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Daniel Romaniuk
In this one hour long project-based course, you will tackle a real-world problem in data analysis and visualization. You will process a dataset of crime incidents in the city of Boston, and use this data to create an animated heatmap displaying crime hotspots.
Heatmaps use color to display a quantity that changes over two dimensions.
By the end of this project, you will have created heatmaps using code you will write in Python.
Register for this course and see more details by visiting:
OpenCourser.com/course/2q29tu/crime
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What's inside
Syllabus
Traffic lights
Traffic lights
Read about what's good
what should give you pause and
possible dealbreakers
Develops technical skills directly applicable in industry
Develops theoretical and applied skills around data analysis and visualization
Appropriate for learners with a working knowledge of Pyhthon
Possible prerequisite for related courses or positions
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Reviews summary
Python folium heatmap project
According to learners, this course is a highly effective project-based experience for creating animated heatmaps with Python and Folium. Students frequently praise its hands-on approach, which allows them to quickly apply new skills. The clear instructions and use of engaging real-world crime data are consistently highlighted as positive aspects. While many find it a perfect concise lesson for adding a specific skill, some learners note the fast pace and suggest it is best suited for those with some prior Python knowledge, as it doesn't delve into deep theoretical concepts.
The use of real-world crime data enhances engagement and relevance.
"The use of crime data made it engaging. I already knew Python and Pandas, so this was a perfect way to add Folium."
"The Boston crime data provided a good context. The instructor's guidance was clear."
"The crime data made it relevant and engaging. This is exactly what I needed to bridge my Python skills with geospatial visualization."
A brief, one-hour course delivering a specific, practical skill.
"While it's only an hour, it packs a lot in. Some parts felt a bit rushed, but it was generally easy to follow."
"A short and sweet project. The animation feature was particularly interesting. For an hour, it's quite effective."
"It's concise but covers enough to get you going. The code worked perfectly, and the result was impressive."
Effectively teaches the creation of animated heatmaps using Folium.
"A good short course to get introduced to Folium and animated visualizations."
"I was able to follow along easily and create my own heatmap... This is exactly what I needed to bridge my Python skills with geospatial visualization."
"It does what it says – creates a heatmap. For an hour, it's quite effective."
Offers a practical, project-based approach for immediate skill application.
"This project was a fantastic hands-on experience! I learned how to use Folium to create an interactive animated heatmap..."
"Excellent quick project! ...a perfect way to add Folium to my visualization toolkit. I loved the practical application of mapping and data."
"Fantastic practical lesson! I've been looking for a way to visualize geospatial data in Python... Perfect for those who learn by doing."
Best suited for learners with existing Python and data visualization basics.
"I found it a bit challenging without prior experience in data visualization libraries. The pace was fast for a complete beginner."
"I struggled with this course... I think it assumes more prior knowledge than stated. I needed more foundational teaching."
"While it teaches you to build a heatmap, it doesn't deeply explain the underlying concepts. I had to look up some Folium documentation outside."
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 Crime Zone Heatmaps with Python and Folium with these
activities:
Read 'Data Visualization: The Fundamentals' by Andy Kirk
Show steps
Gain a foundational understanding of data visualization principles and best practices by reading this comprehensive book.
View
Introduction to Data Visualisation
on Amazon
Show steps
-
Purchase or borrow a copy of the book.
-
Set aside dedicated time each week to read the book.
-
Take notes and highlight key concepts as you read.
-
Apply the principles you learn to your own data visualization projects.
Form a study group with other students in the course
Show steps
Enhance your understanding of the course material and improve your problem-solving skills by collaborating with peers.
Show steps
-
Identify other students in the course who are willing to form a study group.
-
Set regular meeting times and locations.
-
Prepare for each meeting by reviewing the course material and identifying areas where you need support.
-
Meet with your group, discuss the material, and work through problems together.
Attend a data visualization conference or meetup
Show steps
Connect with other data visualization professionals, learn about the latest trends, and get inspired by innovative projects.
Browse courses on
Data Visualization
Show steps
-
Research upcoming data visualization conferences or meetups in your area.
-
Register for the event and make plans to attend.
-
Attend the event, engage with other attendees, and learn from the speakers.
-
Follow up with any connections you make at the event.
