Applied Python Pandas
Published 12/2024
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
Language: English | Size: 506.37 MB | Duration: 1h 12m
Published 12/2024
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
Language: English | Size: 506.37 MB | Duration: 1h 12m
Data Analysis and Data Cleaning with Pandas Library in Python Programming Language.
What you'll learn
Data Analysis and Data Cleaning with Pandas Library in Python Programming Language.
Data Structured Provided by Pandas.
Data Selection and Filtering.
Groupby, Aggregation and Visualisation.
Requirements
No Programming Experience Required.
Description
Applied Python Pandas is a course on pandas library, which is used for data analysis and data cleaning using python programming language.The intent of this course in to learn data analysis with pandas by solving problems that can be encountered in real world.This course has following lectures.Overview of PandasData StructuresData Selection & Data FilteringGroupby, Aggregation & Visualisation.Time SeriesEach section is presented with a scenario and set of tasks to solve. As we solve each task we shall learn new concepts in pandas library. All the code/data presented in the course is available in GitHub. When you clone the git repository we would get both exercise and solution notebooks. Exercise notebooks can be used to coding along as you watch exercises being solved in the course videos.The focus of this course is to apply our learnings to solve real world issues, whether you are a Student, Professional or Business person this course shall give you enough knowledge in short time to work with data you encounter in your field to derive insights and solve real problems with a data driven approach.If you are new to Data Analysis and Python Pandas you will find this course useful and can provide you a jump start.The course is easy to follow even if you are new to python.Disclaimer: The insights we draw as we solve different tasks in the course are to demonstrate data analysis with pandas, it is not a business or financial advise.
Overview
Section 1: Applied Python Pandas
Lecture 1 Overview of Pandas
Lecture 2 Data Structures
Lecture 3 Data Selection & Data Filtering
Lecture 4 Groupby, Aggregation & Visualization
Lecture 5 Time Series
Beginners and Intermediate