and y x = 45.17 y = -36.89 # Calculate and display the ceil value of x res = math.ceil(x) print("The ceil value of x:", res) # Calculate and display the ceil value of y res = math.ceil(y) print("The ceil value of y:", res)
When we run above program, it produces following result −
The ceil value of x: 46 The ceil value of y: -36
Example
However, this method will not accept any value as its argument other than numeric objects.
In this example, let us try to pass a list containing numeric objects as an argument to this method and check whether it calculates the ceil values for all of them or not.
import math # This will import math module # Create a list containing numeric objects x = [12.36, 87.45, 66.33, 12.04] # Calculate the ceil value for the list res = math.ceil(x) print("The ceil value of x:", res)
On executing the program above, a TypeError is raised as follows −
Traceback (most recent call last): File "main.py", line 5, inres = math.ceil(x) TypeError: must be real number, not list
Example
To return the ceil values of the numeric objects in a list using this method, loop statements can be used.
We are creating a list that contains number objects, whose ceil values are to be calculated using the ceil() method. Then, we will iterate this list using a for loop; and for every iteration, a number object in the list is passed as an argument to this method. Since the objects in the list are all numbers, the method will not raise an error.
import math # This will import math module # Create a list containing numeric objects x = [12.36, 87.45, 66.33, 12.04] ln = len(x) # Calculate the ceil value for the list for n in range (0, ln): res = math.ceil(x[n]) print("The ceil value of x[",n,"]:", res)
Now, if we execute the program above, the result is produced as follows −
The ceil value of x[ 0 ]: 13 The ceil value of x[ 1 ]: 88 The ceil value of x[ 2 ]: 67 The ceil value of x[ 3 ]: 13
Example
We can implement this function in a lot of real-world applications of Python. For example, let us try to find the ceil value of a quotient of two numbers. Let us first create two number objects, divide them using the "/" operator and find the ceil value of their quotient using the ceil() method.
import math # This will import math module # Create a list containing numeric objects x = 54.13 y = 14.78 #Find the quotient of x and y qt = x/y print("The quotient of these values is:", qt) # Calculate the ceil value for the quotient res = math.ceil(qt) print("The ceil value of x/y is:", res)
Let us compile and run the program above, the output is displayed as follows −
The quotient of these values is: 3.6623815967523683 The ceil value of x/y is: 4