Four other activities
Expand to see all activities and additional details
Show all seven activities
Follow tutorials on advanced data visualization techniques
Show steps
Expand your knowledge of data visualization techniques by following tutorials on advanced topics.
Browse courses on
Data Visualization
Show steps
-
Identify specific data visualization techniques you want to learn more about.
-
Search for tutorials or online courses that cover these techniques.
-
Follow the tutorials step-by-step, taking notes and experimenting with the code.
-
Apply the techniques you've learned to your own data visualization projects.
Work through Python practice problems
Show steps
Strengthen your understanding of Python syntax and coding concepts through practice drills.
Browse courses on
Python
Show steps
-
Locate a collection of Python practice problems online.
-
Start working through the problems, one at a time.
-
Take breaks as needed, and review any documentation or resources you need.
-
Once you've completed a problem, check your solution against the provided answer key.
Create an animated heatmap of weather data
Show steps
Reinforce your skills in data manipulation, visualization, and animation by creating an animated heatmap of weather data.
Browse courses on
Data Visualization
Show steps
-
Gather weather data for a specific location and time period.
-
Clean and preprocess the data, removing any outliers or missing values.
-
Use Python and a data visualization library to create an animated heatmap of the data.
-
Export the heatmap as a video or interactive visualization.
Contribute to an open-source data visualization library
Show steps
Deepen your understanding of data visualization techniques and contribute to the community by participating in an open-source project.
Browse courses on
Open Source
Show steps
-
Identify an open-source data visualization library that interests you.
-
Review the library's documentation and codebase.
-
Identify an area where you can contribute, such as adding a new feature or fixing a bug.
-
Submit a pull request with your proposed changes.
Read 'Data Visualization: The Fundamentals' by Andy Kirk
Show steps
Gain a foundational understanding of data visualization principles and best practices by reading this comprehensive book.
View
Introduction to Data Visualisation
on Amazon
Show steps
Show steps
Show steps
- Purchase or borrow a copy of the book.
- Set aside dedicated time each week to read the book.
- Take notes and highlight key concepts as you read.
- Apply the principles you learn to your own data visualization projects.
Form a study group with other students in the course
Show steps
Enhance your understanding of the course material and improve your problem-solving skills by collaborating with peers.
Show steps
Show steps
Show steps
- Identify other students in the course who are willing to form a study group.
- Set regular meeting times and locations.
- Prepare for each meeting by reviewing the course material and identifying areas where you need support.
- Meet with your group, discuss the material, and work through problems together.
Attend a data visualization conference or meetup
Show steps
Connect with other data visualization professionals, learn about the latest trends, and get inspired by innovative projects.
Browse courses on
Data Visualization
Show steps
Show steps
Show steps
- Research upcoming data visualization conferences or meetups in your area.
- Register for the event and make plans to attend.
- Attend the event, engage with other attendees, and learn from the speakers.
- Follow up with any connections you make at the event.
Four other activities
Expand to see all activities and additional details
Show all seven activities
Follow tutorials on advanced data visualization techniques
Show steps
Expand your knowledge of data visualization techniques by following tutorials on advanced topics.
Browse courses on
Data Visualization
Show steps
Show steps
Show steps
- Identify specific data visualization techniques you want to learn more about.
- Search for tutorials or online courses that cover these techniques.
- Follow the tutorials step-by-step, taking notes and experimenting with the code.
- Apply the techniques you've learned to your own data visualization projects.
Work through Python practice problems
Show steps
Strengthen your understanding of Python syntax and coding concepts through practice drills.
Browse courses on
Python
Show steps
Show steps
Show steps
- Locate a collection of Python practice problems online.
- Start working through the problems, one at a time.
- Take breaks as needed, and review any documentation or resources you need.
- Once you've completed a problem, check your solution against the provided answer key.
Create an animated heatmap of weather data
Show steps
Reinforce your skills in data manipulation, visualization, and animation by creating an animated heatmap of weather data.
Browse courses on
Data Visualization
Show steps
Show steps
Show steps
- Gather weather data for a specific location and time period.
- Clean and preprocess the data, removing any outliers or missing values.
- Use Python and a data visualization library to create an animated heatmap of the data.
- Export the heatmap as a video or interactive visualization.
Contribute to an open-source data visualization library
Show steps
Deepen your understanding of data visualization techniques and contribute to the community by participating in an open-source project.
