Python for Data Science : Data Types

Data Types

Data types are the classification or categorization of data items. It represents the kind of value that tells what operations can be performed on a particular data. Since everything is an object in Python programming, data types are actually classes and variables are instance (object) of these classes.

• A data type is a classification that allows specifying which type of value a variable contains.
• It also allows us to determine what type of mathematical operations can be applied to any given data.
• There are different types of python data types some of which are integer, float, string, lists, dictionaries, etc.
• The integer value is a positive or negative whole number.
• The float value is a real number with floating-point representation.
• The string value is a sequence of characters.
• A list can contain data of different data types.
• A dictionary is an ordered set of a key-value pair of items.
• Other data types include tuples and sets. 
  
  

  Example 1:

   

  # Dynamically-inferred types

  x = 20

  print(type(x))

  x = '20'

  print(type(x))

  x = 20.0

  print(type(x))

Output:

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

Example 2: 

# Manual type-conversion (string to int)

x = 20

y = '5'

print(x + int(y))

# output

# 25

Example 3:

# Automatic type-conversion (int to float)

x = 10

print(type(x))

x += 5.0

print(x), 

print(type(x))

Output:

<class 'int'>
15.0
<class 'float'>

Example 4:

# Dividing Integers

a = 20

b = 5

print(a/b)

print(b/a)

Output:

4.0
0.25

Example 5:

# String "arithmetic" (actually concatenation)

a = 'Sani '

b = 'Kamal'

print(a + b)

Output:

Sani Kamal