Python workshop
- 1. Python ProgrammingPython Programming Crash Course WorkshopCrash Course Workshop behzadimbehzadim mariebehzadimariebehzadi mariebehzadimariebehzadi 26-Nov-2018
- 2. Scripting Language ● What is Scripting Language? ● Interpreted Programs vs Compiled Programs ● #!
- 3. What is Python? ● Created in 1990 by Guido van Rossum ● Rossum was BDFL until 2018 ● Origin name from British comedy group Monty Python ● An important goal of Python's developers is keeping it fun to use ● Interpreted high-level programming language ● General-purpose language ● Paradigm – Object-oriented – Imperative – Functional – Procedural – Reflective
- 6. Python 2.7 2016 → 71.9% 2017 → 63.7%
- 7. Why Python? ● Designed to be easy to learn and master ● Readable and Maintainable Code ● Multiple Programming Paradigms ● Robust Standard Library ● Extensive Support Libraries ● Compatible with Major Platforms and Systems ● Many Open Source Frameworks and Tools ● General Purpose Programming Language ● Adopt Test Driven Development ● Lots of 3rd Party Tools ● Active Open-Source Community
- 8. Popularity
- 9. Popularity
- 10. Productivity ● Reduced Development Time – Code is 2-10x shorter than C, C++, Java ● Improved Program Maintenance – High Readability ● Less Training – Easy to Learn
- 13. Python Basics (Math Operations)
- 14. Python Basics (Variable and Types)
- 18. Python Basics (Data Structures)
- 19. Python Basics (Data Structures)
- 20. Python Basics (Data Structures)
- 23. More Details (Exception Handling)
- 24. More Details (Module) ● logically organize your Python code ● Grouping related code → easy, high readability ● Simply, a module is a file consisting of Python code ● A module can define functions, classes and variables. ● A module can also include runnable code.
- 25. The Python Standard Library ● Python comes standard with a set of modules, known as the “standard library” ● Incredibly rich and diverse functionality available from the standard library ● All common internet protocols, sockets, CGI, OS services, GUI services (via Tcl/Tk), database, Berkeley style databases, calendar, Python parser, file globbing/searching, debugger, profiler, threading and synchronisation, persistency, etc https://docs.python.org/3/library/
- 27. Numpy ● Numerical Python ● Why NumPy? ● Designed for scientific computing ● Open-Source ● ndarray is the core object ● Advanced functions to work with arrays ● Universal Functions (ufunc) ● Basic Linear Algebra ● Basic Statistical Operations ● Random Simulation ● discrete Fourier transforms ● mathematical, logical, shape manipulation ● Numeric + Numarray ~ NumPy
- 28. Numpy / Linear Algebra
- 29. Pandas ● data manipulation and analysis ● data structures and operations for manipulating numerical tables and time series ● The name is derived from the term "panel data" ● DataFrame is the Core Object ● Suitable for Data Wrangling ● Open-Source
- 31. scikit-learn ● free software machine learning library for the Python ● Used in data mining and data analysis ● Built on NumPy, SciPy, and matplotlib ● Open-Source ● classification, regression and clustering algorithms – support vector machines – random forests – gradient boosting – k-means – DBSCAN
- 32. scikit-learn (Data Modeling & Prediction)