Using Python for Big Data & Analytics

Introduction Download
Course Outline Download
NumPy
Matplotlib
Pandas
Reading Material Notes.docx
DayModulesSharing
1
  • Development Environment
  • Data types
  • Conditionals
  • Loops
  • Sequences
  • Mapping types
  • Useful types from collections
  • Program structure
  • Functions, Modules, and packages
  • Lambda functions
  • Variable scope
  • List comprehensions
  • Generator expressions
  • Creating modules
  • Using the import statement
  • Date Time module
  • A Minimal Class in Python
  • Attributes
  • Methods
  • The init method
  • Static Methods
  • Class Methods
  • Properties - Getters and Setters
  • Open file for writing
  • Reading Text Files
  • Reading/Writing CSV files
  • Working with XML
  • Reading/Writing JSON
  • Fetching data from Restful API
  • Reading data from Web Pages
2
  • Connecting to Server
  • Connecting to a server
  • Creating and executing a cursor
  • Fetching data from Tables
  • Parameterized statements
  • Ndarray: The Heart of the Library
  • Basic Operations
  • Indexing, Slicing, and Iterating
  • Conditions and Boolean Arrays
  • Shape Manipulation
  • Array Manipulation
  • General Concepts
  • Structured Arrays
  • Reading and Writing Array Data on Files
  • The Python Data Analysis Library
  • Testing Your pandas Installation
  • Getting Started with pandas
  • Introduction to pandas Data Structures
  • Other Functionalities on Indexes
  • Operations Between Data Structures
  • Function Application and Mapping
  • Sorting and Ranking
  • “Not a Number” Data
  • Hierarchical Indexing and Leveling
  • I/O API Tools
  • CSV and Textual Files
  • Reading Data in CSV or Text Files
  • Reading and Writing HTML Files
  • Reading Data from XML
  • Reading and Writing Data on Microsoft Excel Files
  • JSON Data
  • Data Preparation
  • Concatenating
  • Data Transformation
  • Discretization and Binning
  • Permutation
  • String Manipulation
  • Data Aggregation
  • Group Iteration
  • Advanced Data Aggregation
  • The matplotlib Library
  • pyplot
  • The Plotting Window
  • Using the kwargs
  • Adding Elements to the Chart
  • Saving Your Charts
  • Handling Date Values
  • Chart Typology
  • Line Charts
  • Histograms
  • Bar Charts
  • Pie Charts
  • Advanced Charts
  • The mplot3d Toolkit
  • Multi-Panel Plots

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