Gain the skills to transform data into stories, using the DIKW pyramid and the Altair Python library.

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Tool Z Familiarity

Altair, a versatile Python library, empowers you to craft visually compelling and interactive data visualizations. Acquiring proficiency in Altair unlocks new avenues for effectively conveying insights and narratives through data.

The course begins by introducing the concept of data storytelling and the DIKW pyramid. Then, you’ll learn why Altair is a valuable tool for developers interested in data storytelling and how it can enhance their ability to effectively communicate complex ideas. Next, the course takes a sequential approach to cover the DIKW model for data storytelling, which provides a structured framework for organizing and presenting data narratives. Finally, you’ll implement two practical use cases.

After taking this course, you’ll have acquired the skills and knowledge to build compelling data stories that combine Altair and the DIKW pyramid. You will be able to create engaging and impactful visualizations that effectively convey insights and build narratives from data.

Using Python Altair for Data Storytelling

By using the `transform_aggregate()` method

By creating separate encoding channels for each step

In Altair, how do we implement each step of knowledge extraction as a separate layer in a chart?

In Altair, how do we implement each step of knowledge extraction as a separate layer in a chart?

`alt.Chart(df).mark_bar().encode(
    x = alt.X('x'),
    y = alt.Y('y')
).properties(title='My title').configure_title(fontSize=25)`

`alt.Chart(df).mark_bar().encode(
    x = alt.X('x'),
    y = alt.Y('y')
).properties(title='My title', fontSize=25)`

`alt.Chart(df).mark_bar().encode(
    x = alt.X('x'),
    y = alt.Y('y')
).properties(title='My title', titleFontSize=25)`

`alt.Chart(df).mark_bar(titleFontSize=25).encode(
    x = alt.X('x'),
    y = alt.Y('y')
).properties(title='My title')`

Which code snippet sets the title font size to `25` px in a bar chart?

Which code snippet sets the title font size to <code>25</code> px in a bar chart?

`alt.Chart(df).mark_circle(size=200).encode(
  x=alt.X('x'),
  y=alt.Y('y'),
  color=alt.Color('z', scale=alt.Scale(scheme='blues'))
)`

`alt.Chart(df).mark_circle(size=200).encode(
  x='x',
  y='y',
  color=alt.Color('z', scale=alt.Scale(range=['lightblue', 'darkblue']))
)`

`alt.Chart(df).mark_circle(size=200).encode(
  x='x',
  y='y',
  color=alt.condition(alt.datum.x > 0, alt.value('lightblue'), alt.value('darkblue'))
)`

Which code snippet produces the following chart?

<img src='/udata/4z0rDymGPgq/quiz6_q3.png'>

Which code snippet produces the following chart?
<img src='/udata/4z0rDymGPgq/quiz6_q3.png'>

The chart is potentially misleading because the y-axis is truncated.

Apart from some details, the chart is made well and clearly communicates the following message: oranges outperform other fruits.

The chart describes raw data and requires further improvement to extract meaning and knowledge.

**(Select all that apply.)** What problems does the following chart present?

<img src='/udata/zO402a7zDbQ/quiz6_q4.png'>

(Select all that apply.) What problems does the following chart present?
<img src='/udata/zO402a7zDbQ/quiz6_q4.png'>

Test yourself on what you’ve learned in this chapter. 

What is Data Storytelling?

Using Altair for Data Storytelling

The DIKW Pyramid

Introducing the Concept of Data

Getting Familiar with Unknown Data

Assessment 1

Introducing the Concept of Information

Data Modeling

Knowledge

Wisdom

Assessment 2

Case Studies

Wrap Up

Appendix

Quiz: Knowledge