Master Data Analysis with Python – Intro to Pandas

Master Data Analysis with Python – Intro to Pandas, available at Free, has an average rating of 4.42, with 31 lectures, based on 354 reviews, and has 10796 subscribers.

You will learn about Best practices from pandas expert Ted Petrou author of Master Data Analysis with Python Introduction to the pandas DataFrame and Series Understanding the different data types available within a DataFrame Accessing the DataFrame components – the index, columns, and values Setting a meaningful index in a DataFrame Completing a five-step process for data exploration This course is ideal for individuals who are Those who want to begin a comprehensive path for mastering the pandas library with best practices to analyze data It is particularly useful for Those who want to begin a comprehensive path for mastering the pandas library with best practices to analyze data.

Enroll now: Master Data Analysis with Python – Intro to Pandas

Summary

Title: Master Data Analysis with Python – Intro to Pandas

Price: Free

Average Rating: 4.42

Number of Lectures: 31

Number of Published Lectures: 31

Number of Curriculum Items: 31

Number of Published Curriculum Objects: 31

Original Price: Free

Quality Status: approved

Status: Live

What You Will Learn

Best practices from pandas expert Ted Petrou author of Master Data Analysis with Python
Introduction to the pandas DataFrame and Series
Understanding the different data types available within a DataFrame
Accessing the DataFrame components – the index, columns, and values
Setting a meaningful index in a DataFrame
Completing a five-step process for data exploration

Who Should Attend

Those who want to begin a comprehensive path for mastering the pandas library with best practices to analyze data

Target Audiences

Those who want to begin a comprehensive path for mastering the pandas library with best practices to analyze data

Master Data Analysis with Python – Intro to Pandastargets those who want to completely master doing data analysis with pandas. This course provides an introduction to the two primary pandas objects, the DataFrame and Series. This is a brand new free course updated for the latest version of pandas.

This course is taught by expert instructor Ted Petrou, author of the highly-rated text books Pandas Cookbookand Master Data Analysis with Python. Ted has taught over 1,000 hours of live in-person data science courses that use the pandas library. Pandas is a difficult library to use effectively and is often taught incorrectly with poor practices. Ted is extremely adept at using pandas and is known for developing best practices on how to use the library.

All of the material and exercises are written in Jupyter Notebooks available for you to download. This allows you to read the notes, run the code, and write solutions to the exercises all in a single place.

This course targets those who have an interest in becoming experts and completely mastering the pandas library for data analysis in a professional environment. This course does not cover all of the pandas library, just a small and fundamental portion of it. If you are looking for a brief introduction of the entire pandas library, this course is not it. It takes many dozens of hours, lots of practice, and rigorous understanding to be successful using pandas for data analysis in a professional environment.

Intro to Pandas is first in the Master Data Analysis with Python series which includes the following sequence of courses:

Intro to Pandas
Selecting Subsets of Data with Pandas
Essential Pandas Commands
Grouping Data with Pandas
Time Series with Pandas
Cleaning Data with Pandas
Joining Data with Pandas
Data Visualization
Advanced Pandas
Exploratory Data Analysis

This course assumes no previous pandas experience. The only prerequisite knowledge is to understand the fundamentals of Python.

Course Curriculum

Chapter 1: Introduction

Lecture 1: Course Overview

Lecture 2: Python and Pandas Installation with the Miniconda Distribution

Chapter 2: Course Contents

Lecture 1: Downloading the Course Material

Lecture 2: Exploring the Course Contents

Lecture 3: Opening the Material with Jupyter Notebooks

Lecture 4: Introduction to Jupyter Notebooks

Lecture 5: Working through a Course Material

Lecture 6: Differences with Video Notebooks

Lecture 7: When to Open a New Notebook

Chapter 3: What is pandas?

Lecture 1: What is pandas?

Lecture 2: Which version of pandas to use?

Lecture 3: Pandas examples

Chapter 4: The DataFrame and Series

Lecture 1: Intro to the DataFrame and Series

Lecture 2: DataFrame Components

Lecture 3: Selecting a Series

Lecture 4: Components of a Series

Lecture 5: Getting Help in a Jupyter Notebook

Lecture 6: Exercises

Chapter 5: Data Types and Missing Values

Lecture 1: Intro to Data Types and Missing Values

Lecture 2: Finding the Data Type of Each Column

Lecture 3: Getting More Metadata

Lecture 4: Exercises

Chapter 6: Setting a Meaningful Index

Lecture 1: Setting an Index of a DataFrame

Lecture 2: Accessing the Index, Columns, and Data

Lecture 3: Accessing the Components of a Series

Lecture 4: The Default Index

Lecture 5: Setting an Index on Read

Lecture 6: Choosing a Good Index

Lecture 7: Exercises

Chapter 7: Five-Step Process for Data Exploration

Lecture 1: Five-Step Process for Data Exploration

Chapter 8: Continue learning with Selecting Subsets of Data

Lecture 1: Continue learning with Selecting Subsets of Data

Instructors

Ted Petrou
Author of Pandas Cookbook, Founder of Dunder Data

Rating Distribution

1 stars: 2 votes
2 stars: 6 votes
3 stars: 30 votes
4 stars: 122 votes
5 stars: 194 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!

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