visualization.py

from matplotlib import pyplot as plt
from collections import Counter

years = [1950, 1960, 1970, 1980, 1990, 2000, 2010]
gdp = [300.2, 543.3, 1075.9, 2862.5, 5979.6, 10289.7, 14958.3]

plt.plot(years, gdp, color='green', marker='o', linestyle='solid')
plt.title("Nominal GDP")
plt.ylabel("Billions of $")
plt.show()


####
# Bar Charts
movies = ["Annie Hall", "Ben-Hur", "Casablanca", "Gandhi", "West Side Story"]
num_oscars = [5, 11, 3, 8, 10]

# plot bars with left x-coordinates [0,1,2,3,4], height [num_oscars]
plt.bar(range(len(movies)), num_oscars)

plt.title("My Favorite Movies") # add a title
plt.ylabel("# of Academy Awards") # label the y-axis

# label x-axis with movies names at bar centers
plt.xticks(range(len(movies)), movies)

plt.show()


####
# Histograms
grades = [83, 95, 91, 87, 70, 0, 85, 82, 100, 67, 73, 77, 0]

# Bucket grades by decile, but put 100 in with the 90s
histogram = Counter(min(grade // 10 * 10, 90) for grade in grades)

plt.bar([x + 5 for x in histogram.keys()], # Shift bars right by 5
        histogram.values(),                # Give each bar its correct height
        10,                                # Give each bar a width of 10
        edgecolor=(0,0,0))                 # Black edges for each bar

plt.axis([-5, 105, 0, 5])                  # x-axis from -5 to 105
                                           # y-axis from 0 to 5

plt.xticks([10 * i for i in range(11)])    # x-axis labels at 0, 10, ..., 100
plt.xlabel("Decile")
plt.ylabel("# of Students")
plt.title("Distribution of Exam 1 Grades")
plt.show()

mentions = [500, 505]
years = [2017, 2018]

plt.bar(years, mentions, 0.8)
plt.xticks(years)
plt.ylabel("# of times I heard someone say 'data science'")

# if you don't do this, matplotlib will label the x-axis 0, 1
# and then add a +2.013e3 off in the corner (bad matplotlib!)
plt.ticklabel_format(useOffset=False)


plt.axis([2016.5, 2018.5, 499, 506])
plt.title("look at the Huge Increase!")
plt.show()

# without misleading axis
plt.bar(years, mentions, 0.8)
plt.xticks(years)
plt.ylabel("# of times I heard someone say 'data science'")

plt.ticklabel_format(useOffset=False)
plt.axis([2016.5, 2018.5, 0, 550])
plt.title("Not so huge anymore")
plt.show()


####
# Line Charts
variance = [1, 2, 4, 8, 16, 32, 64, 128, 256]
bias_squared = [256, 128, 64, 32, 16, 8, 4, 2, 1]
total_error = [x + y for x, y in zip(variance, bias_squared)]
xs = [i for i, _ in enumerate(variance)]

# We can make multiple calls to plt.plot
# to show multiple series on the same chart
plt.plot(xs, variance, 'g-', label='variance')       # green solid line
plt.plot(xs, bias_squared, 'r-.', label='bias^2')    # red dot-dashed line
plt.plot(xs, total_error, 'b:', label='total error') # blue dotted line

# Because we've assigned labels to each series,
# we can get a legend for free (loc=9 means "top center")
plt.legend(loc=9)
plt.xlabel("model complexity")
plt.xticks([])
plt.title("The Bias-Variance Tradeoff")
plt.show()


####
# Scatterplots
friends = [ 70, 65, 72, 63, 71, 64, 60, 64, 67]
minutes = [175, 170, 205, 120, 220, 130, 105, 145, 190]
labels = ['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h', 'i']

plt.scatter(friends, minutes)

# label each point
for label, friend_count, minute_count in zip(labels, friends, minutes):
  plt.annotate(label,
               xy=(friend_count, minute_count), # Put the label with its point
               xytext=(5, -5),                  # but slightly offset
               textcoords='offset points')
  
plt.title("Daily Minutes vs. Number of Friends")
plt.xlabel('# of friends')
plt.ylabel("daily minutes spent on the site")
plt.show()

test_1_grades = [ 99, 90, 85, 97, 80]
test_2_grades = [100, 85, 60, 90, 70]

plt.scatter(test_1_grades, test_2_grades)
plt.title("Axes Aren't Comparable")
plt.xlabel("test 1 grade")
plt.ylabel("test 2 grade")
plt.show()

test_1_grades = [ 99, 90, 85, 97, 80]
test_2_grades = [100, 85, 60, 90, 70]

plt.scatter(test_1_grades, test_2_grades)
plt.title("Axes Aret Comparable")
plt.axis("equal")
plt.xlabel("test 1 grade")
plt.ylabel("test 2 grade")
plt.show()