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Logarithmic Scale

In some cases, data can span several orders of magnitude, making it difficult to visualize on a linear scale. A logarithmic scale can help by compressing the data so that it's easier to understand.

For example, at LockedIn we have influencers with follower counts ranging from 1 to 1,000,000,000. If we want to plot the follower count of each influencer on a graph, it would be difficult to see the differences between the smaller follower counts. We can use a logarithmic scale to compress the data so that it's easier to visualize.

Assignment

Write a function log_scale(data, base) that takes a list of positive numbers data, and a logarithmic base, and returns a new list with the logarithm of each number in the original list, using the given base.

You may want to use the math.log() function.

Example:

log_scale([1, 10, 100, 1000], 10)
# Output: [0.0, 1.0, 2.0, 3.0]

log_scale([1, 2, 4, 8], 2)
# Output: [0.0, 1.0, 2.0, 3.0]