Real-World Data Analysis | Exploring LEGO Dataset with Pandas | Data Analyst Projects скачать в хорошем качестве

Real-World Data Analysis | Exploring LEGO Dataset with Pandas | Data Analyst Projects

Real-World Data Analysis | Exploring Rebrickable LEGO Dataset with SQL | Data Analyst Projects In this video, we go through real scenarios of answering questions with data with Pandas. We go from basics to exploring complex problems with the use of MERGE, GROUPBY, etc. Solving real-world data analysis problems with Pandas in Python! (Rebrickable LEGO Dataset Analysis) We work on the following Skills in this video Using Merge to join DataFrames Creating Derived columns based on existing columns Understanding different ways of exploring data with Pandas -LINK TO DATA SOURCE- Rebrickable LEGO Data Source: https://rebrickable.com/downloads/ -LINK TO Demo Files- https://github.com/AllThingsDataWithA... https://github.com/AllThingsDataWithA... -LINK TO OTHER RELEVANT CONTENT- Data Analyst Portfolio Series:    • Data Analyst Portfolio   Learn SQL with Microsoft SQL Server:    • SQL   HAPPY WITH THE CONTENT? SUBSCRIBE NOW! CLICK HERE -    / angelinafrimpong   OR HERE - https://bit.ly/angelinafrimpong Timestamps: 00:00 Intro 00:52 Getting Data from Rebrickable.com 01:59 Installing Jupyter Notebook with Anaconda 03:03 Going over Demo Template 03:44 Importing Libraries 04:45 Importing Data for Demo 06:34 Basics of Data Exploration 11:02 Merge Imported Dataset 14:58 Question 1 - What is the total number of parts per theme? 18:27 Question 2 - What is the total number of parts per year? 19:36 Question 3 - How many sets were created in each Century in the dataset? 26:54 Question 4 - What percentage of sets ever released in the 21st Century were Trains Themed? 31:35 Question 5 - What percentage of sets ever released in the 21st Century were Disney Themed? 33:41 Question 6 - What is the popular theme by year in terms of sets released in the 21st Century? 39:47 Question 7 - What is the most produced color of lego ever in terms of quantity of parts? 46:41 Outro #Python #Pandas #DataAnalytics