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Introduction

Before We Begin

Effective Data Analysis and Visualization

Creating Data Visualizations: Types and Purpose Identifying Exploratory Questions with EDA Grouping Our Dataset Analyze Trends in Data Over Time Analyze Correlations Analyze Comparisons Analyze Contrastive Data Quiz: Effective Data Analysis and Visualization

Extracting Narratives from Data

Case Study: Defining Data-Driven Problem Statements Implement Iterative Data Visualization Tailor Visualizations to Your Audience Characterize Personas from Your Data Identifying Context: Correlation vs. Causation Quiz: Extracting Narratives from Data

Tackling Real-World Data

Visualizing Outliers

Handling Missing Data

Forecasting Trends

Visualizing Machine Learning Predictions

Filter Information from Large Datasets

Quiz: Tackling Real-World Data

Project

Time Series Analysis and Visualization Using Python and Plotly

Data Presentation

Engaging Your Audience Layering Compiling Visualizations Prepare Visualizations for Presentations Interactive Visualizations Creating Data Dashboards Quiz: Data Presentation

Data Types and Sources

Preparing to Integrate Data from Additional Sources Text Data Visualization Image Data Visualization

Project

Data Visualization with Seaborn for Walmart Sales Projection

Data Storytelling Best Practices

Keeping Visualizations Concise Color Schemes Consistency Balance Specificity with Content Unbiased Analysis and Interpretation Quiz: Storytelling Best Practices

Wrapping Up

Course Assessment

Test Your Data Storytelling Skills

Data Storytelling through Visualizations in Python/

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Quiz: Tackling Real-World Data

Quiz: Tackling Real-World Data

Test your understanding of tackling real-world data.

We'll cover the following...

Tackling Real-World Data

1.

(Select all that apply.) Which plots can be used to effectively visualize outliers?

A.

Box plots

B.

Histograms

C.

Line plots

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