Easy Python Data science session 485

Description of Python beginning course tutorial:

This video is part 485 of Python full beginning course tutorials. And focus of this video is on Merging Datasets with Pandas 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