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Lære Challenge 2: Exploring Categorical Data | Seaborn
Data Science Interview Challenge
course content

Kursusindhold

Data Science Interview Challenge

Data Science Interview Challenge

1. Python
2. NumPy
3. Pandas
4. Matplotlib
5. Seaborn
6. Statistics
7. Scikit-learn

book
Challenge 2: Exploring Categorical Data

Visualizing categorical data is crucial for gaining insights into how different categories relate to other variables. Categorical data, unlike continuous data, falls into discrete categories or labels. Seaborn, with its suite of powerful tools, provides efficient ways to visualize and interpret such data.

Visualizing categorical variables with Seaborn allows you to:

  • Compare the distribution of a numerical variable across different categories.
  • Visualize the relationships between two categorical variables.
  • Highlight how categorical variables relate to one or more numerical variables.

By leveraging Seaborn's functionalities, one can dive deep into the intricacies of categorical data, enabling a holistic understanding of its nuances.

Opgave

Swipe to start coding

Using Seaborn, dive into the world of categorical data visualization:

  1. Create a box plot to display the distribution of a numerical variable across different categories.
  2. Display the distribution of a numerical variable across different categories using a swarm plot.
  3. Visualize the count of observations in each category using a count plot.

Løsning

Switch to desktopSkift til skrivebord for at øve i den virkelige verdenFortsæt der, hvor du er, med en af nedenstående muligheder
Var alt klart?

Hvordan kan vi forbedre det?

Tak for dine kommentarer!

Sektion 5. Kapitel 2
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book
Challenge 2: Exploring Categorical Data

Visualizing categorical data is crucial for gaining insights into how different categories relate to other variables. Categorical data, unlike continuous data, falls into discrete categories or labels. Seaborn, with its suite of powerful tools, provides efficient ways to visualize and interpret such data.

Visualizing categorical variables with Seaborn allows you to:

  • Compare the distribution of a numerical variable across different categories.
  • Visualize the relationships between two categorical variables.
  • Highlight how categorical variables relate to one or more numerical variables.

By leveraging Seaborn's functionalities, one can dive deep into the intricacies of categorical data, enabling a holistic understanding of its nuances.

Opgave

Swipe to start coding

Using Seaborn, dive into the world of categorical data visualization:

  1. Create a box plot to display the distribution of a numerical variable across different categories.
  2. Display the distribution of a numerical variable across different categories using a swarm plot.
  3. Visualize the count of observations in each category using a count plot.

Løsning

Switch to desktopSkift til skrivebord for at øve i den virkelige verdenFortsæt der, hvor du er, med en af nedenstående muligheder
Var alt klart?

Hvordan kan vi forbedre det?

Tak for dine kommentarer!

Sektion 5. Kapitel 2
Switch to desktopSkift til skrivebord for at øve i den virkelige verdenFortsæt der, hvor du er, med en af nedenstående muligheder
Vi beklager, at noget gik galt. Hvad skete der?
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