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Mining Data to Extract and Visualize Insights in Python

By the end of this project, you will learn how to load and extract useful information from your dataset using Python, a free, open-source program that you can download. You will then learn how to clean your data set by removing unwanted whitespaces, columns containing several empty values, rows containing empty column values and duplicated row entries. Next, you will create various visualizations to identify patterns and outliers in your dataset, and visualize correlations between different columns. Lastly, you will learn how to visualize a highly dimensional dataset using principal component analysis (PCA). These steps are part of exploratory data analysis that you will need to carry out for any data science project to help you understand your dataset. 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.

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Well suited for those starting an exploratory data analysis project

Uses free and open source software

Relevant to any data science project

May be suboptimal for learners outside North America due to regional restrictions

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Reviews summary

Helpful course on mining data in python

Mining Data to Extract and Visualize Insights in Python is a helpful course for beginners who are interested in using Python for data analysis. The course covers topics such as loading and extracting data, cleaning data, creating visualizations, and using principal component analysis. While the course is well-designed, some students have found the interface frustrating and the pace of the lectures to be slow.

Course is designed well

"The course itself is designed well"

Good for beginners

"Good Course for beginners!"

Learned new things

"Learned some new insights in DATA ANALYSING"

"Great course, I have learn many new things."

Slow pace

"the gaps taken by the instructor while he types feels like a waste of time"

Frustrating interface

"The course itself is designed well, but the interface is frustrating"

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 Mining Data to Extract and Visualize Insights in Python with these activities:

Review 'Python for Data Analysis'

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Strengthen foundational knowledge of Python for data analysis.

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Read chapters on data loading, cleaning, and visualization.
Complete practice exercises to reinforce concepts.

Organize course notes and assignments

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Enhance understanding by organizing and reviewing course materials.

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Create a system for organizing notes and assignments.
Regularly review and summarize key concepts.

Follow tutorials on advanced data cleaning techniques

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Enhance data cleaning skills by exploring advanced techniques and best practices.

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Identify and remove outliers using statistical methods.
Handle missing values using imputation techniques.
Automate data cleaning processes using Python libraries.

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Participate in peer code review sessions

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Improve coding skills and understanding of best practices through peer feedback.

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Share code with peers for review.
Provide constructive feedback on peers' code.

Create a visualization dashboard

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Solidify understanding of data visualization techniques and interactive dashboard creation.

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Use a Python library to create visualizations (e.g., matplotlib, seaborn).
Design an interactive dashboard using a tool (e.g., Plotly, Dash).
Deploy the dashboard for sharing and collaboration.

Develop a data exploration report

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Apply data exploration concepts to a real-world dataset and present findings.

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Choose a dataset and define exploration goals.
Use Python libraries to explore and analyze the data.
Create visualizations and tables to present insights.
Write a report summarizing the exploration and findings.

Build a data visualization dashboard for a specific industry

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Apply course concepts to a real-world project and deepen understanding of data visualization.

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Identify an industry and specific use case for the dashboard.
Gather and prepare the necessary data.
Design and develop the dashboard using Python libraries.
Deploy and share the dashboard with stakeholders.

Career center

Learners who complete Mining Data to Extract and Visualize Insights in Python will develop knowledge and skills that may be useful to these careers:

Data Analyst

A Data Analyst is responsible for collecting, processing, analyzing, and visualizing data to extract meaningful insights. This course provides a strong foundation for aspiring Data Analysts by teaching them how to clean, manipulate, visualize, and analyze data. The course's focus on using Python, a widely used programming language in the field, makes it particularly relevant to those seeking to enter this career.

See salaries and explore the career path for Data Analyst

Data Scientist

Data Scientists use their expertise in mathematics, statistics, and computer science to gather and analyze data, and extract meaningful insights. This course provides a strong foundation for aspiring Data Scientists by teaching them how to load, clean, and visualize data using Python. The course's focus on data exploration and visualization techniques is particularly relevant to those seeking to enter this field.

