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Data Analysis with Pandas and Python

  • Development
  • May 12, 2025
SynopsisData Analysis with Pandas and Python, available at $124.99, h...
Data Analysis with Pandas and Python  No.1

Data Analysis with Pandas and Python, available at $124.99, has an average rating of 4.66, with 141 lectures, 36 quizzes, based on 22753 reviews, and has 202084 subscribers.

You will learn about Perform a multitude of data operations in Pythons popular pandas library including grouping, pivoting, joining and more! Learn hundreds of methods and attributes across numerous pandas objects Possess a strong understanding of manipulating 1D, 2D, and 3D data sets Resolve common issues in broken or incomplete data sets This course is ideal for individuals who are Data analysts and business analysts or Excel users looking to learn a more powerful software for data analysis It is particularly useful for Data analysts and business analysts or Excel users looking to learn a more powerful software for data analysis.

Enroll now: Data Analysis with Pandas and Python

Summary

Title: Data Analysis with Pandas and Python

Price: $124.99

Average Rating: 4.66

Number of Lectures: 141

Number of Quizzes: 36

Number of Published Lectures: 141

Number of Published Quizzes: 36

Number of Curriculum Items: 177

Number of Published Curriculum Objects: 177

Original Price: $19.99

Quality Status: approved

Status: Live

What You Will Learn

  • Perform a multitude of data operations in Pythons popular pandas library including grouping, pivoting, joining and more!
  • Learn hundreds of methods and attributes across numerous pandas objects
  • Possess a strong understanding of manipulating 1D, 2D, and 3D data sets
  • Resolve common issues in broken or incomplete data sets
  • Who Should Attend

  • Data analysts and business analysts
  • Excel users looking to learn a more powerful software for data analysis
  • Target Audiences

  • Data analysts and business analysts
  • Excel users looking to learn a more powerful software for data analysis
  • Student Testimonials:

  • The instructor knows the material, and has detailed explanation on every topic he discusses. Has clarity too, and warns students of potential pitfalls. He has a very logical explanation, and it is easy to follow him. I highly recommend this class, and would look into taking a new class from him. – Diana

  • This is excellent, and I cannot complement the instructor enough. Extremely clear, relevant, and high quality – with helpful practical tips and advice. Would recommend this to anyone wanting to learn pandas. Lessons are well constructed. I’m actually surprised at how well done this is. I don’t give many 5 stars, but this has earned it so far. – Michael

  • This course is very thorough, clear, and well thought out. This is the best Udemy course I have taken thus far. (This is my third course.) The instruction is excellent! – James

  • Welcome to the most comprehensive Pandas course available on Udemy! An excellent choice for both beginners and experts looking to expand their knowledge on one of the most popular Python libraries in the world!

    Data Analysis with Pandas and Python offers 19+ hours of in-depth video tutorials on the most powerful data analysis toolkit available today. Lessons include:

  • installing

  • sorting

  • filtering

  • grouping

  • aggregating

  • de-duplicating

  • pivoting

  • munging

  • deleting

  • merging

  • visualizing

  • and more!

    Why learn pandas?

    If you’ve spent time in a spreadsheet software like Microsoft Excel, Apple Numbers, or Google Sheets and are eager to take your data analysis skills to the next level, this course is for you! 

    Data Analysis with Pandas and Python introduces you to the popular Pandas library built on top of the Python programming language. 

    Pandasis a powerhouse tool that allows you to do anything and everything with colossal data sets analyzing, organizing, sorting, filtering, pivoting, aggregating, munging, cleaning, calculating, and more! 

    I call it “Excel on steroids”!

    Over the course of more than 19 hours, I’ll take you step-by-step through Pandas, from installation to visualization! We’ll cover hundreds of different methods, attributes, features, and functionalities packed away inside this awesome library. We’ll dive into tons of different datasets, short and long, broken and pristine, to demonstrate the incredible versatility and efficiency of this package.

    Data Analysis with Pandas and Python is bundled with dozens of datasets for you to use. Dive right in and follow along with my lessons to see how easy it is to get started with pandas!

