Axis scales (linear, log) in Matplotlib - Cheat Sheet & Quick Revision

Recall & Review

beginner

What does a linear axis scale represent in a plot?

A linear axis scale shows data points spaced evenly according to their actual values. For example, the distance between 1 and 2 is the same as between 4 and 5.

beginner

What is a logarithmic (log) axis scale?

A log axis scale spaces data points based on the logarithm of their values. This means equal distances represent equal ratios, not equal differences. It helps show data that changes exponentially.

beginner

How do you set a logarithmic scale on the y-axis in matplotlib?

Use the command plt.yscale('log') after plotting your data to change the y-axis to a logarithmic scale.

intermediate

Why might you choose a log scale over a linear scale?

You choose a log scale when data covers a wide range or grows exponentially. It makes it easier to see patterns and compare values that differ by large amounts.

intermediate

What happens if you try to use a log scale with zero or negative values?

Log scales cannot display zero or negative values because logarithms of these numbers are undefined. You must remove or adjust such data before using a log scale.

Which matplotlib command sets the x-axis to a logarithmic scale?

A plt.yscale('log')

B plt.xscale('log')

C plt.axis('log')

D plt.scale('log')

Use plt.xscale('log') to set the x-axis to logarithmic scale.

What kind of data is best visualized with a log scale?

A Data that grows exponentially or covers many orders of magnitude

B Data with negative values

C Data with only zero values

D Data with small range and linear growth

Log scales help visualize data that grows exponentially or spans large ranges.

What will happen if you plot zero values on a log scale axis?

A They will appear at zero

B They will be shown as negative values

C They will cause an error or not display

D They will be converted to one

Logarithms of zero are undefined, so zero values cause errors or are not shown on log scales.

Which axis scale spaces values evenly by their actual difference?

A Linear scale

B Logarithmic scale

C Exponential scale

D Categorical scale

Linear scales space values evenly by their actual difference.

How do you switch back to a linear scale on the y-axis in matplotlib?

A plt.scale('linear')

B plt.yaxis('linear')

C plt.axis('linear')

D plt.yscale('linear')

Use plt.yscale('linear') to set the y-axis back to linear scale.

Explain the difference between linear and logarithmic axis scales and when to use each.

Think about how distances between numbers appear on each scale.

Describe how to set a logarithmic scale on an axis using matplotlib and what to watch out for.

Recall the matplotlib commands and data requirements.