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Practical Data Analysis with Python

Master data analysis and visualization with Python, using powerful libraries like NumPy, Pandas, and Matplotlib, to tackle real-world datasets.

30 lessons0 free lessons9 hr 07 min video
Practical Data Analysis with Python
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Course Overview

Dive into the world of data analysis with the comprehensive "Practical Data Analysis with Python" course. Designed for beginners who are familiar with basic Python, this course will guide you through the essential tools and techniques needed to analyze and visualize data effectively.

Key Concepts and Tools

You will start with an overview of data analysis in the realm of data science, understanding its importance and various applications. Then, you will delve into NumPy, learning how to manipulate arrays and perform fast vectorized calculations essential for large-scale data processing. Next, you'll explore Pandas, focusing on cleaning and organizing data — from handling missing values to filtering with loc and iloc. With practical projects, such as cleaning workout data and choosing a Netflix movie, you'll apply these techniques to real-world scenarios.

Data Visualization

The course emphasizes creating clear and informative visualizations. You will work with Matplotlib and Seaborn to create line plots, scatter plots, bar plots, histograms, and heat maps. You'll also gain exposure to Plotly for interactive visualizations.

Advanced Data Manipulation

Through in-depth lessons, you'll understand grouped summary statistics, merging and joining dataframes, and creating pivot tables. Finally, the course covers executing SQL queries directly on Pandas DataFrames with the Pandasql package, allowing for powerful data extraction and manipulation.

What You’ll Learn

  • Analyze and visualize data using Python libraries like NumPy, Pandas, and Matplotlib.
  • Clean, filter, and summarize data effectively using Pandas.
  • Create strong visual narratives with Seaborn and Plotly.
  • Execute SQL queries directly on DataFrames using Pandasql.

Skills Covered

  • Data Analysis
  • Data Cleaning
  • Data Visualization
  • Python Programming
  • SQL Query Execution

How This Course Helps You on the Job

  • Enhance decision-making with data-driven insights.
  • Communicate findings effectively with clear visualizations.
  • Increase efficiency in data handling and manipulation.
  • Contribute to data science projects with practical skills.
Course Curriculum

Start with any free lesson

0 of 30 lessons free
What is data analysis in data science? Overview, importance, and applications.1 lessons · 0 free
  1. What is data analysis in data science? Overview, importance, and applications.Premium lesson — member login required
NumPy and its applications3 lessons · 0 free
  1. NumPy and its applications part 1Premium lesson — member login required
  2. NumPy and its applications part 2Premium lesson — member login required
  3. NumPy and its applications part 3Premium lesson — member login required
Pandas and its applications1 lessons · 0 free
  1. Pandas Part 1:Pandas and its applicationsPremium lesson — member login required
Cleaning data with pandas4 lessons · 0 free
  1. Pandas Part 2: Cleaning data with pandas: Missing ValuesPremium lesson — member login required
  2. Pandas Part 3:Cleaning data with pandas: Wrong Data Types & FormatsPremium lesson — member login required
  3. Pandas Part 4:Cleaning data with pandas: Wrong Data & DuplicatesPremium lesson — member login required
  4. Project: cleaning workout dataPremium lesson — member login required
Accessing rows and columns using loc and iloc3 lessons · 0 free
  1. Accessing rows and columns using loc and iloc part 1Premium lesson — member login required
  2. Accessing rows and columns using loc and iloc part 2Premium lesson — member login required
  3. Project: Choosing a Netflix movie for the weekendPremium lesson — member login required
Grouped summary statistics1 lessons · 0 free
  1. Grouped summary statisticsPremium lesson — member login required
Merging & joining dataframes1 lessons · 0 free
  1. Merging & joining dataframesPremium lesson — member login required
Joining data frames1 lessons · 0 free
  1. Joining data framesPremium lesson — member login required
Pivot tables1 lessons · 0 free
  1. Pivot tablesPremium lesson — member login required
Working with matplotlib5 lessons · 0 free
  1. Working with matplotlib part 1 line plotPremium lesson — member login required
  2. Working with matplotlib part 2 scatter plotPremium lesson — member login required
  3. Working with matplotlib part 3 bar plotPremium lesson — member login required
  4. Titanic survivors projectPremium lesson — member login required
  5. Working with matplotlib part 4 histogramsPremium lesson — member login required
Making better visuals with seaborn2 lessons · 0 free
  1. Making better visuals with seaborn part 1Premium lesson — member login required
  2. Making better visuals with seaborn part 2Premium lesson — member login required
Exploring plotly1 lessons · 0 free
  1. Exploring plotlyPremium lesson — member login required
heat map1 lessons · 0 free
  1. heat mapPremium lesson — member login required
pandasql5 lessons · 0 free
  1. pandasql lesson 1: the select queryPremium lesson — member login required
  2. pandasql lesson 2: the where clausePremium lesson — member login required
  3. pandasql lesson 3: and, or, notPremium lesson — member login required
  4. pandasql lesson 4: aggregate functionsPremium lesson — member login required
  5. pandasql lesson 5: joinsPremium lesson — member login required

Frequently Asked Questions

What is the prerequisite knowledge for this course?

Basic Python knowledge is required, including an understanding of variables, loops, and functions.

Who is this course designed for?

It is designed for beginners with basic Python skills and those needing to conduct data analysis.

What tools will I learn in this course?

You'll learn to use NumPy, Pandas, Matplotlib, Seaborn, and Pandasql for data analysis and visualization.