Python Geospatial Data Analysis from Coursera

Note: Read the prerequisites carefully. If you do not know intermediate pandas and intermediate Python you will not be able to understand this project. This guided project is for beginners who want to learn about geospatial data analysis using Python. You will analyze crime data from the Boston Police Department. It is a clean dataset, so you can get straight to generating interactive maps. While you are watching me code, you will get a cloud desktop with all the required software pre-installed. This will allow you to code along with me. After all, we learn best with active, hands-on learning. Generate interactive maps in under an hour, just like this: https://vinitasilaparasetty.github.io/coursera-spatial-data-analysis/ By the end of this project, you will know how to generate maps using folium and analyze geospatial data using geovisualization. Then you will learn how to identify possible contributing factors for the problem statement. Special Features: 1) Learn a cool hack using one line of code to convert a jupyter notebook into a dashboard. 2) After you complete this project, you get a jupyter notebook of all the work you covered. It acts as a useful learning tool that you can refer to at any time in the future. 3) Examples for logical thinking required for geospatial data analysis are provided. Note: This course works best for learners who are based in the North America region. Weâ€™re currently working on providing the same experience in other regions.

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Builds a foundation in geospatial analysis using Python, including folium for interactive maps, making it suitable for beginners interested in GIS and data visualization

Perfect for learners with intermediate proficiency in Python and pandas, easing comprehension of the course material

Provides step-by-step guidance with hands-on exercises, enabling active learning and effective skill development

Converts Jupyter notebooks into interactive dashboards with a simple one-line code, enhancing the usability and accessibility of analytical insights

Presents real-life examples of geospatial analysis using Boston Police Department crime data, facilitating practical learning and understanding

Requires intermediate proficiency in pandas and Python, potentially limiting accessibility for learners with lower levels of experience

Reviews summary

Geospatial python analysis

This course provides a concise introduction to geospatial data analysis using Python. Though the course can feel rush, learners have enjoyed creating interactive maps with the included Jupyter notebooks.

This course is great for beginners who need to learn the basics of geospatial data analysis.

"This course provides a concise introduction to geospatial data analysis using Python."

"This project is quite an eye-opener for me in the field of geospatial analysis."

The course provides many opportunities to practice with Jupyter notebooks.

"Education was excellent."

"It was very enjoyable and educational to produce a crime heat map with codes in a virtual environment."

"you can use what you learn in many projects"

The code used in this course often results in errors.

"Multiple crashes and unexplained errors when copying the code verbatim from the video."

"The code was written isn’t working and there is no resource for assistance."

The course lacks explanation and context for the code.

"The concepts involved are not explained clearly."

"It'd have helped if the code was explained slightly."

"I thought it would be a guided course with step-to-step explanations for the applied commands."

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 Python Geospatial Data Analysis with these activities:

Review basics of pandas and Python

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This activity will help you brush up on the basics of pandas and Python, which are essential for this course. This will help ensure that you have a solid foundation in these concepts, and can quickly follow along with the course material.

Browse courses on Python Basics

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Find a tutorial on the basics of pandas.
Follow the tutorial to learn how to import data, clean data, and perform basic data analysis tasks in pandas.
Find a tutorial on the basics of Python.
Follow the tutorial to learn about variables, data types, and control flow in Python.

Python basics review

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Ensure a strong foundation in Python by reviewing basic concepts to prepare for the course's technical aspects.

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Review Python syntax and data types
Practice writing simple Python scripts

Spatial Data Analysis in GIS

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Expand knowledge of spatial data analysis concepts and techniques by reading an introductory text, providing a theoretical foundation for the course.

View Melania on Amazon

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Read the selected chapters
Take notes on key concepts
Apply the concepts to the course work

Six other activities

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Folium documentation review

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Become familiar with the capabilities and usage of Folium to prepare for creating interactive maps during the course.

Browse courses on Folium

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Read the Folium documentation
Review examples and tutorials

Analyze sample dataset

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Develop an understanding of the crime data and identify potential patterns or insights for further exploration during the course.

Browse courses on Exploratory Data Analysis

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Load the crime data into a Python environment
Perform basic data exploration
Identify any interesting patterns or trends

Interactive coding with Jupyter notebook

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Practice coding to reinforce understanding of basic Python concepts and become comfortable with the Jupyter notebook environment.

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Set up a Jupyter notebook environment
Write code to analyze sample data
Troubleshoot any errors that arise

Discussion forum participation

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Engage with peers to discuss course concepts, ask questions, and share insights, fostering a collaborative learning environment.

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Join the course discussion forum
Participate in discussions
Answer questions from other students

Interactive map project

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Apply the concepts of geospatial data analysis and interactive mapping to a practical project, solidifying knowledge and skills.

Browse courses on Geospatial Data Analysis

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Choose a geospatial data source
Prepare the data for analysis
Create an interactive map using Folium
Analyze and interpret the results

Contribute to Folium project

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Deepen understanding of Folium by actively contributing to its development, gaining practical experience and enhancing the library's capabilities.

Browse courses on Folium

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Identify an area to contribute to
Submit a pull request
Provide documentation and testing

Career center

Learners who complete Python Geospatial Data Analysis will develop knowledge and skills that may be useful to these careers:

GIS Analyst

GIS Analysts are responsible for collecting, analyzing, and presenting geographical information. The skills learned in Python Geospatial Data Analysis, such as generating interactive maps and analyzing geospatial data using geovisualization, can be essential for GIS Analysts. The course may also help GIS Analysts build a foundation in Python, which is a popular programming language for GIS.

