Data Visualization with Python

Data Visualization with Python

This course is part of Applied Python Data Engineering Specialization

Instructors: Matt Harrison

What you'll learn

Apply Python, spreadsheets, and BI tooling proficiently to create visually compelling and interactive data visualizations.
Formulate and communicate data-driven insights and narratives through impactful visualizations and data storytelling.
Assess and select the most suitable visualization tools and techniques to address organizational data needs and objectives.

Details to know

Shareable certificate

Add to your LinkedIn profile

Assessments

4 assignments

Taught in English

See how employees at top companies are mastering in-demand skills

Learn more about Coursera for Business

Build your subject-matter expertise

This course is part of the Applied Python Data Engineering Specialization

When you enroll in this course, you'll also be enrolled in this Specialization.

Learn new concepts from industry experts
Gain a foundational understanding of a subject or tool
Develop job-relevant skills with hands-on projects
Earn a shareable career certificate

Earn a career certificate

Add this credential to your LinkedIn profile, resume, or CV

Share it on social media and in your performance review

There are 4 modules in this course

In today's data-driven world, the ability to create compelling visualizations and tell impactful stories with data is a crucial skill. This comprehensive course will guide you through the process of visualization using coding tools with Python, spreadsheets, and BI (Business Intelligence) tooling. Whether you are a data analyst, a business professional, or an aspiring data storyteller, this course will provide you with the knowledge and best practices to excel in the art of visual storytelling.

Throughout the course, a consistent dataset will be used for exercises, enabling you to focus on mastering the visualization tools rather than getting caught up in the intricacies of the data. The emphasis is on practical application, allowing you to learn and practice the tools in a real-world context. To fully leverage the Python sections of this course, prior experience programming in Python is recommended. Additionally, a solid understanding of high-school level math is expected. Familiarity with the Pandas library will also be beneficial. By the end of this course, you will possess the necessary skills to become a proficient data storyteller and visual communicator. With the ability to create compelling visualizations and leverage the appropriate tools, you will be well-equipped to navigate the world of data and make informed decisions that drive meaningful impact.

In this module, we will introduce you to the fundamentals of data visualization and provide step-by-step guidance on how to get started with creating basic plots in Excel and Google Sheets. Whether you are new to data visualization or looking to enhance your skills, this week will lay the groundwork for effective visual storytelling using these widely accessible tools.

What's included

13 videos7 readings1 assignment2 discussion prompts

13 videosTotal 24 minutes

Getting Started with Data Visualization4 minutesPreview module
Introduction to Excel for Visualization0 minutes
Creating a Line Plot in Excel2 minutes
Creating a Histogram in Excel0 minutes
Creating a Scatterplot in Excel0 minutes
Creating a Bar Plot in Excel1 minute
Minimizing Clutter in Visualizations2 minutes
Introduction to Sheets for Visualization0 minutes
Creating a Line Graph in Sheets2 minutes
Creating a Histogram in Sheets0 minutes
Creating a Scatterplot in Sheets1 minute
Creating Bar Plot in Sheets1 minute
Optimizing Color for Visualizations5 minutes

7 readingsTotal 70 minutes

Course Structure10 minutes
Meet your Instructor: Matt Harrison10 minutes
Common Plots Refresher10 minutes
Getting Ready: Accessing Microsoft Excel10 minutes
Plotting Exercise: Excel10 minutes
Getting Ready: Accessing Google Sheets10 minutes
Plotting Exercise: Google Sheets10 minutes

1 assignmentTotal 30 minutes

Data Visualization Fundamentals with Excel and Sheets30 minutes

2 discussion promptsTotal 20 minutes

Meet and Greet (optional)10 minutes
Plotting Exercise Discussion10 minutes

In this module, you will embark on an exciting journey of learning as you explore data visualization using Pandas, Seaborn and Matplotlib. You will use Pandas and Seaborn to construct histograms, which will allow you to gain insights into the distribution of your numerical data. You will also delve into scatterplots, enabling you to visualize the relationships between different variables in your datasets and identify patterns and correlations. Lastly, you will learn how to utilize line plots to capture temporal trends and changes over time, enhancing your ability to communicate data-driven narratives effectively.

