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Intermediate Python

Histogram

  • Explore dataset
  • Get idea about distribution

Matplotlib

import matplotlib.pyplot as plt

import matplotlib.pyplot as plt
help(plt.hist)
Hidden output 
values = [0,0.6,1.4,1.6,2.2,2.5,2.6,3.2,3.5,3.9,4.2,6]
plt.hist(values, bins = 3)
plt.show()

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!".
# Import the course packages
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt

# Import the two datasets
gapminder = pd.read_csv("datasets/gapminder.csv")
brics = pd.read_csv("datasets/brics.csv")

Data visualization

  • Many Options
  1. Different plot types
  2. Many customizations
  • Choice depends on
  1. Data
  2. Story you want to tell
# Basic plot
import matplotlib.pyplot as plt
year = [1950,1951,1952, 2100]
pop = [2.538, 2.57, 2.62 , 10.05]

#Add more data
year = [1800, 1850, 1900] + year
pop = [1.0, 1.262, 1.650] + pop

plt.plot(year, pop)

plt.xlabel('Year')
plt.ylabel('Population')
plt.title('World Population Projections')
plt.yticks([0,2,4,6,8,10],
           ['0','2B','4B','6B','8B','10B'])
plt.show()

Dictionaries

# List

pop = [30.55,2.77,39.21]
countries = ["afghanistan", "albania", "algeria"]
ind_alb = countries.index("albania")
ind_alb
pop[ind_alb]
  • Not convenient
  • Not intuitive
# Dictionary
pop = [30.55,2.77,39.21]
countries = ["afghanistan", "albania", "algeria"]

...

world = {"afghanistan":30.55, "albania":2.77, "algeria":39.21}
world["albania"]

# Definition of dictionary
europe = {'spain':'madrid', 'france':'paris', 'germany':'berlin', 'norway':'oslo' }

# Print out the keys in europe

print(europe.keys())

# Print out value that belongs to key 'norway'

print(europe['norway'])
# Recap
world = {"afghanistan":30.55, "albania":2.77, "algeria":39.21}
world["albania"]
world = {"afghanistan":30.55, "albania":2.77, "algeria":39.21, "albania":2.81}
world
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