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Oppiskele Challenge 1: Visualizing Distributions | Seaborn
Data Science Interview Challenge
course content

Kurssisisältö

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 1: Visualizing Distributions

Understanding how data is distributed is fundamental in the data analysis process. Distributions help us to visualize the central tendencies, variability, and the presence of any outliers in our dataset. Seaborn, a statistical plotting library built on top of Matplotlib, provides a suite of tools that makes visualizing distributions a breeze.

The various plots and tools under Seaborn's distribution utilities can:

  • Examine the distribution of a dataset.
  • Visualize the relationship between multiple variables.
  • Display the underlying probability distributions of datasets.

Using Seaborn to create distribution plots ensures that the viewer can get a comprehensive view of the data's distribution and its characteristics.

Tehtävä

Swipe to start coding

Using Seaborn, visualize the distribution of a dataset:

  1. Plot a univariate distribution of data using a histogram and overlay it with a kernel density estimate (KDE).
  2. Visualize the bivariate distribution between two variables using a scatter plot and include a KDE plot to see the data's density.

Ratkaisu

Switch to desktopVaihda työpöytään todellista harjoitusta vartenJatka siitä, missä olet käyttämällä jotakin alla olevista vaihtoehdoista
Oliko kaikki selvää?

Miten voimme parantaa sitä?

Kiitos palautteestasi!

Osio 5. Luku 1
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book
Challenge 1: Visualizing Distributions

Understanding how data is distributed is fundamental in the data analysis process. Distributions help us to visualize the central tendencies, variability, and the presence of any outliers in our dataset. Seaborn, a statistical plotting library built on top of Matplotlib, provides a suite of tools that makes visualizing distributions a breeze.

The various plots and tools under Seaborn's distribution utilities can:

  • Examine the distribution of a dataset.
  • Visualize the relationship between multiple variables.
  • Display the underlying probability distributions of datasets.

Using Seaborn to create distribution plots ensures that the viewer can get a comprehensive view of the data's distribution and its characteristics.

Tehtävä

Swipe to start coding

Using Seaborn, visualize the distribution of a dataset:

  1. Plot a univariate distribution of data using a histogram and overlay it with a kernel density estimate (KDE).
  2. Visualize the bivariate distribution between two variables using a scatter plot and include a KDE plot to see the data's density.

Ratkaisu

Switch to desktopVaihda työpöytään todellista harjoitusta vartenJatka siitä, missä olet käyttämällä jotakin alla olevista vaihtoehdoista
Oliko kaikki selvää?

Miten voimme parantaa sitä?

Kiitos palautteestasi!

Osio 5. Luku 1
Switch to desktopVaihda työpöytään todellista harjoitusta vartenJatka siitä, missä olet käyttämällä jotakin alla olevista vaihtoehdoista
Pahoittelemme, että jotain meni pieleen. Mitä tapahtui?
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