Python is a great language for doing data analysis, primarily because of the fantastic ecosystem of data-centric Python packages. Pandas is one of those packages and makes importing and analyzing data much easier.
There are some important math operations that can be performed on a pandas series to simplify data analysis using Python and save a lot of time.

Python is a powerful programming language that provides several built-in functions and libraries for mathematical operations used in data analysis. Some of the most commonly used math operations in data analysis include addition, subtraction, multiplication, division, and exponentiation.

Addition: The addition operator ‘+’ is used for adding two or more numbers in Python. For example, if you want to add two variables a and b, you can use the following code: 

a = 5
b = 3
c = a + b
print(c)

Subtraction: The subtraction operator ‘-’ is used for subtracting one number from another in Python. For example: 

a = 5
b = 3
c = a - b
print(c)

Multiplication: The multiplication operator ‘*’ is used for multiplying two or more numbers in Python. For example: 

a = 5
b = 3
c = a * b
print(c)

Division: The division operator ‘/’ is used for dividing one number by another in Python. For example: 

a = 5
b = 3
c = a / b
print(c)

Exponentiation: The exponentiation operator ‘**’ is used for raising one number to the power of another in Python. For example: 

a = 5
b = 3
c = a ** b
print(c)

In addition to these basic math operations, Python also provides several built-in math functions and libraries such as numpy and scipy that are widely used in data analysis. These libraries provide a wide range of functions such as trigonometric functions, logarithmic functions, statistical functions, and more.