Master Data Analysis with Python – Intro to Pandas


Begin your data analysis journey with Python by mastering the fundamentals of the pandas library

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

Description

Master Data Analysis with Python – Intro to Pandas 2022 targets 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 Cookbook and 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.


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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.

English
language

Content

Introduction
Course Overview
Python and Pandas Installation with the Miniconda Distribution
Course Contents
Downloading the Course Material
Exploring the Course Contents
Opening the Material with Jupyter Notebooks
Introduction to Jupyter Notebooks
Working through a Course Material
Differences with Video Notebooks
When to Open a New Notebook
What is pandas?
What is pandas?
Which version of pandas to use?
Pandas examples
The DataFrame and Series
Intro to the DataFrame and Series
DataFrame Components
Selecting a Series
Components of a Series
Getting Help in a Jupyter Notebook
Exercises
Data Types and Missing Values
Intro to Data Types and Missing Values
Finding the Data Type of Each Column
Getting More Metadata
Exercises
Setting a Meaningful Index
Setting an Index of a DataFrame
Accessing the Index, Columns, and Data
Accessing the Components of a Series
The Default Index
Setting an Index on Read
Choosing a Good Index
Exercises
Five-Step Process for Data Exploration
Five-Step Process for Data Exploration
Continue learning with Selecting Subsets of Data
Continue learning with Selecting Subsets of Data
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