Browse courses on
Open Source
Show steps
Show steps
Show steps
- Identify an open-source data visualization library that interests you.
- Review the library's documentation and codebase.
- Identify an area where you can contribute, such as adding a new feature or fixing a bug.
- Submit a pull request with your proposed changes.
Career center
Learners who complete Crime Zone Heatmaps with Python and Folium will develop knowledge and skills
that may be useful to these careers:
Geographic Information Systems (GIS) Analyst
Geographic Information Systems (GIS) Analyst
GIS Analysts use geographic information systems (GIS) to analyze and visualize spatial data. This course provides a solid foundation in spatial analysis and visualization, which are essential skills for GIS Analysts.
Law Enforcement Officer
Law Enforcement Officer
Law Enforcement Officers enforce the law and maintain public order. This course may be useful for Law Enforcement Officers who are interested in developing their skills in crime analysis and visualization.
Police Officer
Police Officer
Police Officers protect and serve the community. This course may be useful for Police Officers who are interested in developing their skills in crime analysis and visualization.
Urban Planner
Urban Planner
Urban Planners design and implement plans for the development of urban areas. This course may be useful for Urban Planners who are interested in developing their skills in crime analysis and visualization.
Data Scientist
Data Scientist
Data Scientists use data to solve complex problems and improve decision-making. This course provides an introduction to spatial analysis and visualization, which are valuable skills for Data Scientists.
Cartographer
Cartographer
Cartographers translate and display geographical data into maps and charts. Crime analysis and visualization are relevant to this role. This course helps build a foundation in spatial analysis and visualization, enabling you to create informative maps for effective decision-making.
Sociologist
Sociologist
Sociologists study human behavior and society. This course may be useful for Sociologists who are interested in developing their skills in crime analysis and visualization.
Market Research Analyst
Market Research Analyst
Market Research Analysts collect and analyze data on consumer behavior and market trends. This course may be useful for Market Research Analysts who are interested in developing their skills in crime analysis and visualization.
Data Analyst
Data Analyst
Data Analysts collect, analyze, and interpret data to identify trends and patterns. This course may be useful for Data Analysts who are interested in developing their skills in crime analysis and visualization.
Public Safety Officer
Public Safety Officer
Public Safety Officers protect the public from harm. This course may be useful for Public Safety Officers who are interested in developing their skills in crime analysis and visualization.
Geographer
Geographer
Geographers study the Earth's physical and human characteristics. This course may be useful for Geographers who are interested in developing their skills in crime analysis and visualization.
Journalist
Journalist
Journalists investigate and report on news events. This course may be useful for Journalists who are interested in developing their skills in crime analysis and visualization.
Information Security Analyst
Information Security Analyst
Information Security Analysts design and implement security measures to protect information systems from unauthorized access, use, disclosure, disruption, modification, or destruction. This course may be useful for Information Security Analysts who are interested in developing their skills in crime analysis and visualization.
Risk Analyst
Risk Analyst
Risk Analysts identify and assess risks to an organization or individual. This course may be useful for Risk Analysts who are interested in developing their skills in crime analysis and visualization.
Social Worker
Social Worker
Social Workers help people address social and emotional problems. This course may be useful for Social Workers who are interested in developing their skills in crime analysis and visualization.
For more career information including salaries, visit:
OpenCourser.com/course/2q29tu/crime
Reading list
We've selected eight books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
Crime Zone Heatmaps with Python and Folium.
Provides a comprehensive overview of data analysis using Python, covering topics such as data cleaning, wrangling, visualization, and modeling.
This handbook provides a comprehensive overview of criminology, including topics such as crime theory, crime patterns, and crime prevention.
This handbook provides a comprehensive overview of criminological theory, including topics such as classical theory, positivist theory, and postmodern theory.
Save
Provides a good overview of crime mapping and the use of GIS for crime analysis. It does not go into depth on data visualization techniques.
Covers web-based data visualization. It focuses on d3.js, which is not used in this course, but provides insights into the principles of creating interactive data visualizations.
Provides a comprehensive overview of spatial data analysis using R, including topics such as data cleaning, wrangling, visualization, and modeling.
Provides a good overview of crime mapping and the use of GIS for crime analysis. It does not go into depth on data visualization techniques.
Provides a good overview of the relationship between crime and public policy. It does not go into depth on data visualization techniques.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/2q29tu/crime
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