See salaries and explore the career path for GIS Analyst

Geospatial Analyst

Geospatial Analysts use geospatial data to solve real-world problems. The skills learned in Python Geospatial Data Analysis, such as analyzing geospatial data using geovisualization, can be valuable for Geospatial Analysts. The course may also help Geospatial Analysts build a foundation in Python, which is a popular programming language for geospatial analysis.

See salaries and explore the career path for Geospatial Analyst

Cartographer

Cartographers are responsible for creating maps. The skills learned in Python Geospatial Data Analysis, such as generating interactive maps and analyzing geospatial data using geovisualization, can be essential for Cartographers. The course may also help Cartographers build a foundation in Python, which is a popular programming language for geospatial analysis.

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Data Visualization Specialist

Data Visualization Specialists are responsible for creating visual representations of data. The skills learned in Python Geospatial Data Analysis, such as generating interactive maps and analyzing geospatial data using geovisualization, can be valuable for Data Visualization Specialists who are working with data with geographical components. The course may also help Data Visualization Specialists build a foundation in Python, which is a popular programming language for data analysis.

See salaries and explore the career path for Data Visualization Specialist

Business Intelligence Analyst

Business Intelligence Analysts are responsible for using data to help businesses make informed decisions. The skills learned in Python Geospatial Data Analysis, such as analyzing geospatial data using geovisualization, can be useful for Business Intelligence Analysts who are working with data with geographical components. The course may also help Business Intelligence Analysts build a foundation in Python, which is a popular programming language for data analysis.

See salaries and explore the career path for Business Intelligence Analyst

Market Research Analyst

Market Research Analysts are responsible for conducting and interpreting market research. The skills learned in Python Geospatial Data Analysis, such as analyzing geospatial data using geovisualization, can be useful for Market Research Analysts who are working with data with geographical components. The course may also help Market Research Analysts build a foundation in Python, which is a popular programming language for data analysis.

See salaries and explore the career path for Market Research Analyst

Data Scientist

Data Scientists are responsible for using data to solve real-world problems. The skills learned in Python Geospatial Data Analysis, such as analyzing geospatial data using geovisualization, can be useful for Data Scientists who are working with data with geographical components. The course may also help Data Scientists build a foundation in Python, which is a popular programming language for data analysis.

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Data Analyst

Data Analysts help businesses make informed decisions using data analysis and data visualization techniques. The skills learned in Python Geospatial Data Analysis, such as analyzing geospatial data using geovisualization, can be valuable for Data Analysts who are managing data with geographical components. The course may also help Data Analysts build a foundation in Python, which is a popular programming language for data analysis.

See salaries and explore the career path for Data Analyst

Financial Analyst

Financial Analysts are responsible for analyzing and interpreting financial data. The skills learned in Python Geospatial Data Analysis, such as analyzing geospatial data using geovisualization, can be useful for Financial Analysts who are working with data with geographical components. The course may also help Financial Analysts build a foundation in Python, which is a popular programming language for data analysis.

See salaries and explore the career path for Financial Analyst

Environmental Scientist

Environmental Scientists are responsible for studying and protecting the environment. The skills learned in Python Geospatial Data Analysis, such as analyzing geospatial data using geovisualization, can be useful for Environmental Scientists who are working with data with geographical components. The course may also help Environmental Scientists build a foundation in Python, which is a popular programming language for data analysis.

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Transportation Planner

Transportation Planners are responsible for planning and managing transportation systems. The skills learned in Python Geospatial Data Analysis, such as analyzing geospatial data using geovisualization, can be useful for Transportation Planners who are working with data with geographical components. The course may also help Transportation Planners build a foundation in Python, which is a popular programming language for data analysis.

See salaries and explore the career path for Transportation Planner

Urban Planner

Urban Planners are responsible for planning and managing the physical development of cities and towns. The skills learned in Python Geospatial Data Analysis, such as analyzing geospatial data using geovisualization, can be useful for Urban Planners who are working with data with geographical components. The course may also help Urban Planners build a foundation in Python, which is a popular programming language for data analysis.

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Statistician

Statisticians are responsible for collecting, analyzing, and interpreting data. The skills learned in Python Geospatial Data Analysis, such as analyzing geospatial data using geovisualization, can be useful for Statisticians who are working with data with geographical components. The course may also help Statisticians build a foundation in Python, which is a popular programming language for data analysis.

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Geographer

Geographers are responsible for studying the Earth's surface and its inhabitants. The skills learned in Python Geospatial Data Analysis, such as analyzing geospatial data using geovisualization, can be useful for Geographers who are working with data with geographical components. The course may also help Geographers build a foundation in Python, which is a popular programming language for data analysis.

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Climate Scientist

Climate Scientists are responsible for studying the climate and its impact on the environment. The skills learned in Python Geospatial Data Analysis, such as analyzing geospatial data using geovisualization, can be useful for Climate Scientists who are working with data with geographical components. The course may also help Climate Scientists build a foundation in Python, which is a popular programming language for data analysis.

See salaries and explore the career path for Climate Scientist