Exploratory Data Analysis for the Public Sector with ggplot from Coursera

Learn about the core pillars of the public sector and the core functions of public administration through statistical Exploratory Data Analysis (EDA). Learn analytical and technical skills using the R programming language to explore, visualize, and present data, with a focus on equity and the administrative functions of planning and reporting. Technical skills in this course will focus on the ggplot2 library of the tidyverse, and include developing bar, line, and scatter charts, generating trend lines, and understanding histograms, kernel density estimations, violin plots, and ridgeplots. These skills are enhanced with lessons on best practices for good information visualization design. Upon completing this course, you will understand the layered grammar of graphics and its implementation in ggplot2, all while exploring a diverse set of authentic public datasets.

All coursework is completed in RStudio in Coursera without the need to install additional software.

This is the second of four courses within the Data Analytics in the Public Sector with R Specialization. The series is ideal for current or early-career professionals working in the public sector looking to gain skills in analyzing public data effectively. It is also ideal for current data analytics professionals or students looking to enter the public sector.

What's inside

Syllabus

Week 1 | Introduction to Visualization with ggplot2

Welcome to the second course in the Data Analytics in the Public Sector with R—Exploratory Data Analysis for Public Administration with ggplot. This week, you will begin to develop the skills of exploratory data analysis through constructing ggplot plots and line plots in RStudio. You will also get to recognize the importance of data visualization for public administration and how powerful data visualization skills are in the profession of a data analyst.

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Read about what's good

what should give you pause

and possible dealbreakers

Develops core administering skills in the public arena, such as planning and reporting

Taught by recognized instructors Christopher Brooks and Paula Lantz

Emphasizes the core principle of equity

Covers diverse set of public sector datasets

Builds on previous skills with ggplot2 and R statistical software

Introduces students to ggplot2 library of tidyverse for statistical data visualization

Reviews summary

Practical ggplot for public sector data analysis

According to learners, this course offers a fantastic deep dive into ggplot2 with a unique focus on the public sector, particularly emphasizing equity and data visualization ethics. Students praise the clear instruction and the highly practical, hands-on labs in RStudio, which make applying concepts straightforward. While widely lauded for its relevance to public administration and teaching effective data communication, some learners with prior R experience found the pace a bit slow, noting it's best for those new to ggplot. A key consideration is the implied prerequisite for foundational R knowledge, as absolute beginners in R might struggle. Overall, it's a highly recommended course for developing impactful visualizations for public data.

Concepts are explained clearly, making complex topics manageable.

"The instructor was clear..."

"The instructor explains concepts clearly, and the assignments reinforced the learning."

"The instructor broke down complex concepts into manageable chunks."

"The ggplot2 grammar of graphics section was particularly well-explained."

Provides valuable hands-on practice with real-world applications in RStudio.

"The instructor was clear, and the hands-on labs in RStudio were excellent."

"The practical exercises using RStudio were invaluable."

"The hands-on labs were extremely helpful for practicing R and ggplot skills."

"I found the course really practical and focused on applying data visualization to real-world public sector challenges."

Emphasizes data visualization for public administration and equity.

"This course was a fantastic deep dive into ggplot2 specifically tailored for public sector data. I appreciated the real-world examples and the focus on equity..."

"The material on data visualization ethics and equity was insightful and often overlooked in other courses."

"The focus on public administration and data equity truly sets it apart."

"I learned so much about communicating data effectively for policy decisions. It's a must-take for anyone working in or aspiring to work in the public sector data field."

Some learners wished for more complex examples or deeper statistical dives.

"Sometimes the examples felt a bit too simplified for complex real-world problems."

"I was hoping for more advanced statistical techniques applied to public data."

"The course could benefit from a bit more challenge in the later weeks, perhaps more complex datasets or case studies."

"My only minor critique is that some explanations could have used more detailed code examples."

Ideal for those with some R foundation, may be slow for advanced users or hard for beginners.

"I struggled with this course. While the ggplot concepts are fine, the prerequisite knowledge of R was higher than expected. I felt a bit lost sometimes without a stronger R foundation."

"It's good for beginners [in ggplot], but if you have prior EDA experience, it might feel a bit slow."

"Decent course, but a bit slow for me. I already knew some R and ggplot, so much of it felt like a review. It's probably best for those entirely new to ggplot."

"Maybe this course is not for absolute beginners in R, even if it's second in a specialization."

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Exploratory Data Analysis for the Public Sector with ggplot with these activities:

Practice R programming basics

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Ensure your proficiency in R programming, a crucial skill for data analysis in this course.

Browse courses on R

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Install R and RStudio.
Review basic R syntax.
Complete beginner-level R tutorials.

Review 'Data Analysis for the Social Sciences with R'

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Gain a better understanding of data analysis techniques commonly used in social science research, specifically with the R programming language.

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Read Chapters 1-3.
Complete the exercises at the end of each chapter.

Solve EDA practice problems on DataCamp

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Gain practical experience in applying EDA techniques through interactive practice problems.

Browse courses on EDA

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Create a DataCamp account.
Complete the 'Exploratory Data Analysis in R' course.

Four other activities

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Follow tutorials on ggplot2 library

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Enhance your understanding of the ggplot2 library for data visualization, which is a core component of this course.

Browse courses on Ggplot2

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Visit the ggplot2 website.
Follow the 'Getting Started' tutorial.
Complete the 'Tutorials' section.

Join a study group

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Collaborate with peers, exchange ideas, and reinforce learning through discussions and problem-solving.

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Find a study group or create your own.
Meet regularly to discuss course materials.
Work together on assignments and projects.

Create a data visualization dashboard

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Develop a practical understanding of data visualization principles and techniques by creating a dashboard using ggplot2.

Browse courses on Data Visualization

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Identify a dataset to use.
Clean and prepare the data.
Create visualizations using ggplot2.
Design the dashboard layout.
Deploy the dashboard.

Develop a data analysis plan

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Translate your understanding of data analysis principles into a practical plan for a specific public administration project.

Browse courses on Data Analysis

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Identify a specific public administration issue.
Determine the research questions.
Develop a data collection strategy.
Outline the methods for data analysis.
Create a timeline for project completion.

Career center

Learners who complete Exploratory Data Analysis for the Public Sector with ggplot will develop knowledge and skills that may be useful to these careers:

Public Policy Analyst

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Statistician

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Program Manager

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Data Analyst

Data analysts use data to solve problems and make decisions. They work in a variety of industries, including healthcare, finance, government, and retail. This course can help you develop the skills you need to be a successful data analyst, including data visualization, data analysis, and communication. It can also help you build a strong foundation in the principles of public administration.

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Project Manager

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Market Researcher

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Financial Analyst

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Business Analyst

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Operations Research Analyst

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Consultant

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Data Scientist

Data scientists use data to develop new products and services. They work in a variety of industries, including healthcare, finance, and retail. This course can help you develop the skills you need to be a successful data scientist, including data visualization, data analysis, and communication. It can also help you build a strong foundation in the principles of public administration.

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Software Engineer

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Computer Scientist

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Information Technology Manager

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Database Administrator

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