Python Programming

History of Python, thrust areas, installing Anaconda distribution, Jupyter Notebook; Identifiers, keywords, statements and expressions, variables, operators, precedence and associativity, data types; Indentation, comments, reading input, print output, type conversions, type() and is operator, dynamic and strongly typed language; Control flow: if, if-else, if-elif-else, nested if, while and for loops, continue and break, catching exceptions with try/except

Functions: built-in functions, modules, definition and calling, return and void functions, scope and lifetime; Default parameters, keyword arguments, *args and **kwargs, command line arguments; Strings: creating and storing, basic operations, indexing, slicing and joining, string methods, formatting; Lists: creating, basic operations, indexing and slicing, built-in functions, list methods, del statement

Dictionaries: creating, accessing and modifying key:value pairs, built-in functions, methods, del statement; Tuples: creating, basic operations, tuple() function, indexing and slicing, built-in functions; Relation between tuples and lists, tuples and dictionaries, using zip(); Sets, set methods, frozenset

Files: types of files, creating and reading text data, file methods to read and write; Reading and writing binary files, pickle module, reading and writing CSV files, os and os.path modules; Classes and objects, creating classes and objects, constructor method, classes with multiple objects; Class attributes vs data attributes, encapsulation, inheritance, polymorphism

Functional programming; JSON and XML in Python; NumPy with Python; Pandas