Python Data Science with Pandas: Master 12 Advanced Projects

Course Curriculum

Chapter 1: Getting Started

Lecture 1: Course Overview (don´t skip!)

Lecture 2: Tips: How to get the most out of this Course (don´t skip!)

Lecture 3: FAQ / Your Questions answered

Lecture 4: How to download and install Anaconda for Python coding

Lecture 5: Jupyter Notebooks – let´s get started

Lecture 6: How to work with Jupyter Notebooks

Chapter 2: Project 1: Explanatory Data Analysis & Data Presentation (Movies Dataset)

Lecture 1: Project Overview

Lecture 2: Downloads (Project 1)

Lecture 3: Project Brief for Self-Coders

Lecture 4: Data Import from csv file and first Inspection

Lecture 5: The best and the worst movies… (Part 1)

Lecture 6: The best and the worst movies… (Part 2)

Lecture 7: Which Movie would you like to see next?

Lecture 8: What are the most common Words in Movie Titles, Taglines and Overviews?

Lecture 9: Are Franchises more successful?

Lecture 10: What are the most successful Franchises?

Lecture 11: The most successful Directors

Lecture 12: The most successful Actors (Part 1)

Lecture 13: The most successful Actors (Part 2)

Lecture 14: Now it´s your turn (Homework)

Chapter 3: Excursus: How to avoid and debug Coding Errors (incl. ChatGPT)

Lecture 1: Introduction

Lecture 2: Test your debugging skills!

Lecture 3: Major reasons for Coding Errors

Lecture 4: The most commonly made Errors at a glance

Lecture 5: Omitting cells, changing the sequence and more

Lecture 6: IndexErrors

Lecture 7: Indentation Errors

Lecture 8: Misuse of function names and keywords

Lecture 9: TypeErrors and ValueErrors

Lecture 10: **NEW** Debugging Pandas Errors with ChatGPT

Lecture 11: Getting help on StackOverflow.com

Lecture 12: How to traceback more complex Errors

Lecture 13: Problems with the Python Installation

Lecture 14: External Factors and Issues

Lecture 15: Errors related to the course content (Transcription Errors)

Lecture 16: Summary and Debugging Flow-Chart

Lecture 17: **NEW** The Debugging Flow-Chart with ChatGPT

Chapter 4: Project 2: Data Import – Working with APIs and JSON (Movies Dataset)

Lecture 1: Project Overview

Lecture 2: What is JSON?

Lecture 3: Downloads (Project 2)

Lecture 4: Project Brief for Self-Coders

Lecture 5: Importing Data from JSON files

Lecture 6: JSON and Orientation/Formats

Lecture 7: What is an API? – The Movie Database API

Lecture 8: Working with APIs and JSON (Part 1)

Lecture 9: How to work with your own API-KEY

Lecture 10: Working with APIs and JSON (Part 2)

Lecture 11: Importing and Storing the Movies Dataset (Best Practice)

Lecture 12: Importing and Storing the Movies Dataset (Real World Scenario)

Chapter 5: Project 3: Data Cleaning – Tidy up messy Datasets (Movies Dataset)

Lecture 1: Project Overview

Lecture 2: Downloads (Project 3)

Lecture 3: Project Brief for Self-Coders

Lecture 4: First Steps

Lecture 5: Dropping irrelevant Columns

Lecture 6: How to handle stringified JSON columns (Part 1)

Lecture 7: How to handle stringified JSON columns (Part 2)

Lecture 8: How to flatten nested Columns

Lecture 9: How to clean Numerical Columns (Part 1)

Lecture 10: How to clean Numerical Columns (Part 2)

Lecture 11: How to clean Columns with DateTime Information

Lecture 12: How to clean String / Text Columns

Lecture 13: How to remove Duplicates

Lecture 14: Handling Missing Values & Removing Obervations/Rows

Lecture 15: Final Steps

Chapter 6: Project 4: Merging, Cleaning & Transforming Data (Movies Dataset)

Lecture 1: Project Overview

Lecture 2: Downloads (Project 4)

Lecture 3: Project Brief for Self-Coders

Lecture 4: Getting the Datasets

Lecture 5: Preparing the Data for Merge

Lecture 6: Merging the Data (Left Join)

Lecture 7: Cleaning and Transforming the new "Cast" Column

Lecture 8: Cleaning and Transforming the new "Crew" Column

Lecture 9: Final Steps

Chapter 7: Project 5: Working with Pandas and SQL Databases (Movies Dataset)

Lecture 1: Project Overview

Lecture 2: What is a Database / SQL?

Lecture 3: Downloads (Project 5)

Lecture 4: Project Brief for Self-Coders

Lecture 5: How to create an SQLite Database

Lecture 6: How to load Data from DataFrames into an SQLite Database

Lecture 7: How to load Data from SQLite Databases into DataFrames

Lecture 8: Some simple SQL Queries

Lecture 9: Some more SQL Queries

Lecture 10: Join Queries

Lecture 11: Final Case Study

Chapter 8: Project 6: Importing & Concatenating many files (Baby Names Dataset)

Lecture 1: Project Overview

Lecture 2: Downloads (Project 6)

Lecture 3: Project Brief for Self-Coders (Part 1)

Lecture 4: Getting the Data from the Web

Lecture 5: Importing one File & Understanding the Data Structure (easy case)

Lecture 6: Importing & merging many Files (easy case)

Lecture 7: Final Steps

Lecture 8: Project Brief for Self-Coders (Part 2)