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

**(Select all that apply.)** Which techniques are data storytelling methods?

(Select all that apply.) Which techniques are data storytelling methods?

Use grey as the color for all the elements of the plot.

Use grey to hide certain elements of the plot.

Which is a good use of the color grey?

Obtaining survey data from all participants attending a program to understand if the program is helping them succeed.

Obtaining data from all the temperature sensors in a room

Obtaining survey data only from participants who participated in a program who can attend the person in-survey

Which is an example of selection bias?

By changing the font size of the labels so they are easy to read

Ensure the scale of the axes is in the same range

How can a data storyteller create consistency in their visualization? 

How can a data storyteller create consistency in their visualization?

Defining and explaining a clear problem statement that the audience cares about

Narrowing down visualizations to a specific group as an example during your narrative

Only talking about one portion of your dataset throughout the narrative

**(Select all that apply.)** Which of the following techniques is the right way of balancing specificity with content as part of a narrative?

(Select all that apply.) Which of the following techniques is the right way of balancing specificity with content as part of a narrative?

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: Storytelling Best Practices