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Intermediate Python

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

1 hidden cell

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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!".
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DataFrameas
events_per_city
variable
SELECT v.venuecity, COUNT(e.eventid) AS event_count
FROM event e
JOIN venue v ON e.venueid = v.venueid
GROUP BY v.venuecity
ORDER BY event_count DESC
LIMIT 20;
import plotly.express as px

events_per_city = pd.DataFrame({
    'venuecity': ['New York City', 'Los Angeles', 'Las Vegas', 'Chicago', 'San Francisco', 'Washington', 'Houston', 'Detroit', 'Boston', 'Baltimore', 'Denver', 'Seattle', 'Minneapolis', 'St. Louis', 'Toronto'],
    'event_count': [2647, 312, 300, 209, 194, 164, 155, 152, 144, 142, 136, 136, 131, 127, 120]
})

fig = px.bar(events_per_city, x='venuecity', y='event_count', title='Top 20 Cities by Number of Events', labels={'venuecity': 'City', 'event_count': 'Number of Events'})
fig.show()