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Python Data Science Toolbox (Part 2)

Run the hidden code cell below to import the data used in this course.

# Import the course packages
import pandas as pd
import matplotlib.pyplot as plt

# Import the course datasets 
world_ind = pd.read_csv('datasets/world_ind_pop_data.csv')
tweets = pd.read_csv('datasets/tweets.csv')

Explore Datasets

Use the DataFrames imported in the first cell to explore the data and practice your skills!

  • Create a zip object containing the CountryName and CountryCode columns in world_ind. Unpack the resulting zip object and print the tuple values.
  • Use a list comprehension to extract the first 25 characters of the text column of the tweets DataFrame provided that the tweet is not a retweet (i.e., starts with "RT").
  • Create an iterable reader object so that you can use next() to read datasets/world_ind_pop_data.csv in chunks of 20.

List Comprehension

# list comprehension of a simple list

doctor = ['house', 'cuddy', 'chase', 'thirteen', 'wilson']

new_doc = [doc[0] for doc in doctor]

print(new_doc)

# We can build a list comprehension of a single object.

jean = '2350'
 
new_jean = [j[0] for j in jean]

print(new_jean)

# Create list comprehension: squares
squares = [i**2 for i in range(0,9)]

print(squares)


matrix = [[col for col in range(0,5)] for row in range(0,5)]

for row in matrix:
   print(matrix)
# Create a list of strings: fellowship
fellowship = ['frodo', 'samwise', 'merry', 'aragorn', 'legolas', 'boromir', 'gimli']

# Create list comprehension: new_fellowship
new_fellowship = [member for member in fellowship if len(member) >= 7]

# Print the new list
print(new_fellowship)
# Create a list of strings: fellowship
fellowship = ['frodo', 'samwise', 'merry', 'aragorn', 'legolas', 'boromir', 'gimli']

# Create list comprehension: new_fellowship
new_fellowship = [member if len(member) >= 7 else member.replace(member,"") for member in fellowship]

# Print the new list
print(new_fellowship)
# Create a list of strings: fellowship
fellowship = ['frodo', 'samwise', 'merry', 'aragorn', 'legolas', 'boromir', 'gimli']

# Create dict comprehension: new_fellowship
new_fellowship = {member : len(member) for member in fellowship }

# Print the new dictionary
print(new_fellowship)

Generator Expressions

Generator Expressions work with () instead of []. The output that we obtain is the same as list comprehensions but in this case is not a list, it is a generator object that allow us to generate different values or lists.

# List of strings
fellowship = ['frodo', 'samwise', 'merry', 'aragorn', 'legolas', 'boromir', 'gimli']

# List comprehension
fellow1 = [member for member in fellowship if len(member) >= 7]

# Generator expression
fellow2 = (member for member in fellowship if len(member) >= 7)
print(fellow2)
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