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Intermediate Python

Run the hidden code cell below to import the data used in this course.

1 hidden cell

Take Notes

Add notes about the concepts you've learned and code cells with code you want to keep.

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Explore Datasets

Use the DataFrames imported in the first cell to explore the data and practice your skills!

  • Create a loop that iterates through the brics DataFrame and prints "The population of {country} is {population} million!".
  • Create a histogram of the life expectancies for countries in Africa in the gapminder DataFrame. Make sure your plot has a title, axis labels, and has an appropriate number of bins.
  • Simulate 10 rolls of two six-sided dice. If the two dice add up to 7 or 11, print "A win!". If the two dice add up to 2, 3, or 12, print "A loss!". If the two dice add up to any other number, print "Roll again!".

The first thing we'll need are random generators, so we can simulate the die. You need to import numpy, and inside numpy, there is the random package. Inside that package we find the "rand" function. Let's try it out: we get a random number between zero and one. How was this random number created? Well, computers typically generate so-called pseudo-random numbers. Those are random numbers that are generated using a mathematical formula, starting from a random seed. This seed was chosen by Python when we called the rand function, but you can also set this manually. Suppose we set it to 123, just a number I chose, like this, and then call the rand function twice. We get two random numbers.