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Introduction

• Python versatility: from data analysis to web crawling

Python Data Structures and Operations

• Integers and floats
• Strings and bytes
• Tuples and lists
• Dictionaries and ordered dictionaries
• Sets and frozen sets
• Data frame (pandas)
• Conversions

Object-Oriented Programming with Python

• Inheritance
• Polymorphism
• Static classes
• Static functions
• Decorators
• Other

Data Analysis with Pandas

• Data cleaning
• Using vectorized data in pandas
• Data wrangling
• Sorting and filtering data
• Aggregate operations
• Analyzing time series

Data Visualization

• Plotting diagrams with matplotlib
• Using matplotlib from within pandas
• Creating quality diagrams
• Visualizing data in Jupyter notebooks
• Other visualization libraries in Python

Vectorizing Data in Numpy

• Creating Numpy arrays
• Common operations on matrices
• Using ufuncs
• Views and broadcasting on Numpy arrays
• Optimizing performance by avoiding loops
• Optimizing performance with cProfile

Processing Big Data with Python

• Building and supporting distributed applications with Python
• Data storage: Working with SQL and NoSQL databases
• Distributed processing with Hadoop and Spark
• Scaling your applications

Extending Python (and vice versa) with Other Languages

• C#
• Java
• C++
• Perl
• Others

Python Multi-Threaded Programming

• Modules
• Synchronizing
• Prioritizing

Data Serialization

• Python object serialization with Pickle

UI Programming with Python

• Framework options for building GUIs in Python
  • Tkinter
  • Pyqt

Python for Maintenance Scripting

• Raising and catching exceptions correctly
• Organizing code into modules and packages
• Understanding symbol tables and accessing them in code
• Picking a testing framework and applying TDD in Python

Python for the Web

• Packages for web processing
• Web crawling
• Parsing HTML and XML
• Filling web forms automatically

Summary and Conclusion