Notice: This page requires JavaScript to function properly.
Please enable JavaScript in your browser settings or update your browser.
Apprendre Challenge 3: Subplots | Matplotlib
Data Science Interview Challenge
course content

Contenu du cours

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 3: Subplots

With Matplotlib, not only can you create diverse and intricate visualizations, but you can also effectively organize and display multiple plots together using subplots and advanced layout management techniques. Grasping these techniques can offer multiple advantages:

  • Comparison: By visualizing multiple plots side by side, you can make quicker comparisons and observations.
  • Organization: Rather than having multiple separate figures, you can combine related visualizations into one cohesive figure.
  • Flexibility: Matplotlib allows for a high degree of customization when it comes to positioning and aligning subplots, ensuring your visualizations are both functional and aesthetically pleasing.

Mastering subplots and layout management is pivotal for conveying multi-faceted insights and constructing comprehensive visual narratives.

Note

Some subplots have been intentionally left empty.

Tâche

Swipe to start coding

Using Matplotlib, perform the following tasks related to subplots and layout management:

  1. Create a 2x2 grid of subplots.
  2. Plot a line graph on the top-left subplot.
  3. Plot a scatter plot on the bottom-right subplot.

Solution

Switch to desktopPassez à un bureau pour une pratique réelleContinuez d'où vous êtes en utilisant l'une des options ci-dessous
Tout était clair ?

Comment pouvons-nous l'améliorer ?

Merci pour vos commentaires !

Section 4. Chapitre 3
toggle bottom row

book
Challenge 3: Subplots

With Matplotlib, not only can you create diverse and intricate visualizations, but you can also effectively organize and display multiple plots together using subplots and advanced layout management techniques. Grasping these techniques can offer multiple advantages:

  • Comparison: By visualizing multiple plots side by side, you can make quicker comparisons and observations.
  • Organization: Rather than having multiple separate figures, you can combine related visualizations into one cohesive figure.
  • Flexibility: Matplotlib allows for a high degree of customization when it comes to positioning and aligning subplots, ensuring your visualizations are both functional and aesthetically pleasing.

Mastering subplots and layout management is pivotal for conveying multi-faceted insights and constructing comprehensive visual narratives.

Note

Some subplots have been intentionally left empty.

Tâche

Swipe to start coding

Using Matplotlib, perform the following tasks related to subplots and layout management:

  1. Create a 2x2 grid of subplots.
  2. Plot a line graph on the top-left subplot.
  3. Plot a scatter plot on the bottom-right subplot.

Solution

Switch to desktopPassez à un bureau pour une pratique réelleContinuez d'où vous êtes en utilisant l'une des options ci-dessous
Tout était clair ?

Comment pouvons-nous l'améliorer ?

Merci pour vos commentaires !

Section 4. Chapitre 3
Switch to desktopPassez à un bureau pour une pratique réelleContinuez d'où vous êtes en utilisant l'une des options ci-dessous
We're sorry to hear that something went wrong. What happened?
some-alt