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Data Storytelling through Visualizations in Python

Keeping Visualizations Concise

Explore how to keep data visualizations concise by focusing on essential information, using simple color schemes, and avoiding clutter. Learn to create clear, readable plots that effectively convey your message, ensuring your audience easily interprets your data storytelling visuals.

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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:

Python 3.10.4
# 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 ...