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Challenge 5: Adding Text to Plots | Matplotlib
Data Science Interview Challenge
course content

Course Content

Data Science Interview Challenge

Data Science Interview Challenge

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

bookChallenge 5: Adding Text to Plots

Annotating and adding textual elements to plots can provide context and clarity to the data being presented. These textual elements can:

  • Highlight specific data points or trends in the data.
  • Explain the significance of certain features of the plot.
  • Provide additional details or supplementary information that doesn't fit neatly into the x or y axis labels.

Matplotlib offers versatile text and annotation functions that allow you to place text in arbitrary positions, adjust its style, and even point to specific parts of the chart.

Enhancing your plots with appropriate textual elements ensures that the viewer can grasp the full story behind the data.

Task

Using Matplotlib, add text and annotations to a simple line plot:

  1. Label the x-axis as X-Axis and the y-axis as Y-Axis.
  2. Determine the maximum and minimum y-values from the given data and annotate these points on the plot. Also, include arrows pointing to the max and min points.
  3. Insert a textual note at the coordinate (2.45, 2) with the content 'The greatest decline', rotated at an angle of -72 degrees.

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Section 4. Chapter 5
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bookChallenge 5: Adding Text to Plots

Annotating and adding textual elements to plots can provide context and clarity to the data being presented. These textual elements can:

  • Highlight specific data points or trends in the data.
  • Explain the significance of certain features of the plot.
  • Provide additional details or supplementary information that doesn't fit neatly into the x or y axis labels.

Matplotlib offers versatile text and annotation functions that allow you to place text in arbitrary positions, adjust its style, and even point to specific parts of the chart.

Enhancing your plots with appropriate textual elements ensures that the viewer can grasp the full story behind the data.

Task

Using Matplotlib, add text and annotations to a simple line plot:

  1. Label the x-axis as X-Axis and the y-axis as Y-Axis.
  2. Determine the maximum and minimum y-values from the given data and annotate these points on the plot. Also, include arrows pointing to the max and min points.
  3. Insert a textual note at the coordinate (2.45, 2) with the content 'The greatest decline', rotated at an angle of -72 degrees.

Switch to desktopSwitch to desktop for real-world practiceContinue from where you are using one of the options below
Everything was clear?

How can we improve it?

Thanks for your feedback!

Section 4. Chapter 5
toggle bottom row

bookChallenge 5: Adding Text to Plots

Annotating and adding textual elements to plots can provide context and clarity to the data being presented. These textual elements can:

  • Highlight specific data points or trends in the data.
  • Explain the significance of certain features of the plot.
  • Provide additional details or supplementary information that doesn't fit neatly into the x or y axis labels.

Matplotlib offers versatile text and annotation functions that allow you to place text in arbitrary positions, adjust its style, and even point to specific parts of the chart.

Enhancing your plots with appropriate textual elements ensures that the viewer can grasp the full story behind the data.

Task

Using Matplotlib, add text and annotations to a simple line plot:

  1. Label the x-axis as X-Axis and the y-axis as Y-Axis.
  2. Determine the maximum and minimum y-values from the given data and annotate these points on the plot. Also, include arrows pointing to the max and min points.
  3. Insert a textual note at the coordinate (2.45, 2) with the content 'The greatest decline', rotated at an angle of -72 degrees.

Switch to desktopSwitch to desktop for real-world practiceContinue from where you are using one of the options below
Everything was clear?

How can we improve it?

Thanks for your feedback!

Annotating and adding textual elements to plots can provide context and clarity to the data being presented. These textual elements can:

  • Highlight specific data points or trends in the data.
  • Explain the significance of certain features of the plot.
  • Provide additional details or supplementary information that doesn't fit neatly into the x or y axis labels.

Matplotlib offers versatile text and annotation functions that allow you to place text in arbitrary positions, adjust its style, and even point to specific parts of the chart.

Enhancing your plots with appropriate textual elements ensures that the viewer can grasp the full story behind the data.

Task

Using Matplotlib, add text and annotations to a simple line plot:

  1. Label the x-axis as X-Axis and the y-axis as Y-Axis.
  2. Determine the maximum and minimum y-values from the given data and annotate these points on the plot. Also, include arrows pointing to the max and min points.
  3. Insert a textual note at the coordinate (2.45, 2) with the content 'The greatest decline', rotated at an angle of -72 degrees.

Switch to desktopSwitch to desktop for real-world practiceContinue from where you are using one of the options below
Section 4. Chapter 5
Switch to desktopSwitch to desktop for real-world practiceContinue from where you are using one of the options below
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