Python Code Challenges for Data Analysis
34mAdvanced2025-02-25
Authors
Jonathan Fernandes
Consultant focusing on data science, AI, and big data
Course details
In this course, Jonathan Fernandes—an expert in Generative AI and Large Language Models—explores the essentials of data analysis using Python. Learn how to load data, filter it by specific criteria, and manipulate data structures to achieve the desired results. Discover the use of CoderPad to effectively compare and evaluate different Python data structures. Dive deep into hands-on challenges like sorting data by various metrics and finding elements with the most nominations. By the end of this course, you will be proficient in using Python for data analysis tasks and capable of tackling complex data problems. This course is ideal for aspiring data analysts, Python programmers, and anyone interested in data science.
Learning objectives
Analyze the data and select a specific format.
Choose the correct python container to capture the data.
Apply and work with correct Python data structures for a task.
Subdivide the problem into chunks where each performs a single function.
Learning objectives
Analyze the data and select a specific format.
Choose the correct python container to capture the data.
Apply and work with correct Python data structures for a task.
Subdivide the problem into chunks where each performs a single function.
Skills covered
PythonData AnalysisProgramming LanguagesData ScienceBusiness Analysis and StrategyBusiness Software and ToolsOpen SourceSoftware DevelopmentOne-Off
Concepts
0. Introduction
- 01 - Data analysis using Python
- 02 - How to use CoderPad
1. Python Code Challenges for Data Analysis
- 03 - Solution - Load JSONL data
- 04 - Solution - Filter by year
- 05 - Solution - Released by year
- 06 - Solution - Sort by runtime
- 07 - Solution - Find the most nominations