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.

Data Storytelling- Efficient Data Visualization and Narratives  (1).png

plotly_bokeh.tar.gz

plotly and bokeh

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

The probability that their dataset is incorrect

What do bar plots help data scientists understand?

What do bar plots help data scientists understand?

Which pandas operation is a correct way to create a subset of the data for x = 1?

Which pandas operation is a correct way to create a subset of the data for x = 1?

**(Select all that apply.)** Which of the following are examples of contrastive data analysis?

(Select all that apply.) Which of the following are examples of contrastive data analysis?

`df.plot.line(x=df['year'], y=df['pop'])`


You are trying to plot a line plot between the `x` and the `y` variable, but the line plot appears completely zig zagged.

What could be missing from the below code block?

<pre><code>
df= df[['x', 'y']]
df.plot.line(x, y)
</code></pre>

You are trying to plot a line plot between the <code>x</code> and the <code>y</code> variable, but the line plot appears completely zig zagged.
What could be missing from the below code block?
<pre><code>
df= df[['x', 'y']]
df.plot.line(x, y)
</code></pre>

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: Effective Data Analysis and Visualization