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Line plot (1)

With matplotlib, you can create a bunch of different plots in Python. The most basic plot is the line plot. A general recipe is given here.

import matplotlib.pyplot as plt
plt.plot(x,y)
plt.show()

In the video, you already saw how much the world population has grown over the past years. Will it continue to do so? The world bank has estimates of the world population for the years 1950 up to 2100. The years are loaded in your workspace as a list called year, and the corresponding populations as a list called pop.

This course touches on a lot of concepts you may have forgotten, so if you ever need a quick refresher, download the Python Cheat Sheet and keep it handy!

This is a part of the course

“Intermediate Python”

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Exercise instructions

  • print() the last item from both the year and the pop list to see what the predicted population for the year 2100 is. Use two print() functions.
  • Before you can start, you should import matplotlib.pyplot as plt. pyplot is a sub-package of matplotlib, hence the dot.
  • Use plt.plot() to build a line plot. year should be mapped on the horizontal axis, pop on the vertical axis. Don't forget to finish off with the plt.show() function to actually display the plot.

Hands-on interactive exercise

Have a go at this exercise by completing this sample code.

# Print the last item from year and pop



# Import matplotlib.pyplot as plt


# Make a line plot: year on the x-axis, pop on the y-axis


# Display the plot with plt.show()
Edit and Run Code

This exercise is part of the course

Intermediate Python

BeginnerSkill Level
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Level up your data science skills by creating visualizations using Matplotlib and manipulating DataFrames with pandas.

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Data visualization is a key skill for aspiring data scientists. Matplotlib makes it easy to create meaningful and insightful plots. In this chapter, you’ll learn how to build various types of plots, and customize them to be more visually appealing and interpretable.

Exercise 1: Basic plots with MatplotlibExercise 2: Line plot (1)
Exercise 3: Line Plot (2): InterpretationExercise 4: Line plot (3)Exercise 5: Scatter Plot (1)Exercise 6: Scatter plot (2)Exercise 7: HistogramExercise 8: Build a histogram (1)Exercise 9: Build a histogram (2): binsExercise 10: Build a histogram (3): compareExercise 11: Choose the right plot (1)Exercise 12: Choose the right plot (2)Exercise 13: CustomizationExercise 14: LabelsExercise 15: TicksExercise 16: SizesExercise 17: ColorsExercise 18: Additional CustomizationsExercise 19: Interpretation

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