lab1 file for py

1. Business
Analytics
Eng. Tasneem Mohammed Helil

2. Installation
• Jupyter is a web server
• Anaconda  Jupyter
• Cmd  pip install notebook
• To open jupyter run “jupyter notebook”
• Python

3. What is python?
• Python is a popular high-level programming language used
in various applications.
• Python is an easy language to learn because of its simple
syntax.
• Python works on different platforms (Windows, Mac, Linux).
• Python relies on indentation, using whitespace, to define
scope; such as the scope of loops, functions and classes.

4. Data types
• Integer: Integers are whole numbers, positive or negative,
without any decimal point.
• Float: are numbers with a decimal point.
• String: Strings are sequences of characters, enclosed within
single quotes, double quotes.
• boolean: represents truth values, True or False.

5. Data types cont.
• List is a collection which is changeable. Allows duplicate
members.
• Tuple is a collection which is ordered and unchangeable.
Allows duplicate members.
• Set is a collection which is unordered, unchangeable. No
duplicate members.
• Dictionary is a collection which is changeable. No duplicate
members.

6. Variables

7. Variables cont.

8. • The input() function always returns a string, even if the user
enters a number or another type of value.
• For output we use print() function. This function is used to
display output to the console.
Input and output

9. • example of accessing individual characters of a string using
indexing:

10. • It can have any number of items and they may be of
different types (integer, float, string etc.)
List

11. Dictionary

12. Dictionary cont.

13. if condition

14. while loop

15. for loop

16. NumPy
• Pip install numpy
• The NumPy library offers a collection of high-level
mathematical functions including support for
multi-dimensional arrays.

17. NumPy arrays
• NumPy arrays are much faster than
Python lists for numerical operations.
• NumPy arrays use less memory and
are more compact.
• NumPy provides a broad range of
mathematical tools for arrays.

18. NumPy arrays cont.
Built-in methods to generate Arrays:
1. Array and shape
2. zeros and ones
3. Eye
4. Linspace
5. random number arrays
6. arange
7. max, min, argmax, argmin
8. reshape

19. NumPy indexing
Indexing1Dand 2Darrays
1. Get a value at an index
2. Get values in a range
3. Setting a value with index range
4. Difference between copy and view in arrays

20. NumPy selection
Indexing1Dand 2Darrays
1. Get a value at an index
2. Get values in a range
3. Setting a value with index range
4. Difference between copy and view in arrays

21. NumPy operations
Arithmetic
1. Addition – subtraction – division – multiplication –
exponentiation
Universal Array Functions
1. Square roots
2. Exponential
3. Log
4. Sin and cos

22. Thank You