See salaries and explore the career path for Data Scientist

Business Analyst

Business Analysts use data to identify and solve business problems. This course provides a strong foundation for aspiring Business Analysts by teaching them how to clean, manipulate, and visualize data to identify patterns and trends. The course's focus on using Python, a widely used programming language in the business world, makes it particularly relevant to those seeking to enter this career.

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Quantitative Analyst

Quantitative Analysts use mathematical and statistical techniques to analyze financial data and make investment decisions. This course provides a strong foundation for aspiring Quantitative Analysts by teaching them how to clean, manipulate, and visualize data, and apply statistical techniques using Python. The course's focus on financial data makes it particularly relevant to those seeking to enter this field.

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Machine Learning Engineer

Machine Learning Engineers build and deploy machine learning models to solve business problems. This course provides a strong foundation for aspiring Machine Learning Engineers by teaching them how to clean, manipulate, and visualize data, and apply machine learning techniques using Python. The course's focus on data exploration and visualization techniques is particularly relevant to those seeking to enter this field.

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Statistician

Statisticians collect, analyze, interpret, and present data. This course provides a strong foundation for aspiring Statisticians by teaching them how to clean, manipulate, and visualize data, and apply statistical techniques using Python. The course's focus on data exploration and visualization techniques makes it particularly relevant to those seeking to enter this field.

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Market Researcher

Market Researchers collect and analyze data to understand market trends and make informed decisions. This course provides a strong foundation for aspiring Market Researchers by teaching them how to clean, manipulate, and visualize data to identify patterns and trends. The course's focus on using Python, a widely used programming language in the marketing field, makes it particularly relevant to those seeking to enter this career.

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Data Engineer

Data Engineers design, build, and maintain data systems. This course provides a strong foundation for aspiring Data Engineers by teaching them how to clean, transform, and load data using Python. The course's focus on data management and data integration techniques makes it particularly relevant to those seeking to enter this field.

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Database Administrator

Database Administrators design, implement, and maintain databases. This course provides a strong foundation for aspiring Database Administrators by teaching them how to install, configure, and monitor databases. The course's focus on data management and data security techniques makes it particularly relevant to those seeking to enter this field.

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Information Architect

Information Architects design and organize information systems. This course provides a strong foundation for aspiring Information Architects by teaching them how to clean, structure, and visualize data. The course's focus on data modeling and data visualization techniques makes it particularly relevant to those seeking to enter this field.

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Data Visualization Engineer

Data Visualization Engineers design and develop data visualizations to communicate data insights. This course provides a strong foundation for aspiring Data Visualization Engineers by teaching them how to clean, transform, and visualize data using Python. The course's focus on data visualization techniques and best practices makes it particularly relevant to those seeking to enter this field.

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Data Journalist

Data Journalists use data to tell stories and inform the public. This course provides a strong foundation for aspiring Data Journalists by teaching them how to clean, manipulate, and visualize data to identify patterns and trends. The course's focus on data storytelling and data visualization techniques makes it particularly relevant to those seeking to enter this field.

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Web Developer

Web Developers design, develop, and maintain websites. This course provides a strong foundation for aspiring Web Developers by teaching them how to use Python to manipulate data and create interactive web applications. The course's focus on data visualization and data manipulation techniques makes it particularly relevant to those seeking to enter this field.

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Software Engineer

Software Engineers design, develop, and maintain software systems. This course provides a strong foundation for aspiring Software Engineers by teaching them how to use Python to manipulate data and create software applications. The course's focus on data structures and algorithms makes it particularly relevant to those seeking to enter this field.

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Reading list

We've selected 13 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 Mining Data to Extract and Visualize Insights in Python.

Python Data Science Handbook

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Provides a comprehensive guide to data analysis using Python, covering topics such as data cleaning, wrangling, exploration, visualization, and modeling.

Mining Data to Extract and Visualize Insights in Python

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Reviews summary

Helpful course on mining data in python

Activities

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