Data Storytelling through Visualizations in Python/

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Keeping Visualizations Concise

Keeping Visualizations Concise

Interact with sample code to understand how to keep visualizations concise.

We'll cover the following...

Ensuring visualizations are concise and only convey the exact information that needs to be put across is critical. Our audience should be able to easily interpret the message our visualizations are trying to convey.

In this section, we'll take a look at both good and bad examples of keeping visualizations concise.

Dataset explanation

For this lesson, we'll take a look at a small dataset of a few data scientists working in the artificial intelligence space. We have constructed a hypothetical DataFrame below:

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# Importing pandas library
import pandas as pd
# Creating a dataframe
df = pd.DataFrame({
    'Name': ['Abby', 'Brian', 'Curtis', 'Dev', 'Emily'],
    'Years working in AI': [5, 5, 10, 15, 30],
    'Year started teaching in AI': [2020, 2020, 2021, 2019, 2015],
})
print(df)

The DataFrame contains the name variable for each of the scientists, the Years ...