Numeric functions are discussed in set 1 below
Logarithmic and power functions are discussed in this set.
1. exp(a) :- This function returns the value of e raised to the power a (e**a) .
2. log(a, b) :- This function returns the logarithmic value of a with base b. If base is not mentioned, the computed value is of natural log.
The e**4 value is : 54.598150033144236 The value of log 2 with base 3 is : 0.6309297535714574
3. log2(a) :- This function computes value of log a with base 2. This value is more accurate than the value of the function discussed above.
4. log10(a) :- This function computes value of log a with base 10. This value is more accurate than the value of the function discussed above.
The value of log2 of 16 is : 4.0 The value of log10 of 10000 is : 4.0
5. pow(a, b) :- This function is used to compute value of a raised to the power b (a**b).
6. sqrt() :- This function returns the square root of the number.
The value of 3 to the power 2 is : 9.0 The value of square root of 25 : 5.0
This article is contributed by Manjeet Singh .If you like GeeksforGeeks and would like to contribute, you can also write an article using contribute.geeksforgeeks.org or mail your article to firstname.lastname@example.org. See your article appearing on the GeeksforGeeks main page and help other Geeks.
Please write comments if you find anything incorrect, or you want to share more information about the topic discussed above.
Attention geek! Strengthen your foundations with the Python Programming Foundation Course and learn the basics.
To begin with, your interview preparations Enhance your Data Structures concepts with the Python DS Course.
- Mathematical Functions in Python | Set 3 (Trigonometric and Angular Functions)
- Mathematical Functions in Python | Set 4 (Special Functions and Constants)
- Mathematical Functions in Python | Set 1 (Numeric Functions)
- Log and natural Logarithmic value of a column in Pandas - Python
- Python - Logarithmic Discrete Distribution in Statistics
- sympy.stats.Logarithmic() in Python
- Python | Mathematical Median of Cumulative Records
- Plot Mathematical Expressions in Python using Matplotlib
- Evaluate the Mathematical Expressions using Tkinter in Python
- ML | Mathematical explanation of RMSE and R-squared error
- Mathematical explanation for Linear Regression working
- Q-learning Mathematical Background
- Chi-Square Test for Feature Selection - Mathematical Explanation
- Highest and Smallest power of K less than and greater than equal to N respectively
- Complex Numbers in Python | Set 2 (Important Functions and Constants)
- Complex Numbers in Python | Set 3 (Trigonometric and Hyperbolic Functions)
- Statistical Functions in Python | Set 1 (Averages and Measure of Central Location)
- Python | Set 2 (Variables, Expressions, Conditions and Functions)
- Array in Python | Set 1 (Introduction and Functions)
- numpy.power() in Python