Gain insights into data storytelling in Python using Matplotlib, Seaborn, and Plotly. Explore trends, handle data challenges, and create impactful visual narratives aligning with business goals.

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Mining the insights from data is the next critical step after parsing data and generating visualizations. This activity is called data storytelling, where you form a cohesive story explaining the strengths, weaknesses, and trends of your dataset with the help of predictions through machine learning models. 

In this course, you will learn how to identify and evaluate your data for trends, handle common real-world challenges of messy data such as large datasets and missing values, and present the right visualizations for different kinds of data. We will use Python, Matplotlib, Seaborn, and Plotly as the data science libraries for this course.

This course will help you develop the key skills to translate the technical indicators in line with business objectives. It also aids in building your technical skills and processes to create effective data visualizations and narratives. Data storytelling can help you unlock actionable insights from your data.

Data Storytelling through Visualizations in Python

Determining the event or problem statement that the narrative will cover.

Identifying the next steps for an audience.

Creating a visualization dashboard for the audience to get a grasp of key trends.

What is the first step of a typical data storytelling process?

What is the first step of a typical data storytelling process?

Frank is focusing on growth opportunities revealed by the ad scheme. 

Frank is focusing on pain points revealed by the ad scheme.

Frank is using data storytelling to demonstrate how adopting a new advertisement scheme can increase the conversion rate for their company's website. 

Frank is now putting together a narrative from data from preliminary A/B testing. They want to present the insights to their executive management. 

How would you define the purpose of the story they are telling?

Frank is using data storytelling to demonstrate how adopting a new advertisement scheme can increase the conversion rate for their company’s website.
Frank is now putting together a narrative from data from preliminary A/B testing. They want to present the insights to their executive management.
How would you define the purpose of the story they are telling?

A bar plot showing the representation of satisfied customers who converted.

A line plot showing customers' conversion rate over time.

A box plot showing outliers, where 3 out of 50 customers interacted with the ad incorrectly.

**(Select all that apply.)** Which visualizations would be the most effective for Frank to help tailor their data storytelling strategy to their audience?

(Select all that apply.) Which visualizations would be the most effective for Frank to help tailor their data storytelling strategy to their audience?

Identify a causal context between the variables.

Use additional data (e.g., data from the weather or news) to help identify the context.

Create a context that you think best seems to tell the story.

What is an effective way to better understand the relationship between variables in a dataset beyond visualizations?

What is an effective way to better understand the relationship between variables in a dataset beyond visualizations?

Extracting Narratives From Data

Extracting Narratives From Data

Test your understanding of extracting narratives from data.

Introduction

Effective Data Analysis and Visualization

Extracting Narratives from Data

Tackling Real-World Data

Data Presentation

Data Types and Sources

Data Storytelling Best Practices

Wrapping Up

Test Your Data Storytelling Skills

Quiz: Extracting Narratives from Data