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Lære Challenge 4: Handling Missing Values | NumPy
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

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Challenge 4: Handling Missing Values

Managing gaps in your datasets is a task that no data scientist can overlook. In this area, NumPy offers an extensive set of tools. Whether it's detecting, removing, or filling missing values, NumPy has functionalities tailored to handle these tasks with ease.

Employing NumPy's capabilities in handling missing values not only refines your datasets but also paves the way for a more robust and reliable analysis, a cornerstone in data science undertakings.

Opgave

Swipe to start coding

Sometimes, datasets might have missing or non-numeric values. Handle them efficiently with numpy.

  1. Check for the presence of NaN values. Set True if NaN exists, False if not.
  2. Replace NaN values with 0.

Løsning

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Var alt klart?

Hvordan kan vi forbedre det?

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Sektion 2. Kapitel 4
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book
Challenge 4: Handling Missing Values

Managing gaps in your datasets is a task that no data scientist can overlook. In this area, NumPy offers an extensive set of tools. Whether it's detecting, removing, or filling missing values, NumPy has functionalities tailored to handle these tasks with ease.

Employing NumPy's capabilities in handling missing values not only refines your datasets but also paves the way for a more robust and reliable analysis, a cornerstone in data science undertakings.

Opgave

Swipe to start coding

Sometimes, datasets might have missing or non-numeric values. Handle them efficiently with numpy.

  1. Check for the presence of NaN values. Set True if NaN exists, False if not.
  2. Replace NaN values with 0.

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 2. Kapitel 4
Switch to desktopSkift til skrivebord for at øve i den virkelige verdenFortsæt der, hvor du er, med en af nedenstående muligheder
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