Python Pandas For Your Grandpa

Name: Python Pandas For Your Grandpa
Rating: 4.7 (257 reviews)

So easy, your grandpa could learn it!

Created byBen Gorman

Last updated 3/2022

English

What you'll learn

Python Pandas for data cleaning and wrangling
Creating and manipulating Series
Creating and manipulating DataFrames
Advanced techniques like merging, reshaping, MultiIndexes, Categoricals, and Dates & Times

Course content

4 sections • 28 lectures • 1h 58m total length

1.1 Introduction0:49
Introduction to the course!
Song: Good Enough Pizza by Sam Barsh
PLEASE READ!0:06

2.1 Series - Creation6:32
In this video we'll discuss the Series data structure and look at different ways to create a Series from scratch.
Song: Five Leaves by Federico Ferrandina
2.2 Series - Basic Indexing10:50
In this video we'll see how to use the index of a Series to access and modify its elements in meaningful ways.
Song: The Pretender by Isaac Joel
2.3 Series - Basic Operations3:13
In this video we'll see how to use the index of a Series to access and modify its elements in meaningful ways.
Song: The Pretender by Isaac Joel
2.4 Series - Boolean Indexing3:28
In this video we'll see how to perform basic math between Series like addition, subtraction, multiplication, and division.
Song: Powdery Piggyback by Isaac Joel
2.5 Series - Missing Values5:22
In this video we'll see how to use boolean indexing to select values from a Series based on logical conditions.
Song: Lucky Number 7 by Dresden, The Flamingo
2.6 Series - Vectorization2:03
In this video we'll see how to use NaN to represent missing or invalid values in a Series.
Song: Overtime by Simple Thieves
2.7 Series - apply()2:15
In this video we'll learn about vectorization and why using natively built Series methods is usually better than rolling your own custom methods.
Song: Bus Won't Stop by Famous Cats
2.8 Series - View vs Copy4:24
In this video we'll see how you can use the apply() method of a Series to apply a function to each element in the Series, and then we'll see why apply() is usually inferior to a vectorized solution.
Song: Looking Wes by Federico Ferrandina
2.9 Challenge - Baby Names1:48
Song: Dead Moll’s Fingers by Isaac Joel
2.10 Challenge - Bees Knees1:27
Song: Havana Banana by Mikey Geiger
2.12 Challenge - Price Gouging2:06
Song: All The Time by Ghost Beatz
2.13 Challenge - Fair Teams2:19
Song: Only The Brave Run Wild by Sounds Like Sander

3.1 DataFrame - Creation2:17
In this video we'll look at different ways to create a DataFrame from scratch.
Song: Story by Half Measure
3.2 DataFrame - To And From CSV3:08
In this video we'll see how you can read from and write to CSV with Pandas.
Song: Flashing Cone by Mikey Geiger
3.3 DataFrame - Basic Indexing6:13
In this video we'll look at some basic indexing operations for subsetting and modifying DataFrames.
Song: Swamp Bacon by Isaac Joel
3.4 DataFrame - Basic Operations1:45
In this video we'll go over some basic DataFrame operations like how to insert or delete columns and how to modify existing data.
Song: Violet Collybia by Isaac Joel
3.5 DataFrame - apply()3:54
In this video we'll see how you can use the apply() method of a DataFrame to apply a function to each row or column in a DataFrame.
Song: Swinging Paris by Federico Ferrandina
3.6 DataFrame - View vs Copy2:29
In this video we'll see examples of when a DataFrame gets copied and when it gets referenced as a view.
Song: Havana Connection by Federico Ferrandina
3.7 DataFrame - merge()7:53
In this video we'll look at one of the most common and important operations involving DataFrames - merging them together.
Song: Family Discount by Fantoms
3.8 DataFrame - Aggregation3:45
In this video we'll see how you can aggregate the rows of a DataFrame to calculate summary statistics.
Song: Yellow Plates by Isaac Joel
3.9 DataFrame - groupby()10:55
In this video we'll see how you can use groupby() to partition a DataFrame into groups and subsequently aggregate or transform the groups.
Song: Winter Sky by Bobo Renthlei
3.10 Challenge - Hobbies2:43
Song: The Lighthouse by Sounds Like Sander
3.11 Challenge - Party Time2:48
Song: Takes Me Under by Neon Beach
3.13 Challenge - Cradle Robbers2:02
Song: Morning Thoughts by Soulplusmind

Requirements

Basic knowledge of Python
Some knowledge of NumPy preferred (not necessary)

Description

Wanna learn Pandas?

Then boy do I have good news for you! For three months I hid from my wife and responsibilities, slaving away making this course so that you could learn Python Pandas. In this course, I cover topics like

Importing and installing pandas
Series
DataFrames
Indexes (including MultiIndexes)
Reading and writing to CSV
Merge, Reshape, Aggregation operations
Dates & times
Missing values
Strings
Categoricals

including tons of examples, animations, and practice problems with detailed solutions. But rather than me drone on about the course, check out some of my free lectures in the course curriculum to see it for yourself!

Need help?

If you buy this course, you'll have a commitment from me to help you understand any Pandas topics you might struggle with. I'm usually pretty quick to reply to questions.

Notes

This course was developed using Python 3.9.1 and Pandas version 1.2.0. If you're on a later version, don't worry - most of what I teach is unlikely to break.

Throughout this course, I use Google Colab as my IDE. You don't need to use Google Colab, but if you want to, it's a fantastic way to execute Python directly from your browser.

Also, you could take this course without knowing NumPy, but pre-existing knowledge of NumPy is preferred. After all, Pandas is built on top of it. And if you don't know NumPy, check out my course Python NumPy For Your Grandma.

Who this course is for:

Anyone with basic Python knowledge interested in learning Pandas for data wrangling
People interested in data science and machine learning

Python Pandas For Your Grandpa

What you'll learn

Explore related topics

Course content

1. Introduction2 lectures • 1min

Series12 lectures • 46min

3. DataFrame12 lectures • 50min

4. Advanced2 lectures • 22min

Requirements

Description

Who this course is for: