Python Data Visualization

Python Data Visualization

Duration: 3 Days

Description

This three-day course introduces participants to the powerful world of data visualization using Python. Starting with essential Python programming concepts, the course quickly transitions into key data science libraries such as NumPy, Pandas, and Matplotlib. Through hands-on examples, learners will gain the skills needed to process, analyze, and visualize data effectively. By the end of the course, participants will be able to create compelling, customized visualizations to derive insights and support data-driven decision-making.

Audience

This course is ideal for professionals who want to visualize and interpret data using Python, students and recent graduates exploring careers in data science, developers with basic coding knowledge aiming to enhance their data analysis and visualization skills, and anyone looking to understand and communicate data visually in Python.

Objectives

  • Understand core Python programming concepts relevant to data processing
  • Explain the importance and principles of effective data visualization
  • Use NumPy for efficient array-based computation and statistical analysis
  • Work with Pandas for data manipulation, cleaning, and exploration
  • Create, customize, and present various types of visualizations using Matplotlib
  • Integrate visualization techniques with real-world datasets to draw insights
  • Develop interactive and quality visual representations of data

Prerequisites

Participants should have a basic familiarity with programming concepts (e.g. variables, loops, functions) and a general understanding of data concepts such as rows, columns, and tabular data.

Course Outline

Module 1: Python Basics

  • Strings and Data Types
  • Conditional Statements
  • Collections
  • Functions and Classes
  • Lambdas

Module 2: Data Visualization Overview

  • Importance of Data Visualization
  • Visualization Using Python
  • Statistics
  • Probability

Module 3: NumPy

  • Basic Array Operations
  • Handling Multidimensional Data
  • Array Indexing and Slicing
  • Broadcasting and Vectorization
  • Data Aggregation

Module 4: Pandas

  • Introduction to Pandas
  • Data Structures
  • Data Importing and Exporting
  • Data Cleaning
  • Data Analysis

Module 5: Matplotlib

  • Creating Basic Plots
  • Customizing Plots
  • Adding Labels and Titles
  • Multiple Figures and Axes
  • Interactive Plots
  • Integrating with Pandas