A Python Pandas crash course to teach you all the essentials to get started with data analytics
This course includes:
- 1.5 hours of on-demand video
- 1 article
- 1 downloadable resource
- Full lifetime access
- Access on mobile and TV
- Certificate of completion
4.9
(67 ratings)
4,344 students
Created by Dr. Ali Gazala, Aimei Zhu
What you’ll learn
- Describe the Anatomy and main components of Pandas Data Structures. Understand Pandas Data Types and the correct use case for each type.
- Implement several methods to get data into and from Pandas DataFrames. These methods include Python Native Data Structures, Tabular data files, API queries, etc
- Describe any information within a Pandas data frame. This will help you to identify data problems such as having missing values or using incorrect data types
- Perform Data manipulation and cleaning. This part includes fixing data types, handling missing values, removing duplicate records, and many more
- Merge & Join multiple datasets into Pandas DataFrames
- Perform Data Summarization & Aggregation within any DataFrame
- Create different types of Data Visualization
- Apply all the Pandas knowledge you have learned in this course to a real-world Data Analysis Project to investigate COVID-19 infection and the consequent lo
Course content
9 sections • 17 lectures • 1h 32m total lengthCollapse all sections
Before We Start1 lecture • 1min
- Course Resources – Read Me01:07
Lesson 1 – Getting Started1 lecture • 7min
- Getting Started with PandasPreview06:30
- Lesson 1 – Quiz4 questions
Lesson 2 – Getting Data into and from Pandas5 lectures • 24min
- What is Pandas IO02:22
- Working with Python Native Data Structures03:40
- Working with Tabular Data Format07:05
- Working with API Data07:35
- Working with Web Data03:26
- Lesson 2 – Quiz2 questions
Lesson 3 – Exploring Data Objects2 lectures • 9min
- How to Examine my Data00:46
- Exploring Data Objects07:47
- Lesson 3 – Quiz3 questions
Lesson 4 – Data Cleaning with Pandas1 lecture • 11min
- Data Cleaning with Pandas11:16
- Lesson 4 – Quiz1 question
Lesson 5 – Merging & Joining Data3 lectures • 11min
- Intro to Merging and Joining01:35
- Concat FunctionPreview05:20
- Merge Function04:30
- Lesson 5 – Quiz3 questions
Lesson 6 – Data Accessing & Aggregation1 lecture • 11min
- Data Accessing & Aggregation11:18
- Lesson 8 – Quiz2 questions
Lesson 7 – Pandas Data Visualization2 lectures • 9min
- Intro to Data Visualization01:13
- Pandas Data Visualization07:22
- Lesson 7 – Quiz1 question
Lesson 8 – Pandas Analysis Project1 lecture • 10min
- Pandas Analysis Project09:47
Requirements
- To take the best out of this course, you will need a minimum working knowledge of Python programming language and be comfortable running data science documents using Jupyter notebook
Description
Welcome to our Pandas crash course! This course is designed to provide you with a practical guide to using Pandas, the popular data manipulation library in Python. We’ve included real-life examples and reusable code snippets to help you quickly apply what you learn to your own data analysis projects.
Throughout this course, you will learn how to:
- Describe the Anatomy of Pandas Data Structures. This includes Pandas DataFrames, Series, and Indices.
- Implement several methods to get data into and from Pandas DataFrames. These methods include Python Native Data Structures, Tabular data files, API queries, JSON format, web scraping, and more.
- Describe any information within a Pandas data frame. This will help you to identify data problems such as missing values or using incorrect data types.
- Understand Pandas Data Types and the correct use case for each type.
- Perform Data manipulation and cleaning. This part includes fixing data types, handling missing values, removing duplicate records, and many more.
- Merge & Join multiple datasets into Pandas DataFrames
- Perform Data Summarization & Aggregation within any DataFrame
- Create different types of Data Visualization
- Update Pandas Styling Settings
- Conduct a Data Analysis Project using Pandas library to collect and investigate COVID-19 infection, and the consequent lockdown in different countries.
In addition to the course materials, you’ll also have free access to a Jupyter Notebook with all of the code examples covered in this course, as well as a free e-book in PDF format. By the end of this course, you’ll have a solid understanding of how to use Pandas to perform data manipulation tasks and analyze data.
Who this course is for:
- This course is for aspiring data professionals and Python developers who want to learn how to process data in Pandas.
