Beta
Intermediate Python
Run the hidden code cell below to import the data used in this course.
Take Notes
Add notes about the concepts you've learned and code cells with code you want to keep.
Import numpy as np
import numpy as np
Store pop as a numpy array: np_pop
np_pop=np.array(pop)
Double np_pop
np_pop=np_pop*2
Update: set s argument to np_pop
plt.scatter(gdp_cap, life_exp, s=np_pop)
Previous customizations
plt.xscale('log') plt.xlabel('GDP per Capita [in USD]') plt.ylabel('Life Expectancy [in years]') plt.title('World Development in 2007') plt.xticks([1000, 10000, 100000],['1k', '10k', '100k'])
Display the plot
plt.show()
List = indexed by range of numbers Dictionary = indexed by keys
Print out the capital of France
print(europe['france']['capital'])
# Add your code snippets here
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!".