    Whether you’re a new data analyst or have spent years (*cough* too long *cough*) in Excel, Data Analysis with pandas and Python offers you an incredible introduction to one of the most powerful data toolkits available today!

    Course Curriculum

    Chapter 1: Installation and Setup

    Lecture 1: Introduction to the Course

    Lecture 2: macOS – Download and Install the Anaconda Distribution

    Lecture 3: Windows – Download and Install the Anaconda Distribution

    Lecture 4: How to Uninstall the Anaconda Distribution

    Lecture 5: Use Anaconda Navigator to Create a New Environment

    Lecture 6: Download Course Materials

    Lecture 7: Unpack Course Materials + The Startdown and Shutdown Process

    Lecture 8: Intro to the Jupyter Lab Interface

    Lecture 9: Code Cell Execution

    Lecture 10: Import Libraries into Jupyter Lab

    Chapter 2: Python Crash Course

    Lecture 1: Comments

    Lecture 2: Basic Data Types

    Lecture 3: Operators

    Lecture 4: Variables

    Lecture 5: Built-in Functions

    Lecture 6: Custom Functions

    Lecture 7: String Methods

    Lecture 8: Lists

    Lecture 9: Index Positions and Slicing

    Lecture 10: Dictionaries

    Lecture 11: Classes

    Lecture 12: Navigating Libraries using Jupyter Lab

    Chapter 3: Series

    Lecture 1: Create a Series Object from a List

    Lecture 2: Create a Series Object from a Dictionary

    Lecture 3: Intro to Series Methods

    Lecture 4: Intro to Attributes

    Lecture 5: Parameters and Arguments

    Lecture 6: Import Series with the pd.read_csv Function

    Lecture 7: The head and tail Methods

    Lecture 8: Passing Series to Python Built-In Functions

    Lecture 9: Check for Inclusion with Pythons in Keyword

    Lecture 10: The sort_values Method

    Lecture 11: The sort_index Method

    Lecture 12: Extract Series Values by Index Position

    Lecture 13: Extract Series Values by Index Label

    Lecture 14: The get Method

    Lecture 15: Overwrite a Series Value

    Lecture 16: The copy Method

    Lecture 17: Math Methods on Series Objects

    Lecture 18: Broadcasting

    Lecture 19: The value_counts Method

    Lecture 20: The apply Method

    Lecture 21: The map Method

    Chapter 4: DataFrames I: Introduction

    Lecture 1: Methods and Attributes between Series and DataFrames

    Lecture 2: Differences between Shared Methods

    Lecture 3: Select One Column from a DataFrame

    Lecture 4: Select Multiple Columns from a DataFrame

    Lecture 5: Add New Column to DataFrame

    Lecture 6: A Review of the value_counts Method

    Lecture 7: Drop DataFrame Rows with Missing Values

    Lecture 8: Fill in Missing Values with the fillna Method

    Lecture 9: The astype Method I

    Lecture 10: The astype Method II

    Lecture 11: Sort a DataFrame with the sort_values Method I

    Lecture 12: Sort a DataFrame with the sort_values Method II

    Lecture 13: Sort DataFrame with the sort_index Method

    Lecture 14: Rank Series Values with the rank Method

    Chapter 5: DataFrames II: Filtering Data

    Lecture 1: This Modules Dataset + Memory Optimization

    Lecture 2: Filter a DataFrame Based on a Condition

    Lecture 3: Filter with More than One Condition (AND – &)

    Lecture 4: Filter with More than One Condition (OR – |)

    Lecture 5: The isin Method

    Lecture 6: The isnull and notnull Methods

    Lecture 7: The between Method

    Instructors

  • Data Analysis with Pandas and Python  No.2
    Boris Paskhaver
    Software Engineer | Consultant | Author
  • Rating Distribution

  • 1 stars: 103 votes
  • 2 stars: 210 votes
  • 3 stars: 1458 votes
  • 4 stars: 7407 votes
  • 5 stars: 13575 votes
  • Frequently Asked Questions

    How long do I have access to the course materials?

    You can view and review the lecture materials indefinitely, like an on-demand channel.

    Can I take my courses with me wherever I go?

    Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!