What's included

19 videos7 readings1 assignment1 discussion prompt

19 videosTotal 66 minutes

Exploring Basic Plots6 minutesPreview module
Cleaning your Data5 minutes
Creating a Line Plot with Pandas8 minutes
Creating a Bar Plot with Pandas4 minutes
Creating a Scatterplot with Pandas3 minutes
Creating More Complicated Plots with Pandas0 minutes
Creating a Heatmap with Pandas6 minutes
Creating a Slope Graph with Pandas4 minutes
Chaining Methods with Pandas6 minutes
Introduction to the Seaborn Library1 minute
Creating a Line Plot with Seaborn1 minute
Creating a Bar Plot with Seaborn2 minutes
Creating a Scatterplot with Seaborn1 minute
Creating a Heatmap with Seaborn1 minute
Creating a Slope Graph with Seaborn2 minutes
Introduction to Matplotlib in Python0 minutes
Customizing Text with Matplotlib4 minutes
Customizing Color with Matplotlib2 minutes
Customizing Axes with Matplotlib2 minutes

7 readingsTotal 70 minutes

Getting Ready: Accessing Python and Pandas10 minutes
Pandas Resample, Groupby, and Rolling (optional)10 minutes
Plotting Exercise: Pandas10 minutes
Getting Ready: Installing Seaborn10 minutes
Plotting Exercise: Seaborn10 minutes
Getting Ready: Installing Matplotlib Libraries10 minutes
Plotting Exercise: MatPlotLib10 minutes

1 assignmentTotal 30 minutes

Data Visualization with Pandas, Seaborn and Matplotlib30 minutes

1 discussion promptTotal 10 minutes

Plotting Exercise Discussion10 minutes

In this module, you will explore the powerful combination of Plotly, Dash, and Streamlit for creating interactive and dynamic visualizations within a dashboard. You will use Plotly to create visually appealing histograms, scatterplots, and line plots that can be embedded within a dashboard. You will also dive into Dash and Streamlit, two popular Python frameworks for building interactive web-based dashboards. By the end of the week, you will be able to apply your knowledge and create a comprehensive dashboard that incorporates these visualizations, enabling users to explore and interact with your data.

What's included

15 videos6 readings1 assignment1 discussion prompt

15 videosTotal 27 minutes

Introduction to Plotly1 minutePreview module
Creating a Line Plot with Plotly2 minutes
Creating a Bar Plot with Plotly0 minutes
Creating a Scatterplot with Plotly1 minute
Creating a Heatmap with Plotly1 minute
Creating a Slope Graph with Plotly2 minutes
Introduction to Dash0 minutes
Creating a Line Plot with Dash2 minutes
Creating a Bar Plot with Dash3 minutes
Creating a Scatterplot with Dash5 minutes
Introduction to Streamlit0 minutes
Creating a Line Plot with Streamlit1 minute
Creating a Bar Plot with Streamlit0 minutes
Connecting a Widget to a Plot in Streamlit1 minute
Creating a Scatterplot with Streamlit1 minute

6 readingsTotal 60 minutes

Getting Ready: Accessing Plotly10 minutes
Plotting Exercise: Plotly10 minutes
Getting Ready: Accessing Dash10 minutes
Plotting Exercise: Dash10 minutes
Getting Ready: Accessing Streamlit10 minutes
Plotting Exercise: Streamlit10 minutes

1 assignmentTotal 30 minutes

Data Visualization with Plotly, Dash and Streamlit30 minutes

1 discussion promptTotal 10 minutes

Plotting Exercise Discussion10 minutes

In this module, you will dive into two cloud-based tools, Tableau and Amazon QuickSight, to create compelling visualizations, and gain insights from your data in a user-friendly and interactive manner. You will first use Tableau to design and create histograms, scatterplots, and line plots that effectively showcase your data. You will then use Amazon QuickSight, an intuitive and cloud-based business intelligence tool, to create visually appealing and interactive visualizations. By the end of the week, you will be able to apply your knowledge and create captivating visualizations using these platforms.