In this project, we will analyze life expectancy data by performing data wrangling & exploratory data analysis (EDA). Pandas is a powerful open source data analysis tools in python. Exploratory Data Analysis (EDA) is a process of analyzing data to gain valuable insights such as statistical summary & visualizations.
Practical Data Wrangling with Pandas
Practical Data Wrangling with Pandas
Instructor: Ryan Ahmed
Access provided by Coursera Learning Team
Learn, practice, and apply job-ready skills with expert guidance
Beginner level
No prior experience required
2 hours
Learn at your own pace
Hands-on learning
What you'll learn
Perform Exploratory Data Analysis (EDA) and Data Wrangling in Pandas
Perform Feature Engineering, one-hot encoding and deal with missing data
Understand the difference between normalization and standardization
Skills you'll practice
Details to know
Shareable certificate
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Taught in English
No downloads or installation required
Only available on desktop
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About this Guided Project
Learn step-by-step
In a video that plays in a split-screen with your work area, your instructor will walk you through these steps:
Introduction and Project Overview
Import Datasets and Perform Basic Statistical Data Analysis
Practice Opportunity #1 [Optional]:
Dealing with Missing Datasets
Practice Opportunity #2 [Optional]:
Perform One Hot Encoding
Perform Data Normalization
Perform Data Standardization
Pandas with Functions
Final Capstone Project
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Instructor
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How you'll learn
Skill-based, hands-on learning
Practice new skills by completing job-related tasks.
Expert guidance
Follow along with pre-recorded videos from experts using a unique side-by-side interface.
No downloads or installation required
Access the tools and resources you need in a pre-configured cloud workspace.
Available only on desktop
This Guided Project is designed for laptops or desktop computers with a reliable Internet connection, not mobile devices.
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