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Python Live Stream 10 hours part 202
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Description of Python beginning course tutorial: • This video is part 202 of Python full beginning course tutorials. And focus of this video is on Reading and Writing NumPy Array Data on Files in Python programming. • • Section 1 Installation of Anaconda and set up Python environment • • Section 2 Variables and simple data types • String variables • Numbers • • Section 3 Working with lists • Introducing lists • Changing, Appending,Removing items of Lists • Organizing lists • Looping through an entire list • Making Numerical Lists • List comprehension and Working with Part of a List • Tuples • • Section 4 Conditional test and If statements • Conditional Tests • if Statements • Using if Statements with Lists • • • Section 5 Dictionaries • Working with Dictionaries • Looping Through a Dictionary • Nesting dictionaries • Python Dictionary get() Method • Removing from dictionaries – the pop() method and the del statement • • Section 6 User input and while loop • User input - A • User input - B • Introducing while loops • Using break and continue in while loops • Using a while Loop with Lists • Using a while Loop with Dictionaries • User input • • Section 7 Functions • Defining a function • Passing arguments to function • Functions: Return a simple value • Functions: Return a dictionary • Using a Function with a while Loop • Passing a List to function • Passing an Arbitrary Number of Arguments to function • Storing Your Functions in Modules • Map function and Lambda expression in Python to replace characters • pass multiple arguments to map function • Partial functions • • • Section 8 Classes • Creating and Using a Class • Working with Classes and Instances • Inheritance of Classes • Working with Attributes and Methods for the Child Class • Importing Classes • • • Section 9 Files and Exceptions • Reading from a File • Writing to a File • Introducing try-except Blocks Exception • Handling the FileNotFoundError Exception • Using Try, Except, else,pass and Finally in Python • Storing Data using json() module • Refactoring • • • Section 10 The NumPy library • Introducing NumPy library • Creation of Array in NumPy • Basic operations of Numpy ndarray • Indexing, Slicing, and Iterating, (Conditions and Boolean) of NumPy arrays • Joining, Splitting and Shape Manipulation of NumPy arrays • Copies and Views, difference between NumPy arrays and Python lists • Broadcasting of NumPy arrays • Random Number Generation with Python and NumPy • Reading and Writing NumPy Array Data on Files • • • • Section 11 Introducing The pandas library • Getting Started with Pandas in Python • Introduction of Pandas Data Structures: The Series • Pandas Series Operations • Introduction of Pandas Data Structures: The DataFrame • Basic manipulation of Pandas DataFrame • Working with Index of Pandas Data Structures • Operations and Functions of Pandas Data Structures • Statistics Functions of Pandas Data Structures • Sorting and Ranking of Pandas Data Structures • Handling Not a Number Data with Pandas Data Structures • Hierarchical Indexing and Leveling of Pandas Data Structures • Accessing Rows and Columns of DataFrame • Ways to filter Pandas DataFrame by column values • • • Section 12 Reading and Writing Data with Pandas library() • Reading Data in CSV or Text Files with Pandas • Using Regular Expressions to Parse TXT Files with Pandas • Writing Data to CSV Files with Pandas • Reading and Writing Data on Microsoft Excel Files with Pandas • Reading and Writing HTML Files with Pandas • Reading Data from XML with Pandas • Reading and Writing JSON Data with Pandas • Section 13 Pandas in Depth: Data Manipulation() • Merging Datasets with Pandas • Concatenating and Combining Datasets with Numpy and Pandas • Pivoting,Stacking,Unstacking,Long and Wide forms of Datasets with Pandas • Removing, Mapping Operations with Pandas • Rename Indexes of Axes with Pandas • Detecting and Filtering Outliers with Pandas • Discretization and Binning of Datasets with Pandas • Permutation,Random Sampling with Pandas • Data Aggregation,Grouping with Pandas • Reshape Wide long form pandas • • • #python • #numpy • #pandas
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