Pandas with Python

Pandas with Python, available at Free, has an average rating of 3.75, with 27 lectures, based on 241 reviews, and has 19707 subscribers.

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

Enroll now: Pandas with Python

Summary

Title: Pandas with Python

Price: Free

Average Rating: 3.75

Number of Lectures: 27

Number of Published Lectures: 27

Number of Curriculum Items: 27

Number of Published Curriculum Objects: 27

Original Price: Free

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!

Possess a strong understanding of manipulating 1D, 2D, and 3D data sets

Learn hundreds of methods and attributes across numerous pandas objects

Resolve common issues in broken or incomplete data sets

Who Should Attend

Beginner Python developers curious about Data Science

Target Audiences

Beginner Python developers curious about Data Science

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 Pythonoffers you an incredible introduction to one of the most powerful data toolkits available today!

1. Introduction Series & DataFrame

2. Date Range & Inspecting Data

3. Indexing & Slicing on DataFrame – 1

4. loc & iloc

5. Indexing & Slicing on DataFrame – 2

6. Concatination & Descriptive Statistics

7. Merging DataFrames

8. Working with Text Data

9. Function Application & Loading data in Python

10. Loading Data from CSV, Excel & URL

11. Data Visualization using Pandas

12. What is Data Science

13. What is Machine Learning

Course Curriculum

Chapter 1: Pandas with Python

Lecture 1: Session 1. Introduction Series & DataFrame

Lecture 2: Introduction Series & DataFrame

Lecture 3: Session 2. Date Range & Inspecting Data

Lecture 4: Date Range & Inspecting Data

Lecture 5: Session 3. Indexing & Slicing on DataFrame – 1

Lecture 6: Indexing & Slicing on DataFrame – 1

Lecture 7: Session 4. loc & iloc

Lecture 8: loc & iloc

Lecture 9: Session 5. Indexing & Slicing on DataFrame – 2

Lecture 10: Indexing & Slicing on DataFrame – 2

Lecture 11: Session 6. Concatenation & Descriptive Statistics

Lecture 12: Concatenation & Descriptive Statistics

Lecture 13: Session 7. Merging DataFrames

Lecture 14: Merging DataFrames

Lecture 15: Session 8. Working with Text Data

Lecture 16: Working with Text Data

Lecture 17: Session 9. Function Application & Loading data in Python

Lecture 18: Function Application & Loading data in Python

Lecture 19: Session 10. Loading Data from CSV, Excel & URL

Lecture 20: Loading Data from CSV, Excel & URL

Lecture 21: Session 11. Data Visualization using Pandas

Lecture 22: Data Visualization using Pandas

Lecture 23: Data Science

Lecture 24: 12. What is Data Science

Lecture 25: Machine Learning

Lecture 26: 13. What is Machine Learning

Lecture 27: Summary

Instructors

DATAhill Solutions Srinivas Reddy
Data Scientist

Rating Distribution

1 stars: 25 votes

2 stars: 23 votes

3 stars: 54 votes

4 stars: 69 votes

5 stars: 70 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!