data-science-from-scratch/chapter_03/visualization.py at master · cbare/data-science-from-scratch · GitHub

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"""
Visualization

Code from Chapter 3 of Data Science from Scratch
"""
import matplotlib.pyplot as plt


# ------------------------------------------------------------
# line plot - GPD
# ------------------------------------------------------------

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

# create a line chart, years on x-axis, gdp on y-axis
plt.plot(years, gdp, color='green', marker='o', linestyle='solid')
# add a title
plt.title("Nominal GDP")
# add a label to the y-axis
plt.ylabel("Billions of $")
plt.show()


# ------------------------------------------------------------
# bar chart - academy awards
# ------------------------------------------------------------

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

# bars are by default width 0.8, so we'll add 0.1 to the left coordinates # so that each bar is centered
xs = [i + 0.1 for i, _ in enumerate(movies)]

# plot bars with left x-coordinates [xs], heights [num_oscars]
plt.bar(xs, num_oscars, align='center')

plt.ylabel("# of Academy Awards")
plt.title("My Favorite Movies")

# label x-axis with movie names at bar centers
plt.xticks([i + 0.1 for i, _ in enumerate(movies)], movies)

plt.show()


# ------------------------------------------------------------
# histogram
# ------------------------------------------------------------

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

def decile(grade): return grade // 10 * 10

histogram = Counter(decile(grade) for grade in grades)

plt.bar([x for x in histogram.keys()],
        height=histogram.values(),
        width=8,
        align='center')
plt.axis([-5, 105, 0, 5])
plt.xticks([10 * i for i in range(11)])
plt.xlabel("Decile")
plt.ylabel("# of Students")
plt.title("Distribution of Exam 1 Grades")
plt.show()


# ------------------------------------------------------------
# misleading bar chart
# ------------------------------------------------------------

# huge
mentions = [500, 505]
years = [2013, 2014]
plt.bar(years, mentions, 0.8)
plt.xticks(years)
plt.ylabel("# of times I heard someone say 'data science'")
plt.axis([2012.5,2014.5,499,506])
plt.title("Look at the 'Huge' Increase!")
plt.show()

# not so huge
plt.bar(years, mentions, 0.8)
plt.xticks(years)
plt.ylabel("# of times I heard someone say 'data science'")
plt.axis([2012.5,2014.5,0,550])
plt.title("Not So Huge Anymore")
plt.show()


# ------------------------------------------------------------
# line plot - bias-variance tradeoff
# ------------------------------------------------------------

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.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()