A data type defines the kind of value that a variable can store and the operations that can be performed on that value.

Python provides several built-in data types. The most commonly used basic data types are:

• int (Integer)
• float (Floating-Point Number)
• complex (Complex Number)
• bool (Boolean)
• str (String)

Every value in Python belongs to one of these data types.

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Example 1: Integer (int) #

main.py

age = 25

print(age)
print(type(age))

Output #

25
<class 'int'>

Explanation #

• 25 is an integer value.
• Integers are whole numbers without a decimal point.
• The type() function confirms that the value belongs to the int data type.

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Example 2: Floating-Point Number (float) #

main.py

price = 99.95

print(price)
print(type(price))

Output #

99.95
<class 'float'>

Explanation #

• 99.95 contains a decimal point.
• Therefore, Python stores it as a floating-point number.
• Floating-point numbers are represented by the float data type.

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Example 3: Complex Number (complex) #

main.py

number = 3 + 4j

print(number)
print(type(number))

Output #

(3+4j)
<class 'complex'>

Explanation #

• A complex number contains a real part and an imaginary part.
• The imaginary part is represented using the letter j.
• Python provides built-in support for complex numbers through the complex data type.

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Example 4: Boolean (bool) #

main.py

result1 = True
result2 = False

print(result1)
print(result2)
print(type(result1))

Output #

True
False
<class 'bool'>

Explanation #

• Boolean values can only be True or False.
• They are commonly used in decision-making and comparisons.
• The data type of Boolean values is bool.

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Example 5: String (str) #

main.py

language = "Python"

print(language)
print(type(language))

Output #

Python
<class 'str'>

Explanation #

• A string is a sequence of characters enclosed in quotation marks.
• Strings are represented by the str data type.
• Strings can contain letters, numbers, symbols, and spaces.

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Example 6: Multiple Data Types #

main.py

age = 25
height = 5.9
name = "Alice"
is_student = True

print(type(age))
print(type(height))
print(type(name))
print(type(is_student))

Output #

<class 'int'>
<class 'float'>
<class 'str'>
<class 'bool'>

Explanation #

• Python variables can store different kinds of data.
• Each variable has its own data type.
• The type() function displays the type of every variable.

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Example 7: Scientific Notation #

main.py

distance = 3.5e6

print(distance)
print(type(distance))

Output #

3500000.0
<class 'float'>

Explanation #

• Scientific notation uses e or E.
• 3.5e6 means 3.5 × 10⁶.
• Scientific notation values are stored as floating-point numbers.

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Example 8: Type Conversion Between Data Types #

main.py

number = 25

decimal = float(number)

print(decimal)
print(type(decimal))

Output #

25.0
<class 'float'>

Explanation #

• number is an integer.
• float() converts it into a floating-point number.
• The converted value has the float data type.

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Example 9: Using Different Data Types Together #

main.py

name = "Alice"
age = 22
height = 5.4

print(name, age, height)

Output #

Alice 22 5.4

Explanation #

• Python allows different data types to be used together.
• The print() function can display values of different types in a single statement.
• By default, print() separates the values with spaces.

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Example 10: Checking the Data Type #

main.py

value = False

print(type(value))

Output #

<class 'bool'>

Explanation #

• The variable value stores the Boolean value False.
• The type() function identifies its data type.
• The returned type is bool.

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Common Mistakes #

1. Assuming Numbers with Decimal Points are Integers #

Incorrect Assumption

number = 10.0

Incorrect Expectation #

<class 'int'>

Actual Output #

<class 'float'>

Reason

Any numeric value containing a decimal point is a floating-point number.

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2. Forgetting Quotes Around Strings #

Incorrect

name = Python

Output #

NameError: name 'Python' is not defined

Reason

Text values must be enclosed in quotation marks.

Correct

name = "Python"

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3. Using true and false Instead of True and False #

Incorrect

status = true

Output #

NameError: name 'true' is not defined

Reason

Python Boolean values are written as True and False with uppercase first letters.

Correct

status = True

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4. Confusing Strings with Numbers #

Incorrect

age = "25"

print(age + 5)

Output #

TypeError: can only concatenate str (not "int") to str

Reason

"25" is a string, not an integer.

Correct

age = int("25")

print(age + 5)

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Best Practices #

• Choose the appropriate data type for the information being stored.
• Use type() while learning to verify data types.
• Keep numeric and string data separate unless conversion is required.
• Use meaningful variable names that indicate the type of data being stored.
• Convert values explicitly when needed using functions such as int(), float(), and str().

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Key Points to Remember #

• A data type specifies the kind of value stored by a variable.
• Python’s common basic data types include int, float, complex, bool, and str.
• Integers represent whole numbers.
• Floating-point numbers represent numbers with decimal points.
• Complex numbers use the j suffix for the imaginary part.
• Boolean values are True and False.
• Strings are sequences of characters enclosed in quotation marks.
• The type() function returns the data type of a value or variable.