Intermediate Python

# Print the last item from year and pop
print(year)
print(pop)


# Import matplotlib.pyplot as plt
import matplotlib.pyplot as plt

# Make a line plot: year on the x-axis, pop on the y-axis
plt.plot(year, pop)

# Display the plot with plt.show()
plt.show()

# Change the line plot below to a scatter plot
plt.scatter(gdp_cap, life_exp)

# Put the x-axis on a logarithmic scale
plt.xscale('log')

# Show plot
plt.show()

# Import package
import matplotlib.pyplot as plt

# Build Scatter plot
plt.scatter(pop, life_exp)

# Show plot
plt.show()

# Build histogram with 5 bins
plt.hist(life_exp, bins=5)

# Show and clean up plot
plt.show() #DASAR BIKIN 1 HISTOGRAM SAMPE SINI AJA
plt.clf() #TAPI KALO MAU BIKIN LAGI LANJUT KE SINI. INI BUAT CLEAN DAN START DATA

# Build histogram with 20 bins
plt.hist(life_exp, bins=20)

# Show and clean up again
plt.show()
plt.clf()

# Scatter plot
plt.scatter(gdp_cap, life_exp)

# Previous customizations
plt.xscale('log') 
plt.xlabel('GDP per Capita [in USD]')
plt.ylabel('Life Expectancy [in years]')
plt.title('World Development in 2007')

# Definition of tick_val and tick_lab
tick_val = [1000, 10000, 100000]
tick_lab = ['1k', '10k', '100k']

# Adapt the ticks on the x-axis
plt.xticks(tick_val, tick_lab)

# After customizing, display the plot
plt.show()

dict = {'Asia':'red',
    'Europe':'green',
    'Africa':'blue',
    'Americas':'yellow',
    'Oceania':'black'}
# Specify c and alpha inside plt.scatter()
plt.scatter(x = gdp_cap, y = life_exp, s = np.array(pop) * 2, c = col, alpha = 0.8)
#ALPHA = OPACITY. SEMAKIN DEKET KE 1 SEMAKIN KERENG
# 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'])

# Show the plot
plt.show()